Celia Lerma Martin retweetledi
Celia Lerma Martin
19 posts
Celia Lerma Martin
@Cels121
PhD student at @schirmerlab. Dry and wet lab, interested in spatial transcriptomics. BSc @UABBarcelona & MSc @UPFBarcelona
Heidelberg, Germany Katılım Ocak 2017
101 Takip Edilen92 Takipçiler
📢 It’s out!! 🎉 Huge thanks to everyone involved, and especially to my partner-in-crime @PauBadiaM 🥸🧡 Swipe for ‘Before and After’ pics. 10 years together, and maybe just a little bit wiser 😉 Després de no fer projectes junts a la carrera, aquest ens ha sortit prou bé😋
Saez-Rodriguez Group@saezlab
Our work with @schirmerlab in multiple sclerosis (MS) is out today in @NatureNeuro. We investigated lesion progression and cell-cell communication events in MS using snRNA-seq and spatial transcriptomics 🧠 See below ⬇️ nature.com/articles/s4159…
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Celia Lerma Martin retweetledi
After nearly two years of hard work, the paper I coauthored with my lifelong partner, and now fiancé, is out in @NatureNeuro 🎉 No podria estar més feliç d’haver-ho fet junts @Cels121 😊
Saez-Rodriguez Group@saezlab
Our work with @schirmerlab in multiple sclerosis (MS) is out today in @NatureNeuro. We investigated lesion progression and cell-cell communication events in MS using snRNA-seq and spatial transcriptomics 🧠 See below ⬇️ nature.com/articles/s4159…
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Celia Lerma Martin retweetledi
Our work with @schirmerlab in multiple sclerosis (MS) is out today in @NatureNeuro. We investigated lesion progression and cell-cell communication events in MS using snRNA-seq and spatial transcriptomics 🧠 See below ⬇️
nature.com/articles/s4159…
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Celia Lerma Martin retweetledi
Our pre-print "Comparative evaluation of methods for the prediction of protein-ligand binding sites" is out on Research Square. Check it out!
🔗 tinyurl.com/Utges-LBS-comp
On this paper we benchmark 11 ligand binding site prediction tools on our curated reference dataset: LIGYSIS!
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Celia Lerma Martin retweetledi
Very happy to see that our review on gene regulatory networks is being featured by @NatureRevGenet and that it inspired its cover! 🥳
Nature Reviews Genetics@NatureRevGenet
Our Featured article: Gene regulatory network inference in the era of single-cell multi-omics go.nature.com/3r8TugN #Review by @PauBadiaM, @LornaWessels, @sophia_mullerd, @TrimbourR, @roramirezf94, @RArgelaguet & @saezlab @UniHeidelberg
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🧠 Delighted to have shared today our research on MS lesions from white matter at #ECTRIMS2023 in Milan! I've talked about how our single-nuc and spatial atlas sheds light on disease progression. Grateful for the opportunity to present and happy to see that the room was packed 😊
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Celia Lerma Martin retweetledi
📢Fantastic talk from @Cels121
🎯demonstrating tools for examining spatial transcriptomics ✅delineate which cells, what are they doing and where are they in #MS
#ECTRIMS2023 #MSMilan2023 @ECTRIMS
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Celia Lerma Martin retweetledi
Gene regulatory networks (GRNs) are useful models to understand cellular identity and disease. We have reviewed the GRN inference field in the current era of single-cell multi-omics 📖 out in @NatureRevGenet
🔗doi.org/10.1038/s41576…
Full-text access: rdcu.be/dfpa2
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Celia Lerma Martin retweetledi
Transcription factor (TF) activity estimation can help to interpret transcriptomics data 🧬💻. In collaboration with the @NTNU and the @BSC_CNS, we present a high-confidence collection of signed TF regulons that covers >1,100 TFs tinyurl.com/24ks3uud
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Celia Lerma Martin retweetledi
Cross-condition single cell data are essential for biomedicine💊🏥 and tissue-centric descriptions are needed. We propose a 💻 framework for its sample-level unsupervised analysis and the estimation of multicellular programs. 📄You can read the preprint at tinyurl.com/mvptmsem
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Celia Lerma Martin retweetledi
New preprint is out! 🚨 We analyzed the spatial map of multiple sclerosis (MS) lesions using snRNA-seq and spatial transcriptomics 🧠. This was a close collab with @schirmerlab, led by @Cels121 and our @PauBadiaM. See below 👇
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Celia Lerma Martin retweetledi
It is not everyday when one can celebrate submitting a manuscript with their significant other 😄🥳 So happy to had the chance to work together on this @Cels121 ☺️
Saez-Rodriguez Group@saezlab
New preprint is out! 🚨 We analyzed the spatial map of multiple sclerosis (MS) lesions using snRNA-seq and spatial transcriptomics 🧠. This was a close collab with @schirmerlab, led by @Cels121 and our @PauBadiaM. See below 👇
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Celia Lerma Martin retweetledi
Our very much extended and revised multiomics single cell (RNA/ATAC seq) and spatial atlas of human myocardial infarction 🫀✨🚀 is out now @Nature! 🥳
Collaborative effort w/ @rkramann, @vanvanka123, & H Milting’s labs
nature.com/articles/s4158…
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Celia Lerma Martin retweetledi
Happy to share our latest work @Nature. We studied the remodeling and inflammatory events after human myocardial infarction with single cell and spatial transcriptomics data. 🥳
This is a complete make-over of the first pre-print back in winter 2020: tinyurl.com/5n7sfhd7
Saez-Rodriguez Group@saezlab
Our very much extended and revised multiomics single cell (RNA/ATAC seq) and spatial atlas of human myocardial infarction 🫀✨🚀 is out now @Nature! 🥳 Collaborative effort w/ @rkramann, @vanvanka123, & H Milting’s labs nature.com/articles/s4158…
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Celia Lerma Martin retweetledi
Happy to see this one out today in @NatMetabolism! 😄 If you are interested in extracting transcription factor or pathway signatures like we did in this work, check out our tool ⚙️ decoupler decoupler-py.readthedocs.io
Saez-Rodriguez Group@saezlab
Great work! We are happy we could help analyze the data with our resources, PROGENy tinyurl.com/2p8razkk and DoRothEA tinyurl.com/3kwn9b7n, and in particular to extract a transcription factor signature present in COVID-19 & other hepatic infections.
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Celia Lerma Martin retweetledi
It is finally out! 🎉
Saez-Rodriguez Group@saezlab
Our updated manuscript describing methods for bioactivity inference (pathways, TFs, etc.) is now published in @BioinfoAdv doi.org/10.1093/bioadv… 🥳 We have been working on a new #Python 🐍 implementation and its integration with the meta-resource @omnipathdb 👇
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Celia Lerma Martin retweetledi
There are many computational methods to infer biological activities. Many lab members led by @PauBadiaM have developed decoupleR 💻, a #Bioconductor #rstats package that collects different methods to infer mechanistic signatures from omics 🧬
Paper: tinyurl.com/ad8nb765 1/10
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Celia Lerma Martin retweetledi
Finally my first co-author paper is out! 🥳
nature.com/articles/s4146…
We trained a collection of deep learning models to infer bioactivity signatures for small compounds, even when no experimental information is available.💊
Now you can feed biological information to your models!💻
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