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Prikvačeni tweet
Excited to share our latest pre-print
- a framework for low-N protein engineering with data-efficient deep learning! Had a blast working with brilliant @EthanAlley@SurgeBiswas@kesvelt and@geochurch. https://www.biorxiv.org/content/10.1101/2020.01.23.917682v1 … Thread (1/7)Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
In DC for
#ASMBiothreats, so much cool work here in rapid countermeasure response for new pathogens! If you are working on this, I want to talk#proteinengineering - dms open.Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Stay tuned for code and more! (7/7)
#proteinengineering#MachineLearning#UniRep#eUniRepPrikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Low-N protein engineering with eUniRep+in silico evolution enables engineers to screen 10s of millions of variants even if assaying the target function is very resource intensive, as is often the case in drug development, agriculture, and industrial production. (6/7)
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Even without any experimental data, eUniRep encodes protein function from raw amino acid sequences alone as the representation’s first principal component. This is likely why eUniRep generalizes so well - maybe even less training data is needed! (5/7)pic.twitter.com/SdGTfvjHHa
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eUniRep also engineers enzymes and leverages epistasis! Despite training on just single mutants of beta lactamase, we generate many >WT epistatically non-trivial variants. (4/7)pic.twitter.com/WLPB2mHGTk
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With just hours of GPU computing and 24 assayed mutants of wild GFP
as training data, we generate much brighter diverse fluorescent proteins, some practically as bright as sfGFP - a fruit of a multi-year effort in high-throughput protein engineering. (3/7)pic.twitter.com/zEKzH2qxUH
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With less than a 96well plate worth of assayed variants, our semi-supervised eUniRep method constructs accurate virtual fitness landscapes and screens ten million protein sequences with in silico directed evolution
. (2/7)pic.twitter.com/PkQ5NwuzGK
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Our UniRep for protein engineering now in
@naturemethods with new baselines! Grateful to@EthanAlley@SurgeBiswas@MoAlQuraishi@geochurchhttps://twitter.com/EthanAlley/status/1186302859295330304 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Grigory Khimulya proslijedio/la je Tweet
Pai-chan and Son-kun are the mascots for the Python certification exam in Japan.pic.twitter.com/S4ym5ymrpE
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Grigory Khimulya proslijedio/la je Tweet
there go my vegetableshttps://twitter.com/Lewis_Bollard/status/1174814854793723904 …
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when you change the learning ratehttps://twitter.com/talkhoops/status/1172978044106985477 …
0:40Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Grigory Khimulya proslijedio/la je Tweet
VEGAS: Platform for Facile Directed Evolution in
#Mammalian Cells •One day/round#DirectedEvolution, based on RNA alphavirus •Mutation rates up to 10^−3 https://www.cell.com/cell/fulltext/S0092-8674(19)30622-1 … from@JustinGEnglish and@RothLabUNC@CellCellPress#biotech#protein#synbiopic.twitter.com/L55ht2YvvD
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Grigory Khimulya proslijedio/la je Tweet
New blogpost up on protein representation learning: http://bit.ly/2COkd6g . I use our recent UniRep preprint (https://www.biorxiv.org/content/10.1101/589333v1 …) in collab with
@EthanAlley@grigonomics@SurgeBiswas@geochurch as a springboard for reflecting on the future of the field.pic.twitter.com/6SBrBqlAJv
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Delighted to have been a part of this! Also want to thank
@francesarnold @YangKevinK@uniprot@grocklin@CherylArrowsmi1@krnsrksn@fkondras@dougfowler42 for inspiration, help, and/or kickass data.https://twitter.com/SurgeBiswas/status/1110604004818587648 …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi
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