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What further research can the result of gene variation detection be used for

What further research can the result of gene variation detection be used for


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We do a research on a particular cancer (for e.g. breast cancer). Now, we have a result for the gene variation detection (VCF file). What next steps do we need to do? We don't have a clear picture about this. Can you give us some directions or few papers as an example? (of course it is a huge number but just mention a few). Thanks!


Leveraging genomics to uncover the genetic, environmental and age-related factors leading to asthma

Brian D. Modena , . Varshini Sathish , in Genomic and Precision Medicine (Third Edition) , 2019

Candidate gene association studies

Candidate gene association studies look at the genetic variation associated with disease within a limited number of pre-specified genes. Candidate gene studies are typically structured as case control studies. Cases of disease and controls are first identified, and then genetic differences determined, i.e., identifying variants (SNPs, haplotypes, indels, CNVs) found more commonly in one group or the other. Results are typically reported as odds ratios (ORs) or relative risks (RRs), depending on whether the study was structured as a case control or cross-sectional study, respectively.

Whereas genome wide association studies (GWAS) investigate genetic variants spanning the entire genome, candidate gene studies limit the analysis to a relatively few number of genes. As a result, candidate gene studies have increased statistical power to detect differences. They are also unavoidably biased toward genes and biological pathways of “interest,” i.e., candidate genes are hand-picked by investigators based on scientific interest (i.e., functional candidate) or based on chromosomal position (i.e., positional candidate). As a result, the candidate gene variants discovered may be given undue attention.

Nonetheless, many candidate gene studies were performed and identified hundreds of genetic variants associated with asthma. The results were summarized in several review articles [94–96] , and will not be repeated here. One review of 500 candidate gene studies showed that 25 genes have been associated with asthma in 6 or more populations, including T2 inflammatory response genes (IL13, IL4, IL4RA, STAT6), the IgE receptor (FCER1B), a coreceptor for bacterial lipopolysaccharide that is preferentially expressed on monocytes and macrophages (CD14), a prostanoid receptor to thromboxane (TXAR2), two MHC class II genes (HLA-DRB1, HLA-DQB1), glutathione-S-transferases (LTC4S, GSTM1, GSTP1), pro-inflammatory products (TNF, CCL5, NOD1, LTA) and proteins responsible for immune suppression (IL10, TGFB1, CTLA4). ADAM33, which encodes a metalloproteinase expressed in airway smooth muscles and lung fibroblasts and likely involved in airway remodeling [97] , was one of the first gene variants discovered by a candidate gene study in a Caucasian population [98] . ADAM33 polymorphisms were reproducibly associated with asthma [99–101] and a more rapid decline in postbronchodilator forced expiratory volume in 1 s (FEV1) [102] in subsequent studies. As a result, ADAM33 has garnered much attention over the years [103] Yet, the exact mechanism by which ADAM33 variants increase susceptibility to asthma was never elucidated and its locus was not identified as an asthma susceptibility locus in any of the major subsequent genome wide association studies (GWAS).Thus, ADAM33 serves as cautionary tale where preliminary genetic findings may lead researchers down fruitless pathways.

Several additional weaknesses of gene candidate studies are worth mentioning. Another difficulty with candidate gene studies is that differences in population substructures may result in the detection of alleles that differ between case and control, but are unrelated to disease. Moreover, the number of genetic roots underlying asthma is unknown and could be numerous given its heterogeneity. Therefore, the likelihood of identifying a common causative variant among a small population of asthmatics, as was the case for most gene candidate studies, may be unpredictably low. Finally, gene candidate studies had often limited the analysis to the protein-coding regions of genes and neglected how neighboring genes and introns affect gene expression or epigenetics of candidate genes. For these reasons and others, the accuracy and importance of the early candidate gene association studies are now questioned.


Impact of Genetic Variation on Diagnostic Tests

The presence of SARS-CoV-2 genetic variants in a patient sample can potentially change the performance of the SARS-CoV-2 test. Molecular tests designed to detect multiple SARS-CoV-2 genetic targets are less susceptible to the effects of genetic variation than tests designed to detect a single genetic target. The FDA reminds clinical laboratory staff and health care providers about the risk of false negative results with all laboratory tests, including molecular tests. No test is perfect. Laboratories should expect some false results to occur even when very accurate SARS-CoV-2 tests are used. The prevalence of genetic variants may vary in any population and may lead to more false negative results than otherwise expected.


Over the course of history a majority of plants, including crops have duplicated their genome to reproduce. By duplicating their genome the plant gives two or more copies of instructions to rebuild itself. A study out of Purdue and Harvard University is starting to untangle the genetic mechanisms which allow these plants to duplicate their genome the goal is to improve on the length of time it takes to breed crops such as banana, cotton, canola, strawberry, peanuts, wheat and many others. Current breeding programs that use new polyploids (an organism with three or more genomes) are cumbersome because many of the crops don’t reproduce easily.

Brian Dikes an assistant professor of horticulture at Purdue University and co-author of the published study explains “The machinery that divides the genome during sex is designed to pull paired chromosomes apart and create two cells from one. When you have four chromosomes to work with, they aren’t always divided correctly. “What this paper demonstrates is that we can use evolution as a tool to find the genes that allow plants to tolerate being tetraploids, which have four copies of their genomes.” Researchers found a species which reproduce as both a diploid and tetraploid – Arabidopsis arenosa, a cousin of the standard research plant Arabidopsis thaliana. By comparing the DNA sequences of the whole genomes of plants, they detected the genetic differences between the tetraploid and diploid versions of the species.

Many genes known to play a role in meiosis, or cell division, were different in the tetraploids as compared to the diploids. In particular, the gene Asynaptic1, which controls the organization of chromosome pairs during reproduction, was mutated in tetraploids. Of the plants tested, 95 percent of the tetraploids shared the same mutation in Asynaptic1, while 95 percent of the diploids did not contain this variant. This suggests that the mutation in Asynaptic1 is involved in the adaptation of the meiotic machinery needed to work with four copies of the genome.

“We’re actually learning the mechanisms that were used in evolution to solve challenges faced by plants dealing with tetraploidy,” Dilkes said. “With this understanding we will be able to manipulate crops and crop relatives to accelerate plant breeding and the inclusion of a wider genetic base in the improvement of many existing crops.” Dilkes’ laboratory at Purdue was involved in analyzing the DNA of each plant tested to determine whether it was a diploid or tetraploid. He said the work would continue to determine which genes and mutations allow for sexual reproduction in tetraploid plants.

Kirsten Bomblies, an assistant professor of organismic and evolutionary biology at Harvard and principal investigator for the project, said the results are also important for human health. “Several of the genes have been shown to be critical for survival of tetraploid, but not diploid yeast, and they are also implicated in human polyploid cancers and genome instability syndromes,” Bomblies said. More information: Genetic Adaptation Associated with Genome-Doubling in Autotetraploid Arabidopsis arenosa, Jesse D. Hollister, Brian J. Arnold, Elisabeth Svedin, Katherine S. Xue, Brian P. Dilkes, Kirsten Bomblies, PLoS Genetics. Genome duplication, which results in polyploidy, is disruptive to fundamental biological processes.

