Rajeeva Lochan Musunuri

882 posts

Rajeeva Lochan Musunuri

Rajeeva Lochan Musunuri

@omicsnut

Data Scientist @nygenome

New York 加入时间 Temmuz 2012
2K 关注263 粉丝
Rajeeva Lochan Musunuri
Rajeeva Lochan Musunuri@omicsnut·
@AravSrinivas The subtle difference between a "Research Max" vs "Labs Max" query is a bit confusing (#0" target="_blank" rel="nofollow noopener">perplexity.ai/search/whats-t…). My understanding and experience so far has been that "Labs Max" is much better. Is there any scenario where "Research Max" is preferable over "Labs Max"?
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Aravind Srinivas
Aravind Srinivas@AravSrinivas·
Any Perplexity query on Comet is a lot faster than doing it on another browser. We have optimized it pretty well. And will continue to do so.
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Bjarni Halldórsson
Bjarni Halldórsson@bvhalldorsson·
Long read sequencing of 1,817 Icelanders provides insight into the role of structural variants in human disease disq.us/t/3js36pw
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Dr Harriet Dashnow
Dr Harriet Dashnow@hdashnow·
@lizworthey: Clinical review of 200+ variants per patient takes about 3 hours. Variant fatigue is real! This needs to be faster #gi2019
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brent pedersen
brent pedersen@brent_p·
somalier does a lot of bitwise operations and popcounts to calculate IBS0 and other kinship values. I did an experiment to see if porting to avx512 would speed it up: gist.github.com/brentp/11a497d… it does not. probably need to do the popcounting outside of the loop. any other ideas?
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Jeremy Stanley
Jeremy Stanley@jeremystan·
1/ shapley values (and the Python shap package) have become an *integral* part of my machine learning methodology I’m surprised by how many people still don’t know about them github.com/slundberg/shap
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🔎Julia Evans🔍
🔎Julia Evans🔍@b0rk·
the oom (out of memory) killer
🔎Julia Evans🔍 tweet media
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Nils Homer
Nils Homer@nilshomer·
Bioinformatician: Annotate all the data. Insights will be obvious! Statistical geneticist: Cluster and plot big data. Insights will be obvious! Software Engineer: Make an API to the data. Insights will be obvious! PhD Advisor: Stare at data. Insights are obvious!
Dr Kareem Carr@kareem_carr

Big data: Create huge datasets. Insights will be obvious! Data science: Play with data. Visualize it. Insights will be obvious! Machine learning: Feed data into cool algorithms. Insights will be obvious! Statistics: The insights will never obvious. #epitwitter #statstwitter

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Aaron Darling
Aaron Darling@koadman·
Jason Chin @infoecho introduces hierarchical minimizers and minimizer pair binning to compute human genome assemblies in < 2 hours from high accuracy long reads. simple and beautiful. best #SFAF2019 talk for me!
Aaron Darling tweet mediaAaron Darling tweet media
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Hail
Hail@hailgenetics·
Let's talk about references and citations. References help readers discover relevant work and reproduce results. 1/N
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Jeff Atwood
Jeff Atwood@codinghorror·
There's a ton of pedantry in programming. This may be confusing until you realize that programmers spend 8+ hours a day working with the world's most irritating pedant -- the computer. And the computer is .. kind of an a-hole to be honest.
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