linkstream2 microblog

https://www.quantamagazine.org/new-theory-cracks-open-the-black-box-of-deep-learning-20170921

New Theory Cracks Open the Black Box of Deep Learning

https://www.technologyreview.com/s/610221/this-new-company-wants-to-sequence-your-genome-and-let-you-share-it-on-a-blockchain/?utm_campaign=add_this&utm_source=twitter&utm_medium=post

What to expect in ’18: science in the new year
https://www.Nature.com/articles/d41586-018-00009-5 Insights from cancer & ancient #genomes. Cures from #CRISPR. Progress in
#OpenAccess. Also, lots on outer space. But nothing on #cryoEM, #DeepLearning, #QuantumComputing or the brain connectome. HT @OBahcall

The Future of DNA Seq.
http://www.Nature.com/news/the-future-of-dna-sequencing-1.22787 Apps v Tech. QT: “Platforms for…#sequencing have changed dramatically…Yet the trajectories of other technologies…Internet, digital
photography…suggest…real disrupters will be the resulting applications, not the new tech”

QT:{{”
Killer applications –
Over the years, the platforms for DNA sequencing have changed dramatically (see ”). Yet the trajectories of other technologies for which there is a seemingly insatiable demand — smartphones, the Internet, digital photography — suggest that the real disrupters will be the resulting applications, not the new technologies.

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QT:{{"
"Wikipedia is one of the world’s most popular websites, but scientists rarely cite it in their papers. Despite this, the online encyclopedia seems to be shaping the language that researchers use in papers, according to an experiment showing that words and phrases in recently published Wikipedia articles subsequently appeared more frequently in scientific papers"
…
“Thompson and co-author Douglas Hanley, an economist at the University of Pittsburgh in Pennsylvania, commissioned PhD students to write 43 chemistry articles on topics that weren’t yet on Wikipedia. In January 2015, they published a randomized set of half of the articles to the site. The other half, which served as control articles, weren’t uploaded.
…
Using text-mining techniques to measure the frequency of words, they found that the language in the scientific papers drifted over the study period as new terms were introduced into the field. This natural drift equated to roughly one new term for every 250 words, Thompson told Nature. On top of those natural changes in language over time, the authors found that, on average, another 1 in every 300 words in a scientific paper was influenced by language in the Wikipedia article.”

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#Wikipedia shapes lang. in science https://www.Nature.com/news/wikipedia-shapes-language-in-science-papers-1.22656 Seeding it with new pages & watching them evolve (v ctrls) as a type of soc. expt

Cryo-EM wins chem Nobel
http://www.Nature.com/news/cryo-electron-microscopy-wins-chemistry-nobel-1.22738 Key techdev work in ’80s on flash freezing + atomic res. imaging of xtal & unordered samples

Big names in #statistics want to shake up…#Pvalue
http://www.Nature.com/news/big-names-in-statistics-want-to-shake-up-much-maligned-p-value-1.22375 Stronger significance cutoffs (.005?) but danger of FNs

QT:{{”
“Lowering P-value thresholds may also exacerbate the “file-drawer problem”, in which studies with negative results are left unpublished, says Tom Johnstone, a cognitive neuroscientist at the University of Reading, UK. But Benjamin says all research should be published, regardless of P value.

…
Other scientific fields have already cracked down on P values — and in 2015, one psychology journal banned them. Particle physicists, who collect reams of data from atom-smashing experiments, have long demanded a P value below 0.0000003 (or 3 × 10−7) because of concerns that a lower threshold could lead to mistaken claims, notes Valen Johnson, a statistician at Texas A&M University in College Station and a co-lead author of the paper. More than a decade ago, geneticists took similar steps to establish a threshold of 5 × 10−8 for
genome-wide association studies, which look for differences between people with a disease and those without across hundreds of thousands of DNA-letter variants.”
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.@Genome_Gov Extramural Grant Portfolio
https://www.Genome.Gov/27569006/july-6-2017-the-nhgri-extramural-grant-portfolio-using-different-approaches-to-fund-genomics-research Nice grid divides programs into PI-initiated/consortia & RFA-solicited v not

QT:{{"
“The NCI will continue to supply the NCI-60 cell lines to researchers, but will eventually refocus its drug screening on newer models. It is developing hundreds of ‘patient-derived xenografts’ (PDXs), which are created by implanting small chunks of human tumours into mice. There, the tumours grow in an environment that, although not human, better mimics their native environment”
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Clues from the resilient
http://www.ScienceMag.org/content/344/6187/970.full Potential 2nd site mutations that neutralize #Mendelian-disease mutations

QT:{{”
“For 127 catastrophic Mendelian diseases (those caused by a single gene such as cystic fibrosis and ataxia-telangiectasia), there are presently 164 genes harboring 685 known recurrent variants that are highly penetrant and causal for deleterious traits, most typically manifesting in individuals before the age of 18 (). …For common diseases, the observed small effect sizes of individual gene variants limit diagnostic potential, and given that most variants identified have an unclear function, how to target the corresponding gene for therapeutic intervention is typically unclear. For rarer Mendelian disorders, although genetics directly implicate a specific gene in a disease, a majority of such cases relate to loss-of-function mutations. Designing small molecules to fix the corresponding broken protein has proven difficult….
The prominent role of second-site mutations and environmental factors that enable resistance to (or buffer against) disease traits has been well established in a multitude of model organisms from yeast to mice (–). Screening for second-site mutations in “resilient” individuals that prevent disease-causing alleles from manifesting their effects could identify targets to which drugs would be designed to disrupt their function, as opposed to targeting the disease-causing gene directly. Genetic studies examining seemingly healthy people have revealed, for example, rare mutations in chemokine (C-C motif) receptor type 5 (the co-receptor for human immunodeficiency virus) that block HIV infection (), and secondary mutations in fetal globin genes that modify the severity of sickle cell disease by buffering primary mutations in β-globin genes ()
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