MBB intranet
October 12, 2019Visiting childhood home article
October 12, 2019J&J Hit With $8 Billion Jury Award Over Antipsychotic Drug – WSJ
October 8, 2019interesting perspective on cancer research in wsj + upcoming book
October 8, 2019The focus is on improving detection vs. treatment of late stage disease.
https://www.wsj.com/articles/cancer-is-still-beating-uswe-need-a-new-start-11570206319
Yamna culture – Wikipedia
October 8, 2019QT:{{”
The Yamna people or Yamnaya culture (traditionally known as the Pit Grave culture or Ochre Grave culture) was a late Copper Age to early Bronze Age culture of the region between the Southern Bug, Dniester and Ural rivers (the Pontic steppe), dating to 3300–2600 BC.[2] The Yamna culture is identified with the late Proto-Indo-Europeans, and is the strongest candidate for the Urheimat (homeland) of the
Proto-Indo-European language.
…
They are also closely connected to later, Final Neolithic cultures which spread throughout Europe and Central Asia, especially the Corded Ware people, but also the Bell Beaker culture as well as the peoples of the Sintashta, Andronovo, and Srubna cultures. In these groups, several aspects of the Yamna culture (e.g., horse-riding, burial styles, and to some extent the pastoralist economy) are present. Genetic studies have also indicated that these populations derived large parts of their ancestry from the steppes.[3][6][7][8]
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https://en.m.wikipedia.org/wiki/Yamna_culture
Gravettian – Wikipedia
October 8, 2019https://en.wikipedia.org/wiki/Gravettian
QT:{{”
The Gravettians were hunter-gatherers who lived in a bitterly cold period of European prehistory, and Gravettian lifestyle was shaped by the climate.
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RFMix: A Discriminative Modeling Approach for Rapid and Robust Local-Ancestry Inference: The American Journal of Human Genetics
October 8, 2019https://www.cell.com/ajhg/fulltext/S0002-9297(13)00289-9#%20
Population Genetics: Why structure matters | eLife
October 8, 2019https://elifesciences.org/articles/45380
QT:{{”
This, however, requires accurate and unbiased estimation of the effects of all SNPs included in the score, which is difficult in a structured (non-homogeneous) population when environmental differences cannot be controlled. To see why this is a problem, consider the classic example of chopstick-eating skills (Lander and Schork, 1994). While there surely are genetic variants affecting our ability to handle chopsticks, most of the variation for this trait across the globe is due to environmental differences (cultural background), and a GWAS would mostly identify variants that had nothing to do with chopstick skills, but simply happened to differ in frequency between East Asia and the rest of the world.
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