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But I find that very hard to believe given the fact that no one here demonstrates to me that they know the first thing about what Creation Science is.
Creation science is christian apologetics.
In comparison, evolution is an applied science.
Take, for example, phylogenomics.
With all of the genomic information pouring in from DNA sequencers across the globe there is a real need to make sense of these long runs of A, T, C, and G's. Guess what they use to make sense of this information? You guessed it, evolution.
How? Evolution produces a signal in genomes. That signal is conservation. When a DNA sequence starts to serve a function and a purpose it is built upon by future generations. This causes DNA sequences, and specific bases, to be conserved through generations. By comparing the genomes of species through the lens of evolutionary distance one can identify these conserved sequences. This allows you to assign a probable function to an unknown DNA sequence. This is exactly what scientists have done using a computer algorithm called SIFTER. With just a little information this algorithm, using the theory of evolution, is able to predict protein function with 96% accuracy.
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PLoS Comput Biol. 2005 Oct;1(5):e45. Epub 2005 Oct 7.
Protein molecular function prediction by Bayesian phylogenomics.
Engelhardt BE, Jordan MI, Muratore KE, Brenner SE.
Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, United States of America. bee@cs.berkeley.edu
We present a statistical graphical model to infer specific molecular function for unannotated protein sequences using homology. Based on phylogenomic principles, SIFTER (Statistical Inference of Function Through Evolutionary Relationships) accurately predicts molecular function for members of a protein family given a reconciled phylogeny and available function annotations, even when the data are sparse or noisy. Our method produced specific and consistent molecular function predictions across 100 Pfam families in comparison to the Gene Ontology annotation database, BLAST, GOtcha, and Orthostrapper. We performed a more detailed exploration of functional predictions on the adenosine-5'-monophosphate/adenosine deaminase family and the lactate/malate dehydrogenase family, in the former case comparing the predictions against a gold standard set of published functional characterizations. Given function annotations for 3% of the proteins in the deaminase family, SIFTER achieves 96% accuracy in predicting molecular function for experimentally characterized proteins as reported in the literature. The accuracy of SIFTER on this dataset is a significant improvement over other currently available methods such as BLAST (75%), GeneQuiz (64%), GOtcha (89%), and Orthostrapper (11%). We also experimentally characterized the adenosine deaminase from Plasmodium falciparum, confirming SIFTER's prediction. The results illustrate the predictive power of exploiting a statistical model of function evolution in phylogenomic problems. A software implementation of SIFTER is available from the authors.
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(Also notice that I site peer reviewed sources when I claim that evolution is science. I expect the same when you claim that "creation science" is science.)
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