Genome duplications occur spontaneously in a range of taxa, and problems such as sterility, aneuploidy and gene expression aberrations are common in newly formed polyploids. In mammals, genome duplication is associated with cancer and spontaneous abortion of embryos. Nevertheless, stable polyploid species occur in both plants and animals. Understanding how natural selection enabled these species to overcome early challenges can provide important insights into the mechanisms by which core cellular functions can adapt to perturbations of the genomic environment. Arabidopsis arenosa includes stable tetraploid populations and is related to well-characterized diploids A. lyrata and A. thaliana. It thus provides a rare opportunity to leverage genomic tools to investigate the genetic basis of polyploid stabilization. We sequenced the genomes of 12 A. arenosa individuals and found signatures suggestive of recent and ongoing selective sweeps throughout the genome. Many of these are at genes implicated in genome maintenance functions, including chromosome cohesion and segregation, DNA repair, homologous recombination, transcriptional regulation and chromatin structure. Numerous encoded proteins are predicted to interact with one another. For a critical meiosis gene, ASYNAPSIS1, we identified a non-synonymous mutation that is highly differentiated by cytotype, but present as a rare variant in diploid A. arenosa, indicating selection may have acted on standing variation already present in the diploid. Several genes we identified that are implicated in sister chromatid cohesion and segregation are homologous to genes identified in a yeast mutant screen as necessary for survival of polyploid cells and also implicated in genome instability in human diseases, including cancer. This points to commonalities across kingdoms and supports the hypothesis that selection has acted on genes controlling genome integrity in A. arenosa as an adaptive response to genome doubling.


Archaeology: The milk revolution

When a single genetic mutation first let ancient Europeans drink milk, it set the stage for a continental upheaval.

In the 1970s, archaeologist Peter Bogucki was excavating a Stone Age site in the fertile plains of central Poland when he came across an assortment of odd artefacts. The people who had lived there around 7,000 years ago were among central Europe's first farmers, and they had left behind fragments of pottery dotted with tiny holes. It looked as though the coarse red clay had been baked while pierced with pieces of straw.

Looking back through the archaeological literature, Bogucki found other examples of ancient perforated pottery. “They were so unusual — people would almost always include them in publications,” says Bogucki, now at Princeton University in New Jersey. He had seen something similar at a friend's house that was used for straining cheese, so he speculated that the pottery might be connected with cheese-making. But he had no way to test his idea.

Free podcast

Mark Thomas talks about human evolution and the rise of dairying.

The mystery potsherds sat in storage until 2011, when Mélanie Roffet-Salque pulled them out and analysed fatty residues preserved in the clay. Roffet-Salque, a geochemist at the University of Bristol, UK, found signatures of abundant milk fats — evidence that the early farmers had used the pottery as sieves to separate fatty milk solids from liquid whey. That makes the Polish relics the oldest known evidence of cheese-making in the world 1 .

Roffet-Salque's sleuthing is part of a wave of discoveries about the history of milk in Europe. Many of them have come from a €3.3-million (US$4.4-million) project that started in 2009 and has involved archaeologists, chemists and geneticists. The findings from this group illuminate the profound ways that dairy products have shaped human settlement on the continent.

During the most recent ice age, milk was essentially a toxin to adults because — unlike children — they could not produce the lactase enzyme required to break down lactose, the main sugar in milk. But as farming started to replace hunting and gathering in the Middle East around 11,000 years ago, cattle herders learned how to reduce lactose in dairy products to tolerable levels by fermenting milk to make cheese or yogurt. Several thousand years later, a genetic mutation spread through Europe that gave people the ability to produce lactase — and drink milk — throughout their lives. That adaptation opened up a rich new source of nutrition that could have sustained communities when harvests failed.

This two-step milk revolution may have been a prime factor in allowing bands of farmers and herders from the south to sweep through Europe and displace the hunter-gatherer cultures that had lived there for millennia. “They spread really rapidly into northern Europe from an archaeological point of view,” says Mark Thomas, a population geneticist at University College London. That wave of emigration left an enduring imprint on Europe, where, unlike in many regions of the world, most people can now tolerate milk. “It could be that a large proportion of Europeans are descended from the first lactase-persistent dairy farmers in Europe,” says Thomas.

Young children almost universally produce lactase and can digest the lactose in their mother's milk. But as they mature, most switch off the lactase gene. Only 35% of the human population can digest lactose beyond the age of about seven or eight (ref. 2). “If you're lactose intolerant and you drink half a pint of milk, you're going to be really ill. Explosive diarrhoea — dysentery essentially,” says Oliver Craig, an archaeologist at the University of York, UK. “I'm not saying it's lethal, but it's quite unpleasant.”

Most people who retain the ability to digest milk can trace their ancestry to Europe, where the trait seems to be linked to a single nucleotide in which the DNA base cytosine changed to thymine in a genomic region not far from the lactase gene. There are other pockets of lactase persistence in West Africa (see Nature 444, 994–996 2006 ), the Middle East and south Asia that seem to be linked to separate mutations 3 (see 'Lactase hotspots').

The single-nucleotide switch in Europe happened relatively recently. Thomas and his colleagues estimated the timing by looking at genetic variations in modern populations and running computer simulations of how the related genetic mutation might have spread through ancient populations 4 . They proposed that the trait of lactase persistence, dubbed the LP allele, emerged about 7,500 years ago in the broad, fertile plains of Hungary.

Once the LP allele appeared, it offered a major selective advantage. In a 2004 study 5 , researchers estimated that people with the mutation would have produced up to 19% more fertile offspring than those who lacked it. The researchers called that degree of selection “among the strongest yet seen for any gene in the genome”.

Compounded over several hundred generations, that advantage could help a population to take over a continent. But only if “the population has a supply of fresh milk and is dairying”, says Thomas. “It's gene–culture co-evolution. They feed off of each other.”

To investigate the history of that interaction, Thomas teamed up with Joachim Burger, a palaeogeneticist at the Johannes Gutenberg University of Mainz in Germany, and Matthew Collins, a bioarchaeologist at the University of York. They organized a multidisciplinary project called LeCHE (Lactase Persistence in the early Cultural History of Europe), which brought together a dozen early-career researchers from around Europe.

By studying human molecular biology and the archaeology and chemistry of ancient pottery, LeCHE participants also hoped to address a key issue about the origins of modern Europeans. “It's been an enduring question in archaeology — whether we're descended from Middle Eastern farmers or indigenous hunter-gatherers,” says Thomas. The argument boils down to evolution versus replacement. Did native populations of hunter-gatherers in Europe take up farming and herding? Or was there an influx of agricultural colonists who outcompeted the locals, thanks to a combination of genes and technology?

One strand of evidence came from studies of animal bones found at archaeological sites. If cattle are raised primarily for dairying, calves are generally slaughtered before their first birthday so that their mothers can be milked. But cattle raised mainly for meat are killed later, when they have reached their full size. (The pattern, if not the ages, is similar for sheep and goats, which were part of the dairying revolution.)

On the basis of studies of growth patterns in bones, LeCHE participant Jean-Denis Vigne, an archaeozoologist at the French National Museum of Natural History in Paris, suggests that dairying in the Middle East may go all the way back to when humans first started domesticating animals there, about 10,500 years ago 6 . That would place it just after the Middle Eastern Neolithic transition — when an economy based on hunter-gathering gave way to one devoted to agriculture. Dairying, says Roz Gillis, also an archaeozoologist at the Paris museum, “may have been one of the reasons why human populations began trapping and keeping ruminants such as cattle, sheep and goats”. (See 'Dairy diaspora'.)

Dairying then expanded in concert with the Neolithic transition, says Gillis, who has looked at bone growth at 150 sites in Europe and Anatolia (modern Turkey). As agriculture spread from Anatolia to northern Europe over roughly two millennia, dairying followed a similar pattern.

On their own, the growth patterns do not say whether the Neolithic transition in Europe happened through evolution or replacement, but cattle bones offer important clues. In a precursor study 7 , Burger and several other LeCHE participants found that domesticated cattle at Neolithic sites in Europe were most closely related to cows from the Middle East, rather than indigenous wild aurochs. This is a strong indication that incoming herders brought their cattle with them, rather than domesticating locally, says Burger. A similar story is emerging from studies of ancient human DNA recovered at a few sites in central Europe, which suggest that Neolithic farmers were not descended from the hunter-gatherers who lived there before 8 .

