Genome complexity: only computers can unravel (Introduction)

by David Turell , Sunday, December 08, 2019, 21:41 (1594 days ago) @ David Turell

To find all the patterns and layers in DNA it requires massiv e computer analysis:

http://cshl.nautil.us/article/488/making-sense-of-the-genome-at-last?utm_source=Nautilu...

"The presenter of a TED talk—a biologist named Riccardo Sabbatini [went] onto the stage to explain the staggering amount of information in the human genetic code. As people began to applaud, five assistants emerged from the wings, wheeling carts containing 175 encyclopedia-size books onto the stage...inside those books were 262,000 pages containing the 3 billion DNA letters of the eminent man’s genome—“the visual perception of the code of life.” The audience gasped when Sabbatini cracked open one of the books: Even stretched out over 175 volumes, the letters had to be written so small that each page resembled a black square filled with dots.

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"Now, software-literate computational biologists are harnessing advances in machine learning and data mining to begin to do what the human mind alone could not. They are running comparisons between individuals and between species, seeking out meaningful patterns. They are identifying which portions of the genome, when mutated, are most likely to cause disease. And some have begun applying new analytical tools to saving lives.

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"...it fell to Siepel to design a program that transformed the cross-species comparison into a searchable database. The goal was to let researchers around the globe type in specific genetic sequences and receive a result predicting how likely that sequence was to have some functional importance. Kent and his team reasoned that if a certain chunk of DNA appears nearly the same across divergent species—if it is “highly conserved,” in genetics terminology—it must crucial for life.

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"Siepel’s LINSIGHT project will be important in filling in information about the whole of the human genome, not just the 1 percent that has a well-understood biological function. Meanwhile, intolerance scoring will help by identifying the parts of the human genome that are most likely to be associated with disease—based entirely on computer-driven data analysis, without any human assumptions or biases in the mix. Goldstein thinks that scientists will need to compile and compare genes from millions of people before an AI can usefully analyze your whole genetic makeup, identify problems, and point to specific treatments.

“'So for those of us who consider ourselves informed experts in the interpretation of genomic variation, I think we still have jobs for at least five plus years,” he says. After that, though, an even greater revolution awaits."

Comment: No natural process could invent the DNA code, as complex as it is just to designate protein production, but it also has underlying significant patterns as a deeper set of layers. If the clever human mind cannot do it by itself and it requires super computers, the conclusion must be that it required a super mind by as super designer.