@lgamon It was great meeting you irl Luke! I'll let the lab know and will certainly take you up on your offer
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Kevin Yang
13 posts
Kevin Yang
@yangkl96
Proteome bioinformatician and PhD student at the University of Michigan
Katılım Ekim 2021
42 Takip Edilen60 Takipçiler
@yangkl96 Great to meet you Kevin! Please drop by the lab next time you’re in Copenhagen 👍 Oh and say hi to the fragpipe team for me!
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Honestly one of the coolest and best organized hackathons/conferences I've been to. I learned so much about the nuances of single cell data from the other attendees and had a great time socializing. Booking my ticket back to Copenhagen soon
Erwin Schoof@erwinschoof
Kevin Yang from the @nesvilab closing the data analytics session by showing the power of MSFragger for scp-MS - incredible what free, academic software can do! #iSCMS2024
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Kevin Yang retweetledi
Our #FragPipe-Analyst manuscript is out! pubs.acs.org/doi/10.1021/ac…. Load FragPipe's TMT/ LFQ/DIA quant tables (peptide or protein quant) and get QC, Limma, PCA, volcano plots, heatmaps, do GO/pathway enrichment analysis, all with just a few clicks! Tutorials:fragpipe-analyst-doc.nesvilab.org
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Congratulations @yangkl96 !
Alexey Nesvizhskii@nesvilab
Congratulation to Kevin Yang who has been named a Rackham Predoctoral Fellow. Kevin is the developer of #MSBooster and his thesis is on integration of deep learning models for improved peptide identification in MS-based proteomics. More cools things by Kevin in the next FragPipe!
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Honored to be named a Rackham Predoctoral Fellow. It feels incredibly validating to have my work recognized and to connect with colleagues I haven't seen in a while
Alexey Nesvizhskii@nesvilab
Congratulation to Kevin Yang who has been named a Rackham Predoctoral Fellow. Kevin is the developer of #MSBooster and his thesis is on integration of deep learning models for improved peptide identification in MS-based proteomics. More cools things by Kevin in the next FragPipe!
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Kevin Yang retweetledi
MSBooster manuscript led by @yangkl96 is out! In tandem with Percolator, it improves identification rates in #FragPipe using deep learning-based predictions (from DIA-NN). We illustrate it using HLA peptidomics, direct DIA, single-cell, and timsTOF data. nature.com/articles/s4146…
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Kevin Yang retweetledi
New preprint led by @fcyucn describes MSFragger-DIA for direct peptide identification. Illustrated using single-cell, phospho, GFP-DIA, large-scale studies. One-stop analysis of DIA proteomics data using MSFragger-DIA and #FragPipe computational platform. biorxiv.org/content/10.110…
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Thankful for everyone who has been using and providing feedback on #MSBooster in #FragPipe. Excited to showcase the flexibility of the software, and looking forward to adding new features in the near future. Preprint out now!
Alexey Nesvizhskii@nesvilab
#FragPipe users have been enjoying #MSBooster (led by @yangkl96) for a while, but here is the preprint. Rescoring PSMs using deep learning-based predictions, demonstrated using HLA peptidomics, direct DIA, single-cell proteomics, and timsTOF applications. biorxiv.org/content/10.110…
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@MiguelCos @nesvilab For TMT Integrator, you can cite the CPTAC papers "Quantitative proteomic landscape..." Djomehri et al 2020 (printed in GUI Run tab) and "Integrated proteogenomic characterization..." Clark et al 2019. For MSBooster, we will have a preprint out very soon. Thanks for waiting
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@MiguelCos @nesvilab The default prediction model is only shifting TMT fragment peaks, but it is compatible and should not give empty results. Could you send to our github issues? I do not think this is an MSBooster issue
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@LukaszPK If you have the ASMS2021 app, it should be under the Informatics: Peptide ID and Quant poster section for Wednesday
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