Taken together, the data help to resolve the origins of the first European farmers. “For a long time, the mainstream of continental European archaeology said Mesolithic hunter-gatherers developed into Neolithic farmers,” says Burger. “We basically showed they were completely different.”

Given that dairying in the Middle East started thousands of years before the LP allele emerged in Europe, ancient herders must have found ways to reduce lactose concentrations in milk. It seems likely that they did so by making cheese or yogurt. (Fermented cheeses such as feta and cheddar have a small fraction of the lactose found in fresh milk aged hard cheeses similar to Parmesan have hardly any.)

To test that theory, LeCHE researchers ran chemical tests on ancient pottery. The coarse, porous clay contains enough residues for chemists to distinguish what type of fat was absorbed during the cooking process: whether it was from meat or milk, and from ruminants such as cows, sheep and goats or from other animals. “That gave us a way into saying what types of things were being cooked,” says Richard Evershed, a chemist at the University of Bristol.

“ It's been an enduring question in archaeology — whether we're descended from Middle Eastern farmers or indigenous hunter-gatherers. ”

Evershed and his LeCHE collaborators found milk fat on pottery in the Middle Eastern Fertile Crescent going back at least 8,500 years 9 , and Roffet-Salque's work on the Polish pottery 1 offers clear evidence that herders in Europe were producing cheese to supplement their diets between 6,800 and 7,400 years ago. By then, dairy had become a component of the Neolithic diet, but it was not yet a dominant part of the economy.

That next step happened slowly, and it seems to have required the spread of lactase persistence. The LP allele did not become common in the population until some time after it first emerged: Burger has looked for the mutation in samples of ancient human DNA and has found it only as far back as 6,500 years ago in northern Germany.

Models created by LeCHE participant Pascale Gerbault, a population geneticist at University College London, explain how the trait might have spread. As Middle Eastern Neolithic cultures moved into Europe, their farming and herding technologies helped them to out-compete the local hunter-gatherers. And as the southerners pushed north, says Gerbault, the LP allele 'surfed' the wave of migration.

Lactase persistence had a harder time becoming established in parts of southern Europe, because Neolithic farmers had settled there before the mutation appeared. But as the agricultural society expanded northwards and westwards into new territory, the advantage provided by lactase persistence had a big impact. “As the population grows quickly at the edge of the wave, the allele can increase in frequency,” says Gerbault.

The remnants of that pattern are still visible today. In southern Europe, lactase persistence is relatively rare — less than 40% in Greece and Turkey. In Britain and Scandinavia, by contrast, more than 90% of adults can digest milk.

By the late Neolithic and early Bronze Age, around 5,000 years ago, the LP allele was prevalent across most of northern and central Europe, and cattle herding had become a dominant part of the culture. “They discover this way of life, and once they can really get the nutritional benefits they increase or intensify herding as well,” says Burger. Cattle bones represent more than two-thirds of the animal bones in many late Neolithic and early Bronze Age archaeological sites in central and northern Europe.

The LeCHE researchers are still puzzling out exactly why the ability to consume milk offered such an advantage in these regions. Thomas suggests that, as people moved north, milk would have been a hedge against famine. Dairy products — which could be stored for longer in colder climes — provided rich sources of calories that were independent of growing seasons or bad harvests.

Others think that milk may have helped, particularly in the north, because of its relatively high concentration of vitamin D, a nutrient that can help to ward off diseases such as rickets. Humans synthesize vitamin D naturally only when exposed to the sun, which makes it difficult for northerners to make enough during winter months. But lactase persistence also took root in sunny Spain, casting vitamin D's role into doubt.

The LeCHE project may offer a model for how archaeological questions can be answered using a variety of disciplines and tools. “They have got a lot of different tentacles — archaeology, palaeoanthropology, ancient DNA and modern DNA, chemical analysis — all focused on one single question,” says Ian Barnes, a palaeogeneticist at Royal Holloway, University of London, who is not involved in the project. “There are lots of other dietary changes which could be studied in this way.”

The approach could, for example, help to tease apart the origins of amylase, an enzyme that helps to break down starch. Researchers have suggested that the development of the enzyme may have followed — or made possible — the increasing appetite for grain that accompanied the growth of agriculture. Scientists also want to trace the evolution of alcohol dehydrogenase, which is crucial to the breakdown of alcohol and could reveal the origins of humanity's thirst for drink.

Some of the LeCHE participants are now probing further back in time, as part of a project named BEAN (Bridging the European and Anatolian Neolithic), which is looking at how the first farmers and herders made their way into Europe. Burger, Thomas and their BEAN collaborators will be in Turkey this summer, tracing the origins of the Neolithic using computer models and ancient-DNA analysis in the hope of better understanding who the early farmers were, and when they arrived in Europe.

Along the way, they will encounter beyaz peynir, a salty sheep's-milk cheese eaten with nearly every Turkish breakfast. It is probably much like the cheese that Neolithic farmers in the region would have eaten some 8,000 years ago — long before the march of lactase persistence allowed people to drink fresh milk.


EXCERPT

DeepMind's AlphaFold is an AI system built to tackle this long-standing challenge. In 2018, the initial version of AlphaFold debuted at CASP (Critical Assessment of protein Structure Prediction), a biennial worldwide event for experimenting with state-of-the-art protein structuring technologies. AlphaFold achieved the highest accuracy of the participating technologies at CASP13 in 2018, but has now been developed further into what is being labeled a "stunning advance."

The system was trained on publicly available data on around 170,000 protein structures and a large database of unknown protein structures ahead of its appearance at CASP14 this week. Technologies are graded from 0-100 for accuracy on what is known as the Global Distance test, which assesses what percentage of beads in the protein chain are within a threshold distance of the correct location. In results released today, AlphaFold scored 92.4 across all targets.

Inspired by the aims in LC/MS based comparative metabolomics, a series of approaches are developed and two tools entitled as MET-COFEA (bioinfo.noble.org/manu[. ]ofea/) and MET-XAlign (bioinfo.noble.org/manu[. ]lign/) are implemented.

MET-COFEA, being an analysis tool, can be used to extract and annotate each meaningful metabolite' associated chromatograph features from each LC-MS sample. For the extracted metabolite compound group with multiple fragment peaks, the neutral molecular mass can be deduced and the compound's representative retention time can be estimated, which can be considered as the common thing for the same metabolite across different samples and different experiment configurations, although the fragmentation pattern can vary from sample to sample, from experiment to experiment. MET-COFEA has already been successfully implemented as a pipeline tool with visualization.

MET-XAlign, being as an alignment tool, has been dedicatedly developed based on the analysis results from MET-COFEA. It mainly includes an algorithm core and user interface. The identified compounds from MET-COFEA are characterized by compound retention time and neural molecular mass deduced by multiple associated fragments' m/z value, which are represented as its unique Compound_ID.

In classical GWAS (Genome Wide Association Studies), the genetic marker variants and the phenotypic traits can be connected through the canonical LMM (Linear Mixed Model). We extended the concept of genome-wide association into a broader 'ome'-wide association. Briefly, we proposed a novel LMM and developed an online tool named PATOWAS (bioinfo.noble.org/PATOWAS/), by which we can address not only GWAS, but also TWAS (Transcriptome wide association studies), and MWAS (Metabolome wide association studies) in one unified platform. To explain more the phenotypic variation and address the missing heritability, we also proposed another new LMM and developed another association tool named PEPIS (bioinfo.noble.org/PolyGenic_QTL/), by which the polygenic effect and epistasis from marker pairs can be accounted for. Using these tools, two-dimensional (2D) GWAS that accounts for epistatic genetic effects can be mapped, which are complementary to the one-dimensional (1D) GWAS mapping, and can provide more genetic information.

