ShengyuLi

Houston Methodist Research Institute

[ShengyuLi @Shengyu_LI]

Really thrilled that our foundation model to bridge histopathology and spatial transcriptomics is online in Nature Methods today!

[Guangyu Wang @Guangyu_Wang01]

We are so happy to publish our new foundation model in Nature Methods. we trained OmiCLIP, a vision-omics due modalities model to bridge pathology image and transcriptomic, and Loki, a platform using OmiCLIP as backbone for ST and HE image cross analysis. https://t.co/UkHryBRFqQ

[Kristopher Brannan @bRaNnAn_LAB]

Proud to share this recent work with @Krothamel at @yeo_lab and Lena Street at Marko Jovanovic's lab mapping the direct and RNA-dependent protein interactomes for RBPs across stages of the mRNA life cycle.

https://t.co/KoZj73Upch

[John P. Cooke, MD, PhD @rnacorejpc]

Excited and grateful to be part of this innovative work from @Guangyu_Wang01 team in Nature Biotechnology describing cellDancer, a scalable DNN that locally infers RNA-velocity from cell-specific predictions of transcription, splicing, and decay rates. https://t.co/dNAQiUe1ve

[ShengyuLi @Shengyu_LI]

#computationbiology #Bioinformatics

[Guangyu Wang @Guangyu_Wang01]

Our new study for inferring cell-dependent RNA velocity and kinetics of mRNA by deep learning is online in Nature Biotechnology. The website of cellDancer is https://t.co/chA5AqJ2KQ. Hope it can help your studies.

https://t.co/BQh4HKgB1K

[ShengyuLi @Shengyu_LI]

@TuXinming Thanks for raising the discussion. Yes, for the 'observed future cell', we believe that the state of each cell at the next time point is influenced by its neighbor cells.

[ShengyuLi @Shengyu_LI]

cellDancer (1) enables accurate inference of dynamic cell state transitions in heterogeneous cell populations; (2) reveals RNA turnover strategies in the cell cycle; and (3) improves downstream analysis such as vector field predictions. Welcome to use it and give us feedback!

[ShengyuLi @Shengyu_LI]

Excited our work is out at Nat Biotechnol! Check out cellDancer - which enables RNA velocity estimation with cell-specific kinetics. Thanks to @robinustc, @wchen4005, Dr. Ye, @bRaNnAn_LAB, Dr. Le, Dr. Abe, @rnacorejpc, and Dr. Wang. #RNAvelocity #scRNAseq
https://t.co/O1DqSIS5Es