@hd7chen

Machine Learning Enthusiast 💡👨‍💻🤖#MachineLearning#DeepLearning#AI

 Boston, MA
huidongchen.github.io/
Joined August 2017
  • Tweets513
  • Following45
  • Followers226
9Media
I am beyond excited to share that SIMBA, a versatile single-cell graph embedding method, has been published @naturemethods nature.com/articles/s41592-0… (1/6)
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Jayoung Ryu@JayoungR8 Jun 2023
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.
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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.
Nature Methods@naturemethods30 May 2023
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…
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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…
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To ensure practicality and easy adoption, we also built a dedicated website (simba-bio.readthedocs.io/) with detailed documentation and tutorials. Any feedback is welcome! (5/6)
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We endured an incredibly rigorous peer-review process, and I am immensely grateful to all my co-authors @JayoungR @vinyard_m @adamlerer @lucapinello who joined me on this journey. The remarkable effort from everyone involved made this achievement a reality. (6/6)
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Guo-Cheng Yuan@gc_yuan21 Jul 2022
Our lab is recruiting postdocs on spatial transcriptomics and single-cell multi-omics. Please help spread the word! linkedin.com/hiring/jobs/241…
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Clint Miller@clintomics20 Jul 2022
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…

The emerging landscape of spatial profiling technologies

Nature Reviews Genetics - Spatial omics methods enable the charting of cellular heterogeneity, complex tissue architectures and dynamic changes during development and disease. The authors review...

nature.com
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Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data | Nature Communications nature.com/articles/s41467-0…

Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq...

Nature Communications - Multiple methods to infer cell-cell communication (CCC) from single cell data are currently available. Here, the authors systematically compare 16 CCC inference resources...

nature.com
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Ruben Dries@RnDries10 Jun 2022
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

Dries Lab - Join Us!

Welcome to the Dries Lab

drieslab.com
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scverse@scverse_team17 May 2022
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.

scverse

Foundational tools for single-cell omics data analysis

scverse.org
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Guo-Cheng Yuan@gc_yuan10 Apr 2022
To spatial transcriptomics fans, the detailed protocol of our Giotto package is out in Current Protocols. doi.org/10.1002/cpz1.405

Analyzing Spatial Transcriptomics Data Using Giotto

Spatial transcriptomic technologies have been developed rapidly in recent years. The addition of spatial context to expression data holds the potential to revolutionize many fields in biology....

currentprotocols.onlinelibrary.wiley.com
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Temporal modelling using single-cell transcriptomics dlvr.it/SJNpd4
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Really pleased to see this amazing work come out. So well deserved. Congrats Xiaojie!
evo-devo
@Xiaojie_Qiu1 Feb 2022
After 3.5+ years of perseverance, our dynamo paper is finally online in Cell today! Dynamo is an innovative and powerful framework of reconstructing continuous vector fields for mechanistic and predictive modeling of single cell fate transitions. Link: cell.com/cell/fulltext/S0092…
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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
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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…
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dana_peer@dana_peer13 Jan 2022
(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…

CellRank for directed single-cell fate mapping

Nature Methods - CellRank infers directed cell state transitions and cell fates incorporating RNA velocity information into a graph based Markov process.

nature.com
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