Each includes interactive morph animations, and downloadable Powerpoint-ready animations. These are based on recent cryo-EM structures of multiple conformations.

A protease (typically furin, ample in the lungs) clips spike protein, inducing it to extend a receptor-binding surface to engage the ACE2 receptor on the host cell.

The mechanism of membrane fusion, which deposits the viral RNA inside the host cell initiating infection, appears similar to that of influenza hemagglutinin. The spike protein "spears" the host cell membrane, capturing it with a "fusion peptide", and pulls the virus membrane very close. Fusion has been seen in molecular dynamics simulations (see Figure 2 in the fusion link). Spike protein has a cavity that is the target of drug screening (see Figure 4 in the fusion link). A cute graphical abstract shows a 3-legged folding stool as an analogy to spike protein, with the drug-target cavity between its legs (see Figure 3 in the fusion link).

These tutorials have been cataloged at Merlot.Org: www.merlot.org/merl[. ]eated

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Scientific Confidence Model for Origins&rsquo Beliefs

Historically, since the Scopes trial in 1925, the legal debate over what to teach about origins in science school classrooms has centered on biblical creation versus evolution. With the string of defeats in the courtroom against creationism being given equal time with evolution, a newer form of opposition to evolution has arisen through the Intelligent Design (ID) movement.1 For many people who consider any type of opposition to evolution in science education a breach of &ldquoseparation of church and state,&rdquo this newer intelligent design-evolution battle often translates to an interventionist God versus Darwinism, or yet another way of stating religion versus science. Within non-theist scientific forums, the strongest model presented for biological evolution is modern Darwinism (natural selection as modified with genetics) with no scientific role seen for intelligent design. In forums like Perspectives on Science and Christian Faith, the debate has focused more on philosophical issues such as whether there is (or should be) a role for intelligent design (different from naturalism) in scientific research or education.2

As a philosophical choice, intelligent design is at least as rational an explanation of origins as is Darwinian evolution.3 Further, although Darwinism is the most widely accepted model of evolution for scientific inquiry, Booher shows its foundations are secured more on mentally pleasing perceptions and semantic arguments than on observational and experimental data.4 No long term experiments have ever shown macro-evolution to occur naturally and other convincing evidence once anticipated has not been forthcoming. Paleontology has not produced the finely connected array of fossils that Darwin expected5 biochemistry does not show homologous connections between species at the protein level6 and probabilities rule against chance having produced the complexity needed for progressively higher functions in species.7

Intelligent design, on the other hand, can explain the complexity in biology through such things as the cosmological tuning for life beginning with the Big Bang in scientific terms. For example, Darwinian gradualism says nothing scientific about the thermodynamic interface of precursors to the origins of life, species, and the human mind. None of these origins is thermodynamically plausible from the energy available in speculated precursors.8 Estimations of the increases in complexity to create novelty from precursors can, however, be specified in terms of intelligent information.9

Yet Darwinism continues to be more acceptable to most scientists (including theists) than intelligent design as a model for origins science. The general perception is that Darwinism, even if bad science, is still science whereas, intelligent design, even if highly logical, is still religion, not science.10 The difficulty of advancing intelligent design or creationism as an alternative to Darwinism (as science, not philosophy) cannot be overemphasized, so long as this perception exists not only within the scientific community at large, but among scientific theists as well.

Booher suggests that systems psychology may offer some fresh insight into this issue for scientific theists.11 If so it would be primarily in helping address the following needs: (1) the need for a practical understanding of the phenomenon for intelligent people to prefer a non-verified (even falsified) scientific hypothesis over a logical, highly plausible explanation for origins and (2) the need for a practical strategy to correct any psychological errors associated with this phenomenon. In order to begin to address these needs, we must first get out of the hopeless cycle of "evolution versus creation," and begin to assess the value of specific areas of scientific inquiry in advancing knowledge about origins in other words to find a way to better assess the scientific confidence we can place on various scientific approaches and claims to answer questions about origins. In order to qualify as science, intelligent design must do more than find fault with Darwinism it must suggest scientific research on questions that are distinct from those suggested by evolution. Further it must provide hypotheses that are capable of being verified (or falsified) with the scientific method as is already true with Darwinism.

This paper proposes we return to the strengths of the scientific method and assess origins science in specific terms for specific limited scientific issues, rather than continuing to put the vast majority of Christian intellectual resources into a winner-take-all-fashion that pits grand philosophical theories against one another other in a way that may actually be impeding scientific progress in defining origins.

Levels of Confidence

Perhaps one of the most important statements on the philosophy of science ever made by Carl Sagan was his declaration: &ldquoNot all scientific statements have equal weight.&rdquo12 Here and in his other writings Sagan recognized the scientific method as centermost in distinguishing the relative value of the numerous scientific pronouncements. To have high confidence in the truth of any particular statement, one needs to know to what degree some of the higher techniques of science, like hypothesis formulation, controlled experimentation, direct observation, repeatability, falsifiability were applied.

Scientific levels of confidence can discriminate among the findings of physicists. Today we can be very confident the earth is round and know its exact size. Before Columbus thinkers had erroneous theories about both shape and size. Leucippus and Democritus postulated atoms in the sixth century BC but not until the beginning of the twentieth century were we sure of the existence of atoms and certain elemental particles. We can be highly confident in knowing the structure of the genetic code and the existence of genes whereas knowledge when or how life began has very low scientific confidence. We also have relatively low confidence at our current state of knowledge in the truth of the GUT (Grand Unified Theory) or time of cosmological beginnings. That does not mean theories of low scientific confidence have been proven false. Eventually some or perhaps many of them may eventually be shown to be correct. But currently we are on solid ground in being as skeptical of such ideas as we wish.

While philosophers may debate on whether or not there is such a thing as &ldquotruth&rdquo or &ldquocertainty,&rdquo within science pragmatic tests for truth can be defined. A thing or event or process is more or less certain to the degree anyone in the world can repeatedly find it to be true when he or she take actions assuming it to be true. Every technological development that is successfully applied to everyday use is based on scientific principles that are true. Every time we turn on a light, or fly an airplane, or operate a computer, we personally verify the underlying physics principles that were used in developing that technology. On the other hand, ideas science has shown to be absolutely false, such as perpetual motion machines, spontaneous generation, or a flat earth are to be discarded entirely. They may have been valid hypotheses for investigation at one time, but every scientific experiment and every observation ever made on these topics conclusively show they are not only inconsistent with proven principles but have no incontestable examples in their favor.

