Josh Welch
@LabWelch
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Computational Biologist, Associate Professor at U. Michigan
Ann Arbor, MI
Joined July 2019
I'm very proud of my student Yichen Gu, who successfully defended his dissertation today! He did amazing work developing variational Bayesian methods for discovering cellular mechanisms from single-cell and spatial data. Yichen will join TikTok as an ML engineer after graduation.
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Interesting in traveling to Hawaii next January? Consider submitting to our Systems Biology and Network Analysis session at PSB! Deadline: 8/1/25.
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Looking forward to speaking at GenBio AI!.
📡 Upcoming Seminar: "Mapping Cell Fate Transition in Space and Time," presented by Associate Professor at the @UMich, @LabWelch. Professor Welch will introduce TopoVelo, a method that integrates spatial data with RNA velocity to model cell fate transitions and tissue
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I'm very proud of my student @JialinLiuSKP, who defended his dissertation today! He developed and applied innovative new computational methods for single-cell and spatial transcriptomic data (to appear soon in high-impact journals!). Jialin will pursue postdoctoral research next
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Excited to speak about our work on generative AI for spatial transcriptomics at the WPI-PRIME International Symposium at Osaka University!
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Enjoyed visiting the computational biology department at USC for a seminar! Thanks @adamlmaclean for the invitation. Lots of exciting work happening at USC!.
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I'm very proud of @hojaeklee, who defended her dissertation today and earned her PhD in Electrical and Computer Engineering! Hojae is the only student I know who received fellowships from both the NSF and NIH. She will work as a research scientist at @Numenta after graduation.
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Very grateful to @cziscience for funding our work to use neural networks to identify cell types!.
Deep learning advancements change how we address challenges & bottlenecks in #SingleCell biology. See how researchers are transforming what's possible using existing data to understand health + disease with cutting edge computational approaches
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RT @mariabrbic: Join us for two days of exciting science at @MLCSB starting tomorrow at #ISMB2024! Don’t miss the amazing lineup of speaker….
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RT @CellSystemsCP: We asked @ProfMonaSingh @cenksahinalp @Jianyang_Zeng @vivianstats @ckingsford Qiangfeng Zhang (@frcbs_Tsinghua) @przytyc….
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RT @jmuiuc: How has the AI boom impacted algorithmic biology? Voices piece @CellSystemsCP from @ProfMonaSingh @cenksahinalp @Jianyang_Zeng….
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Excited to speak at the Max Delbruck Center in Berlin tomorrow! Lots of interesting talks about AI for genomics are on the schedule.
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Enjoyed speaking at STATGEN2024! Grear meeting, wish I could have attended more of the talks.
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Excited for #RECOMB2024! It's going to be a great conference.
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Thrilled to see the university tackling one of our biggest problems: lack of parking. “Applying quantum mechanics to vehicular parking is a first-of-its-kind endeavor. and is part of a bold University effort to overcome classical parking limits.”.
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Looking forward to speaking at MCBIOS today and hearing some great talks from other presenters!.
The single cell omics sessions co-organized by @DurenZhana, Prof. Peng Qiu & myself feature esteemed experts in the field:.@LabWelch .@lucapinello .@DrMingyaoLi .@xiangzhoulab .Prof. Saurabh Sinha.Prof. Tianwei Yu.We are so honored to welcome this exceptional lineup of speakers.
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RT @XiuweiZhang: The single cell omics sessions co-organized by @DurenZhana, Prof. Peng Qiu & myself feature esteemed experts in the field:….
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How can you use RNA velocity to infer the dynamics of cell signaling from spatial transcriptomic data? Check out our new preprint!
@JialinLiuSKP developed a new cell-cell communication approach for spatial RNA data: predicting positions of LR protein-protein interactions. TL;DR: we can infer spatial gradients of signaling, signaling-associated DE genes, and signaling velocity 🧵
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What cell signaling analyses can you do with spatial transcriptomic data that you can't do with scRNA? Check out our latest preprint to find out!.
@JialinLiuSKP developed a new cell-cell communication approach for spatial RNA data: predicting positions of LR protein-protein interactions. TL;DR: we can infer spatial gradients of signaling, signaling-associated DE genes, and signaling velocity 🧵
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