Machine Learning Enthusiast 💡👨💻🤖#MachineLearning#DeepLearning#AI
Boston, MA
Joined August 2017
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Huidong Chen retweeted
Excited to be writing & publishing a Nature Portfolio "Behind the Paper" blog post for SIMBA! healthcommunity.nature.com/p… Hope this helps to convey high-level ideas to more readers.
Huidong Chen retweeted
1/6 A little thread to celebrate this milestone! Our SIMBA manuscript has finally seen the light of day, after a journey of more than 2 years. It's been an intense ride, but we're thrilled with the result.
SIMBA learns a co-embedding space of single cells and multiple features such as genes, chromatin accessible regions, and transcription factor binding sequences, boosting performance of various analyses of cellular diversity and regulation. nature.com/articles/s41592-0…
Huidong Chen retweeted
SIMBA learns a co-embedding space of single cells and multiple features such as genes, chromatin accessible regions, and transcription factor binding sequences, boosting performance of various analyses of cellular diversity and regulation. nature.com/articles/s41592-0…
Huidong Chen retweeted
Our lab is recruiting postdocs on spatial transcriptomics and single-cell multi-omics. Please help spread the word! linkedin.com/hiring/jobs/241…
Huidong Chen retweeted
Nice overview of emerging spatial genomics, transcriptomics and proteomics technologies and key applications from Jeffrey Moffitt @Prof_Lundberg @hoheyn @NatureRevGenet nature.com/articles/s41576-0…
Huidong Chen retweeted
Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data | Nature Communications nature.com/articles/s41467-0…
Huidong Chen retweeted
We're looking for new talent and team-players to join our lab! We have multiple positions open, including for a new lab manager, junior bioinformatician and postdoc! All on the crossroads of #spatialOmics #Oncology #technology See drieslab.com/Join%20Us/ for info. Feel free to RT
Huidong Chen retweeted
We are very excited to announce scverse (scverse.org), a new consortium around the core Python packages for single-cell omics data analysis. scverse is a cross-lab effort to ensure the longevity and interoperability of the single-cell analysis ecosystem in Python.
Huidong Chen retweeted
To spatial transcriptomics fans, the detailed protocol of our Giotto package is out in Current Protocols. doi.org/10.1002/cpz1.405
Huidong Chen retweeted
Temporal modelling using single-cell transcriptomics dlvr.it/SJNpd4
Huidong Chen retweeted
Interested in spatial omics? Plz check out our squidpy tool, bringing together omics & image analysis to enable a scalable description of spatial molecular data. Out today @naturemethods thx to @g_palla1, @HannahSpitzer1 & team! nature.com/articles/s41592-0… github.com/theislab/squidpy
Huidong Chen retweeted
Exciting and interesting outlook on new tech for 2022 @Nature - eg. on structure (and cryo-ET), long-read sequencing but also spatial multi-omics. nature.com/articles/d41586-0…
Huidong Chen retweeted
(1) Finally out, after one of the most painful and long reviews (with nitpicky reviews, see my last comment) is a method that I am extremely proud of and excited about. One of the best in my career: nature.com/articles/s41592-0…
Huidong Chen retweeted
What a great surprise to come back to after Christmas holidays to find our paper on benchmarking atlas-level single-cell data integration methods has finally been published. nature.com/articles/s41592-0… . A Tweetorial:
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Huidong Chen retweeted
We extended the RNA velocity model to incorporate epigenome data from single-cell multi-omic protocols like 10X Multiome. Key results: more accurate velocity estimation than RNA alone; inference of RNA/epigenome decoupling; and quantification of time lags.
biorxiv.org/content/10.1101/…
Huidong Chen retweeted
Check out our review on spatial transcriptomic data analysis! #spatialbiology #visualization
In this new paper published in the special issue of Genome Research on single cell genomics, we reviewed the current computational approaches used in spatial transcriptomic analysis. Enjoy! m.genome.cshlp.org/content/3…
Huidong Chen retweeted
New Research: singlecellVR: Interactive Visualization of Single-Cell Data in Virtual Reality: Single-cell assays have transformed our ability to model heterogeneity within cell populations. As these assays have advanced in their ability to… frontiersin.org/articles/10.… #Genetics
Huidong Chen retweeted
singlecellVR online now in @FrontGenetics. Fun fall weekend in2019 turned into a real development effort by @david_stientist, @hd7chen, @QianAlvinQin1, Rebecca Combs, @qianzhangqz, and of course @lucapinello.
frontiersin.org/articles/10.…
Huidong Chen retweeted
Cool preprint applying social network style knowledge graph embeddings to single cell data. "SIMBA: SIngle-cell eMBedding Along with features" by @hd7chen et al out of the @lucapinello lab. doi.org/10.1101/2021.10.17.4…
Huidong Chen retweeted
Today we're releasing SIMBA, a tool for single-cell omics built on top of PyTorch-BigGraph. It’s been fun collaborating with @hd7chen, @lucapinello et al at the Broad to apply PyTorch-BigGraph, originally designed for large-scale web interaction data, to biology!
Really proud of our new collaborative work with and @adamlerer at Facebook and led by the unstoppable @hd7chen and team. We present SIMBA a tool based on graph embedding to build gene regulatory maps.biorxiv.org/content/10.1101/…