There are, of course, many ideas that lie along the scale from absolutely false to completely certain. These are potential candidates for scientific investigation in the quest to acquire certain knowledge. But not all questions or ideas are amenable to scientific verification. In fact, most are not. According to Mortimer Adler, science must remain silent on questions raised in moral or political philosophy, as well as matters covered through philosophical analysis. Moreover, he would say, science has no business in any of the metaphysics (those questions raised about nature, mind, and theology which cannot be answered by empirical investigation).13 Fortunately there are methods outside the scientific realm that can give us greater or less confidence in their truth. Philosophers and theologians can apply these other methods. There can be a filtering back and forth of method and thought among the three domains, but the fundamental strengths of each in determining certainty of statements are unique. In philosophy it is logical discourse in theology it is the revealed word in science it is the scientific method of investigation. Of the three, only science has shown truth with the confidence that everyone accepts. Because of this there is a tendency to err in thinking all statements of science on any topic have greater weight than non-scientific statements. But as Carl Sagan has correctly said, not all scientific statements have equal weight. Further, science cannot make valid statements about all things of human interest. Mortimer Adler argues that even such a question of what the subatomic world is like (determinate or indeterminate) is not answered and routinely claimed the domain of quantum physics is answerable, if at all, only by philosophy.14

Scientific Confidence Model 15

Based on the considerations raised above, can the scientific community make greater strides in assuring real progress is made in the knowledge of origins? What follows is a pragmatic proposal for a three-stage scientific confidence model that is applicable to all science, not just origins science. It is origins science in particular however that suggests the need for such a model. By evaluating origins science using the model for general science, it is relatively easy to see the various strengths and weaknesses of specific claims of origins scientists. To the degree any particular study or idea on origins can be made to fit the model a relative scale of confidence can be attributed to the study or idea. For example, even if a study is well executed, confidence can only reach the maximum allowable by the category under which it fits. Poorly executed studies, of course, should have their results discarded regardless of the category.

The model shown in Figure 1 comprises three types of activities (stages) arranged in order from left to right for increasing potential to establish scientific confidence.

Processing Rules:

1. Ideas can initially appear in any stage, move between stages or skip stages in either direction. To be investigated in any particular stage, however, they must meet the minimal criteria for the stage. For example, an idea may start in stage 2 or 3 from unexpected test results, but if it cannot be tested it must move back to stage 1. This example is represented graphically in Figure 1 by the arrows labeled III? where one arrow is an output from stage III and others are feedback inputs to stages I and II. Similarly questions from stage II can feedback to stage I. (see arrows labeled II?).

2. Verifiable hypotheses must be formulated in order to advance an idea beyond stage 1. As shown in Figure 1 hypotheses (see arrows I. Hyp II. Hyp.) are shown feeding subsequent stages. Hypotheses can also be generated and tested within stages. Questions may feedback, but hypotheses are attempts to progress to higher levels of confidence.

3. Independent findings may strengthen confidence within a stage of examination but do not in themselves increase confidence beyond the stage of examination. For example, great coherence of logic from numerous independent concepts in stage 1 does not raise scientific confidence to the level of subsequent stages or even allow the ideas to be investigated at the higher stages if no testable hypotheses are generated.

4. The stage of examination does not necessarily reflect the level of scientific confidence that will ultimately be determined. For example, an idea like the flat earth can qualify for stage 3 but upon falsification should disappear entirely as a scientific question.

Figure 1. Scientific Confidence Model. The confidence that can be attributed to any idea capable of being investigated by the scientific method varies from low to high. The level of confidence can increase depending on the stage of scientific activity whether I. Creativity, II. Analytical Representation or III. Reality Verification. Scientific creativity is most distinct from philosophy when the mental activity results in scientific hypotheses. Analytical representation advance confidence through models and simulations. Reality verification is accomplished with descriptive and experimental science.


Stage I: Creativity.

This first stage of scientific activity is where ideas are generated and fleshed out by thinking. Rational thought is certainly involved in putting structure to an idea, but it is not necessary for generation of all ideas or even most discoveries. Concepts that come from inspiration, imagination, intuition, and instinct (an sometimes, just plain luck) are not unusual at this stage. In fact W.I.B. Beveridge in his now classic book on The Art of Scientific Investigation says &ldquodiscoveries originate more often from unexpected experimental results or observations, or from intuitions, than directly from logical thought.&rdquo16 It is activity at this stage that often motivates scientists to be scientists, where discovery planned or accidental is always possible, such that imagining it happening, even vicariously, excites and stimulates to such a degree that it is difficult to compare with other human motivators.

This stage is closest to the other intellectual domains of philosophy and theology. For origins science, ideas of naturalism and intelligent design may be stimulated from philosophy. From theology may come ideas of a pantheistic or monotheistic cause for the universe. As ideas become more mature, such critical scientific methodologies as hypothesis formulation and prediction of observations become applicable. An idea never leaves this stage with a confidence higher than that from philosophy, no matter how much thought has gone into it, or how great the consensus gained from other thinkers, until a hypothesis or a prediction is made concerning it. Only then can the idea be tested at the other stages. Even an accidental discovery that came about by pure luck or a speculative urge that suggested where to look, say at finding a new star or new cure for cancer, must be verified by tests in the latter activities. One cannot know whether a new star or a new cure has been found without comparing with what is already known about astronomy and medicine. If a testable hypothesis is not or cannot be formed and the idea is not discarded on logical grounds, then the idea is doomed to continually circulate back and forth between philosophy and science at its lowest confidence level. Consensus on speculations and correlation with other suggestions, even highly mathematical ones, do not advance the idea significantly toward high scientific confidence.

Stage II: Analytical Representation.

The special art of scientific investigation begins at this stage. The two types of investigation that collect empirical data in a way that distinguishes them from the first stage of science and all of philosophy are the empirical sciences and historical research. Pure historical research of natural history (which performs no experiments) is technically not within the domain of science,17 but an exception is made for origins science where the overlap in modes of investigation is great and contributions can be easily made from one to the other.

Scientific thinking employs rational thought to a very high degree in the analytical stage. Beveridge completes his statement above on the importance of intuition and luck in discoveries with emphasis on the role of reason being &ldquothe principle agent in most aspects of research and the guide to most of our actions.&rdquo18 On the road toward proof, he says: &ldquoIt [reason] is the main tool in formulating hypotheses, in judging the correctness of ideas conjured up by imagination and intuition, in planning experiments and in deciding what observations to make, in assessing the evidence and interpreting new facts, in making generalizations and finally in finding extensions and applications of a discovery.&rdquo19

One novel characteristic of the middle stage of scientific confidence development is that it is here where the investigator makes models and simulations of the reality he or she wishes to better understand. In making analytical models and simulations, the investigator often needs to consider a very large number of factors in combination. Hunches and imagination still play a role in identifying potential variables to study but precision and completeness are necessary to successfully model complex processes. One may be able to find large factors that account for most of the variance in a process but this requires correlational methodology to show which factors are important and which are not. The invention of the computer has allowed far more variables to be included and allows greater ability to verify accuracy of models. For example, if a computer model can be developed which considers all the major factors assumed to be operating in a process like speciation, it could be useful in testing assumed evolutionary effects of Darwinian natural selection.

Scientific rigor increases significantly during stage II. Hypothesis formulation and predictions are routine. For many questions, repeatability and falsifiability are features that can now be applied. Any mathematical models or simulations employed are presented in such a way as to have their assumptions carefully scrutinized. Simulations need to closely replicate a possible prebiological environment if their results are to increase confidence that this is how life started. Also independent methods of verifying assumptions are part of the scientific method at this stage. It is difficult to advance the evolutionary concepts of population biology and cosmology beyond stage I if they depend solely upon mathematical speculations without independent corroboration. When theistic scientists develop simulations or models that meet the criteria of stage II, they too need to present independent methods of verification. For example when creationist Gerald Aardsma wished to verify his model for radiometric time dating based on a catastrophic flood model, he used the independent method of tree rings for correlation. Since the result was highly correlated, he provided a model that was of greater scientific confidence than those based on stage I speculations.20

Although greater scientific confidence can be established at the analytical stage than the creativity one, the situation can arise where more than one model is offered to explain the same process. This is particularly troublesome, as in origins science, where the underlying assumptions differ considerably. As with developing a model originally, the best criterion for selection between competing models is reality verification by controlled experiment or direct observation. In the development of flight simulators for pilots, for example, human performance can be tested in the real world and the simulation adjusted until fidelity is excellent. For models or simulations of origins, this kind of verification is not possible. The next best option is selecting the model that best correlates with other known laws of reality, as for example, the laws of thermodynamics, genetics, or gravity.

Stage III: Reality Verification.

Two categories of scientific activity are included in the third stage. Both are necessary and valid for operations at the highest confidence level since both can help prove assumptions about reality. First is the more routine work of descriptive science. Activities like species classification and world mapping are not only exact but essential science. Where would astronomy or geography be were it not for the mappers of the stars and maps of the early explorers? Today geology may be finding a return to greater descriptive activity by including catastrophe.

The other category of activity for stage III includes those observations and experiments that have the primary purpose of verifying theoretical predictions. The distinguishing feature in both categories is that the scientist actually sees (directly with the senses or with instruments) something that can be recorded for others to verify independently.
Observation in the last stage of scientific confidence development provides something more than the formal mathematical confidence that can accrue in the other stages. Although pure mathematics is a very exact discipline, it is still a tool, no better no worse at providing answers to philosophical questions than the mind that employs it. Mathematics allows the rejection of inconsistent ideas and the forming of very precise hypotheses in stage I. Mathematics allows the rejection of spurious variables and the formulation of very exact and complicated models and simulations in stage II. But predictions and representational models of reality are not proven by mathematical operations. Once analytical representations are proven by observation, they can be reliably used thereafter as valid under a similar set of circumstances and assumptions. But until the mathematical nicety is verified by sky, field or laboratory observation, its underlying assumptions are still considered on weak foundation.

The highest stage of confidence is established by reality testing. In the case of theories, confirmation depends primarily on controlled experiment and direct observation of predictions. Not every idea generated or model compiled can be subjected to such rigor. But to the degree it is and found successful, not just once, but over and over again, great scientific confidence can be assigned to the idea as a definite increase in knowledge. Grand ideas like electromagnetics, genetics, thermodynamics, and gravity have repetitively met the criteria for &ldquotruth&rdquo at the highest level we know. Conversely, to date, no grand ideas or models on the origins of the universe, life, species, or appearance of the human mind have successfully exited stage III, not even once.

Application of Model to Origins Science

In order to apply the scientific confidence model to current issues in origins, it is helpful to distinguish grand ideas (like evolution and special creation) from ideas of limited extent (like micro and macro natural selection). To establish grand ideas with high scientific confidence requires extensive experimental verification from many different avenues. Ideas of limited extent however, may progress more easily. Also verification of several ideas of limited extent can increase confidence within the stage of examination. It is very tempting, however, to attempt to advance to higher stages purely on the basis of adding up disparate ideas of limited extent. For Darwinism many forms of evidence can be drawn from different fields, say biochemical, geological, mathematical, etc., and from this argue that taken in combination the evidence is so extensive that Darwinism is entitled to the scientific status that might be given to any other verified Grand idea of science. In philosophy this type of argument is likened to believing that having many buckets each with holes in them will hold more water than just one bucket with a hole. Rule 3 above provides a critical limitation on how far scientific confidence can advance from disparate forms of evidence

Another important distinction is Scientific Confidence Potential versus established Scientific Confidence. Rule 4 above was specified in order to handle this distinction. This is illustrated in Tables 1 and 2 where the categories of Grand and Limited ideas are classified for their highest potential level and their currently established confidence level.


Table 1 illustrates how the author would judge some grand ideas using the Scientific Confidence Model. [Note: When models appear plausible, but not yet developed, they are indicated by ?]. Creation and Evolution (1 and 2) are so broad that they do not have the potential to be examined even at stage I. That is, there is no testable hypothesis that can be stated to test either Grand Idea when stated so broadly. As we become more specific, with scientific ideas that infer a creator (3,4,5) or which infer purpose in nature (6) it is possible to form testable hypotheses which if successful might extend to still further verification through models. This has been done with Intelligent Design for a scientific theory of origin of life.21 With the notable exception of Intelligent Design all of the grand ideas on origins that currently compete with Darwin or Lamarck are stuck in stage I. That is, scientific hypotheses may have been formed conceptually, but not well enough to be tested even as models.

It is interesting that both Darwinism and Lamarckism (7,8) have the potential for higher scientific confidence than any of the grand ideas requiring a higher intelligence or purpose. However tests at the highest confidence level have routinely shown neither idea to be true (at least for macro evolution which is essential for a grand idea). In fact, one might consider these ideas to have been falsified by experiment therefore should be eliminated. They might have some value on a more limited scale, but not as grand theories that naturalistically explain origins.
Grand ideas like genetics, thermodynamics, gravity, and electromagnetics (10, 11, 12,13) that are neutral toward origins not only had the highest potential for confidence, but are now established at the highest scientific confidence level. Only Intelligent Design has reached the scientific confidence level stage II. The models and simulations of Intelligent Design support the hypothesis that some form of intelligence scientifically explains the origin of life. Considering that Darwinism is either at stage I or can be eliminated as a grand theory of origins, Intelligent Design remains as the best scientific explanation of the origin of life.22

Ideas like Big Bang (14) Age of the Earth (15) and Grand Unified Theory (16) that do have evolutionary implications are not capable of being verified at the highest level. They do however have the potential for model verification, and in the case of Big Bang and Age of the Earth have been independently corroborated with different models.

The last two examples, Flat Earth (17) and Sun Revolves Around The Earth (18) are illustrations of scientific theories that at one time had potential for examination at the highest level but (being completely falsified with every known tool to science) are now eliminated.

This model shows graphically why Darwinism might initially be viewed favorably over Intelligent Design as a scientific theory of origins. Potentially it ranks with genetics and gravity that have been verified at the highest level. But that is only half of the picture. When we look at theories that have been tested at the highest level, Darwinism actually ranks closer to Flat Earth. As a grand idea it has failed all scientific tests at both the analytical and reality verification stages.23 The danger of a theory being tested at the highest level is that it can fail, making it lower in confidence than theories still at the analytical verification stage.

The confidence model is encouraging for intelligent design because it shows the potential for actual scientific progress in origins science is currently higher than Darwinism. [This is true for two reasons. 1. Darwinism has failed higher level tests, 2. Intelligent design has passed higher level tests.]. Intelligent design scientific researchers have successfully specified testable models and simulations clearly distinct from Darwinian models.

Since all grand ideas on origins other than Intelligent Design seem to be stuck at the lowest level of scientific confidence, a different tact appears necessary for progress of the other competitors. One suggestion is to attend to the ideas of limited extent with concentration on moving ideas from the creativity level to the analytical representation level. Some ideas of limited extent may even be testable at the reality verification level. Intelligent Design has already accomplished some experiments at stage III24. A number of limited scientific ideas are suggested in Table 2. As with the grand ideas, the scoring indicates the author&rsquos judgment from his personal review. The reader may find considerable disagreement with these classifications, but the primary purpose of both tables is to illustrate how the scientific confidence model may be exercised in developing one&rsquos personal confidence in scientific statements. It would appear that experts in the various fields could use the model to build greater consensus on origins issues and scientific relevance, with greater independence from philosophical or religious preferences.

Implications for Research and Education

Many of the limited scientific ideas regarding origins and biological change have suggested hypotheses that have either been verified or rejected in the reality verification activities. From evolution the idea of natural selection for species variation has been demonstrated in micro and population biology. But many other ideas of evolutionary origins have been falsified. Experiments have shown no spontaneous generation. Lamarckian hypotheses have been falsified in animals. Experiments have consistently shown little encouragement that people will be able to create life or urge organisms along any theoretical evolutionary path. From theism species are found classifiable and stable, but no predictions are made on the bounds of variation within a &ldquokind.&rdquo

Currently Darwinism is the only evolutionary idea that still meets the requirement for hypothesis formulation stated in such a way to be capable of verification (or falsification). This has allowed it access to the more formal activities of the analytical and reality verification stages. Intelligent design as a grand scheme cannot reach the reality verification stage because a super intelligence cannot be evoked at will. It can however conduct experiments that give results that support intelligent design over Darwinism as best explanation of results. Most importantly however, intelligent design has met the criteria for advancing in the confidence process. They have testable hypotheses and predictions that allow testing at the analytical representation level. Moreover this testing has been done successfully. This shows Intelligent Design is fully scientific since it is capable of generating unique scientific hypotheses and models capable of corroboration.

Origins Research

One example uniquely suggested by intelligent design is research to define species. To distinguish itself from Darwinism, one theory of intelligent design sets limits to the amount of variation from natural selection and other random change mechanisms. It can ask research questions therefore on the limits of change that exist in species and can search for a more exact biological definition of what a species is.25 Another example is described by Gordon Mills who offers a unique theory of theistic evolution. His view is that &ldquoin the history of the origin and development of living organisms, at various levels of organization, there has been a continuing provision of new genetic information by an intelligent cause.&rdquo26 The macroevolutionary fossil trail essentially documents the &ldquoprovision of new genetic information.&rdquo Mills&rsquo view allows for both intelligent design and evolutionary chance to have operated in the past. Especially important for theistic science is that Mills&rsquo theory suggests a positive approach to scientific research that is not bound to the naturalistic model. For example, he is not required to assume initial simplicity. &ldquoAn intelligent cause could have provided genetic information for whatever degree of complexity that was necessary.&rdquo27 Consequently in molecular evolution he would not search for simpler structures of enzymes, membranes or genetic codes to better understand the fundamental life processes. Rather he would start by trying to understand aspects of the complexity preexisting each evolutionary change (for example, complex developmental genes) and then search not only for how the developmental genes could be switched on and off to effect changes in form, but also look for some new genetic information to account for each major evolutionary change.28

The systems approach to origins science offers many research opportunities, from the biochemical level, where the function and structure of precursor and novel systems can be defined in detail, through the specification of interfaces between such systems using information models,29 all the way up to models for integration of the sciences. All such models need to depart from solely mathematical speculations and move toward the specificity and confirmation which comes from corroboration with actual biological and physical systems. This will allow the models to progress into the analytical representation levels. For the integration of science fields based on intelligent design, a principal challenge will be to define interfaces between fields in such a way that they can be connected by information links that speak intelligibly with one another.

Origins Education

The scientific confidence model suggests science could best serve public education initially by acknowledging a generally low confidence level for almost all of its statements on biological origins. Even most analytical representation methods that could at least give moderate confidence of what happened in prehistory are poorly constructed, primarily ad hoc rather than predictive. Both private and public education school boards might be advised to search for ways to favor instruction in the scientific method over promoting scientific &ldquoenthusiasm.&rdquo Origins science can provide some very good examples of how the scientific approach can increase confidence in what we know and what we do not. Also, the history of origins science has numerous examples to help the student distinguish scientific observation from scientific interpretation. Origins science can illustrate well how a scientific contribution can be independent of the scientist&rsquos philosophical or religious interpretation. Present day taxonomic classification was started by a creationist, Linnaeus, to show biblical &ldquokinds&rdquo later appropriated by Darwinists to show evolution and adopted today by cladists who reject Darwinism.

The confidence model is silent on recommendations on what the science teacher should be required to teach. The model would support, however, those who resist attempts to constrain educators from teaching science to the best of their ability and understanding. This can be best appreciated in a past National Science Teachers Association position statement on the &ldquoTeaching of Evolution,&rdquo in which it recommends that &ldquoScience textbooks shall emphasize evolution as a unifying concept&rdquo30 and would not permit minority scientific views such as &ldquoso-called intelligent design.&rdquo The NTSA position would not even tolerate &ldquoarguments against evolution.&rdquo Moreover evolution would be Darwinian evolution since it would not allow the concept of &ldquoabrupt appearance.&rdquo Many of the topics discussed in this article illustrate the short sightedness of such an approach. As we have seen, both Darwinism and Intelligent Design have some explanatory value for science. Neither provides scientific confidence at the level of gravity or genetics. Non-Darwinian scientific models can, however, help teach the benefits of properly applying the scientific method to acquire a high level of scientific confidence in the findings of scientists. It is far better for the progress of science that the student understand how to discriminate the speculations of scientists (even if held by a majority) which give low levels of confidence from those proven by scientific investigation (which can have high scientific confidence even when demonstrated by a minority).

1. For a good example of the arguments for Intelligent Design being included in public science education see: John Angus Campbell and Stephen Meyer (eds.) Darwinism, Design, and Public Education (East Lansing, MI: Michigan State University Press, 2003). For a good presentation of the concerns that Intelligent Design is primarily religion see: Barbara Forrest and Paul R. Gross, Creationism's Trojan Horse: The Wedge of Intelligent Design (New York: Oxford University Press, 2004).

2. See for example, "Dialogue III: Intelligent Design and Naturalism," among James Madden, Mark Discher, and Howard J. Van Till, Perspectives on Science and Christian Faith 56, no. 4, (2004): 286-98.

3. See for example, Moreland, J.P. (Ed.) 1994, The Creation Hypothesis, Intervarsity Press, Downer&rsquos Grove, Ill. Jon Buell and Virginia Hearn (Eds.) 1994, Darwinism: Science or Philosophy? Foundation for Thought and Ethics, Richardson, Texas Mere Creation: Conference on Design and Origins Biola University, November 14-17, 1996 Dembski, W.A. &ldquoIntelligent Design as a Theory of Information,&rdquo Perspectives on Science and Christian Faith, September 1997, 49(3), pp. 180-190 and Meyer, Stephen, Signature in the Cell, New York:HarperOne 2009.

4. Booher, H. R., 0rigins, Icons, and Illusions: The Science and Psychology of Creation and Evolution (Warren H. Green, Inc. St. Louis, MO. 1998). See especially Chapters 3-8 and 15-16.

5. The actual status of discovered transitional fossils is so small that the inference of Darwinian gradualism is no longer held by paleontologists. Paleontologist Kurt Wise states &ldquothe total list of transitional forms is very small . compared to the total number of mosaic forms.&rdquo(in J. P. Moreland, (Ed.) 1994 The Creation Hypothesis, p. 227). Similar comments can be found throughout the paleontology literature. See, for example, David Kitts, &ldquoPaleontology and Evolutionary Theory,&rdquo Evolution, (Vol. 28, Sept. 1974 p 467) who states &ldquoDespite the bright promise that paleontology provides a means of &lsquoseeing&rsquo evolution, it has presented some nasty difficulties for evolutionists the most notorious of which is the presence of &lsquogaps&rsquo in the fossil record. Evolution requires intermediate forms between species and paleontology does not provide them. The gaps must therefore be a contingent feature of the record.&rdquo

6. Behe, M. 1996 Darwin&rsquos Black Box: Regnery Behe, M. 1994, &ldquoExperimental Support for Regarding Functional Classes of Proteins to be Functionally Isolated from Each Other,&rdquo in Jon Buell and Virginia Hearn (Eds.) Darwinism: Science or Philosophy? Foundation for Thought and Ethics, Richardson, Texas Denton, M.1986 Evolution: A Theory in Crisis, Adler and Adler.

7. Ambrose, E. J., 1982 The Nature and Origin of the Biological World, New York: Halsted Press Yockey, Hubert P., 1989, The Mathematical Foundations of Molecular Biology, New York: Cambridge Press Dembski, William 1995, &ldquoThe Design Inference: Eliminating Chance Thorough Small Probabilities,&rdquo Technical Monograph. Copy available through Foundation for Thought and Ethics, Richardson, Texas.

8. Booher, H. R., op. cit., note 3. See discussion on thermodynamics and information theory in Chapter 12: &ldquoReversing Time&rsquos Arrow&rdquo pp. 224-247).

9. Bradley, W.L. and Thaxton, C. B. 1994, &ldquoInformation and The Origin of Life,&rdquo in J.P. Moreland, The Creation Hypothesis op. cit. note 2 pp. 173-210 and Meyer (op. cit., note 3)

10. See for example, typical comments of members of the American Scientific Affiliation in Perspectives on Science and Christian Faith. William Hasker (1992, Vol. 44 (3) pp. 150-162) while not opposed to theistic interpretations of the evidence for evolution is critical of Alvin Plantinga&rsquos proposal for a theistic science, being dubious about the benefits to either Christianity or natural science. Raymond Grizzle (ibid, p.175) notes &ldquoall of modern science, not just biological evolutionary theory, by definition, excludes God. its descriptions are limited to the observable natural world."

11. Booher, H.R, &ldquoSystems Psychology and Origins Science,&rdquo Life After Materialism Conference, Biola University, December 2-5, 1999.

12. Sagan, Carl, 1977. Scientists Confront Velikovsky, New York: Norton, p. 59.

13. Adler, Mortimer J.1992. The Four Dimensions of Philosophy, New York: Macmillan, pp. 75-77.

14. Adler, Mortimer J. 1990. Truth in Religion, New York: Macmillan, p. 100.

15. Booher, H.R., op. cit., note 4, pp. 318-325.

16. Beveridge, W.I.B., 1957. The Art of Scientific Investigation, New York: Vintage (3rd Edition) p. 122.

17. Adler, op. cit., note 12, p 15.

18. Beveridge, op. cit., note 15, p. 122.

20. Aardsma, Gerald E., 1991. Radiocarbon and the Genesis Flood, Institute for Creation Research, El Cajon, CA.

23. Darwinism could be proven at the reality verification stage if three forms of evidence were produced. These are (1) experimentally producing the evolution of new species (2) discovering continuous connections between the species in the fossil record and (3) mapping detailed biochemical connections between the species. No one disputes (1) has not been shown and is no longer tried. Darwinists claim progress in (2) but the record is too poor to be convincing. Biochemists Denton and Behe (op. cit., note 6) have shown that (3) does not exist. Additionally Behe (op. cit., note 6) and Meyer (op. cit., note 3) have also shown that no detailed analyses exist to show how natural selection could produce an increase in biological complexity. No Darwinist has ever built a detailed model down to the biochemical level connecting a precursor system to a supposed evolved system.

25. Davis, Percival and Kenyon, Dean H. 1993. Of Pandas and People, Dallas, Texas: Haughton Publishing Co., p. 85.

26. Mills, Gordon C. June 1995. &ldquoA Theory of Theistic Evolution as an Alternative to the Naturalistic Theory,&rdquo Perspectives on Science and Christian Faith, Vol. 47 (2), p. 121.

27. Mills, Gordon C. June 1995. &ldquoTheistic Evolution: A Design Theory at the Level of Genetic Information, Christian Scholar&rsquos Review, pp. 1-12, p. 10.

28. Mills&rsquo theory covers such possibilities as a.) rapid diversity of species (as might follow mass extinctions) b.) macroevolutionary events requiring a number of new genes and control factors and c.) the dormant retention of genetic information until needed again hundreds, thousands, or possibly millions of years later. (Mills, ibid., p.115.)

29. It would appear some combination of Dembski&rsquos (op. cit. notes 3 and 7) Bradley and Thaxton&rsquos (op. cit., note 9) Behe&rsquos (op. cit. note 6) and Meyer&rsquos (op.cit., note 3) research on information theory, thermodynamics, and living systems specification could be used to map out systems research on interfaces between precursor and novel living systems.

30. &ldquoAn NSTA Position Statement on The Teaching of Evolution,&rdquo 1997, National Science Teachers Association Arlington, VA.


ACKNOWLEDGMENTS

This study was supported by the National Basic Research Program (973 Program) (Nos. 2010CB945401 and 2012CB911201), the National Natural Science Foundation of China (Grant Nos. 91019020, 81330055, and 31371508).

ABBREVIATIONS

3PN, tripronuclear DSB, double strand break gRNA, guide RNA IVF, in vitro fertilization HDR, homologous recombination directed repair NHEJ, non-homologous end joining PAM, protospacer adjacent motif PGD, pre-implantation genetic diagnosis SDSA, synthesis-dependent strand annealing.

COMPLIANCE WITH ETHICS GUIDELINES

Puping Liang, Yanwen Xu, Xiya Zhang, Chenhui Ding, Rui Huang, Zhen Zhang, Jie Lv, Xiaowei Xie, Yuxi Chen, Yujing Li, Ying Sun, Yaofu Bai, Zhou Songyang, Wenbin Ma, Canquan Zhou, and Junjiu Huang declare that they have no conflict of interest.

This study conformed to ethical standards of Helsinki Declaration and national legislation and was approved by the Medical Ethical Committee of the First Affiliated Hospital, Sun Yat-sen University. The patients donated their tripronuclear (3PN) zygotes for research and signed informed consent forms.


Thursday, November 29, 2012

Rhode Island to leave "Christmas" out of tree ceremony

(Reuters) - Rhode Island will go ahead with plans to hold a " holiday tree " lighting ceremony in the state capital despite controversy last year over Governor Lincoln Chafee 's decision to avoid using the word "Christmas" in reference the tree.

The announcement on Tuesday that the state would hold a tree-lighting ceremony in Providence came just 24 hours after the governor's spokeswoman said the annual event had been scrubbed. Last year, protesters interrupted the ceremony with demands the conifer be officially referred to as a " Christmas tree ."

Spokeswoman Christine Hunsinger blamed the confusion on a staff communication error and said there would in fact be a "holiday tree" lighting at an unspecified date.

"The governor has stated his position very clearly: He believes ?holiday' is more inclusive," she said. "It's in a building paid for by all Rhode Islanders."

Chafee's decision not to use the word Christmas in reference to the tree drew criticism from conservatives last year, including one state lawmaker who dubbed him "Governor Grinch." Some Christians see the trend towards "holiday" parties, cookies and trees as part of a secular drive to scrub the lexicon of references to Christmas.

The governor has argued that the term is consistent with the state's history of religious tolerance, and Hunsinger noted that Chafee's predecessor also used "holiday tree" on official invitations to the ceremonial lighting.

Rhode Island was founded as a 17th century haven for religious dissidents from England and neighbouring Massachusetts.

(Reporting by Jason McLure Editing by Paul Thomasch and Ciro Scotti)


What further research can the result of gene variation detection be used for - Biology

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Sustained increases in Factor IX (FIX) levels with mean FIX activity of 41.5 percent of normal in full study population one year following a single administration of etranacogene dezaparvovec

Held pre-BLA submission meeting with FDA and aligned on primary endpoint analysis

LEXINGTON, Mass. and AMSTERDAM, June 22, 2021 (GLOBE NEWSWIRE)

Tue, 22 Jun 2021 15:31:00 +0000

Expands uniQure’s Pipeline of Innovative Gene Therapies to Treat Neurological Disorders

Strengthens uniQure’s Global Leadership in the Development of Gene Therapies that Employ miRNA Silencing Technology


Watch the video: 25. Θνησιγόνα γονίδια και Πολλαπλά αλληλόμορφα 5 5ο κεφ. - Βιολογία Γ λυκείου (September 2022).


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