Santiago Carmona 🧬 🖥️ 🧑🏾🔬
@carmonation.bsky.social
Computational biologist, associate professor at University of Geneva, Department of Pathology and Immunology. Single-cell omics, bio data science, immunology & cancer research
Latest preprint from the lab! Evaluating cell type annotations in single-cell omics in the absence of ground truth www.biorxiv.org/content/10.6...
Evaluating cell type annotations in single-cell omics in the absence of ground truth
Accurate cell type annotation is essential for single-cell transcriptomics, directly shaping downstream analyses and biological interpretations. Yet, objective evaluation of annotation quality remains...
biorxiv.org
KLRG1 identifies circulating cytotoxic CD4 T cells with selective anti-tumor function in human cancer @biorxivpreprint.bsky.social www.biorxiv.org/content/10.6... @carmonation.bsky.social
Cell type composition drives patient stratification in single-cell RNA-seq cohorts www.biorxiv.org/content/10.6...
biorxiv.org
One month to go! For 30 more days, you will be able to register and present in a session whose whole premise is to give Postdocs the opportunity to ramble about their very particular niche. Register. Participate. Go for it! RT appreciated 🐟🧪
MadScientist@mads100tist.bsky.social · 7mo ago#Zebrafish 🐟 meeting klaxon🧨 The registration period for the 1st German Zebrafish Meeting (16-18 Sept) is open www.germanfishmeeting.org with Sessions on Development, Pharma, Behavior, Omics, and more. Deadline for Abstracts at the end of April. Hope to see y'all there! 🧪 (1/n)
UCell (v2) and pyUCell: single-cell gene signature scoring for R and Python. We discuss updates and key parameters academic.oup.com/bioinformati...
UCell and pyUCell: single-cell gene signature scoring for R and python
AbstractSummary. Gene signature scoring provides a simple yet powerful approach for quantifying biological signals within single-cell omics datasets. UCell
academic.oup.com
Atomically accurate de novo design of antibodies with RFdiffusion www.nature.com/articles/s41...
Atomically accurate de novo design of antibodies with RFdiffusion - Nature
The combination of computational design, laboratory-based screening and biophysical validation enables the de novo generation of variable heavy-chain antibody fragments and antibodies that precis...
nature.com
Tumour-reactive heterotypic CD8 T cell multiplets from clinical samples www.nature.com/articles/s41...
Tumour-reactive heterotypic CD8 T cell clusters from clinical samples - Nature
Tumour-reactive CD8+ T cells are enriched in functional clusters with tumour cells and/or antigen-presenting cells and can be isolated and expanded from clinical samples.
nature.com
Very happy to share our latest manuscript about TCR-epitope recognition specificity: www.biorxiv.org/content/10.1...
biorxiv.org
Cool paper on scRNA T cell annotation. However, a note for ProjecTILs users: I wouldn’t rely on the ProjecTILs benchmark in this work, as it was run using a mouse reference map to classify human T cells (even though human CD4/CD8 T cell maps are available github.com/carmonalab/P...)
GitHub - carmonalab/ProjecTILs: Interpretation of cell states using reference single-cell maps
Interpretation of cell states using reference single-cell maps - carmonalab/ProjecTILs
github.com
Nature Methods@natmethods.nature.com · 11mo agoIntroducing TCAT, a pipeline to simultaneously capture gene expression programs related to T cell subsets and activation states. www.nature.com/articles/s41...
Your favourite single-cell gene signature scoring method now in Python #scverse and much faster! pypi.org/project/pyuc...
Client Challenge
pypi.org
Introducing ParTIpy, a python package for Pareto Task Inference that scales to large-scale datasets, including single-cell and spatial transcriptomics. 🔗 Manuscript: www.biorxiv.org/content/10.1... 💻 Code: partipy.readthedocs.io
Evaluating the practical aspects and performance of commercial single-cell RNA sequencing technologies www.biorxiv.org/content/10.1...
Evaluating the practical aspects and performance of commercial single-cell RNA sequencing technologies
The rapid development of updated and new commercially available single-cell transcriptomics platforms provides users with a range of experimental options. Cost, sensitivity, throughput, flexibility, a...
biorxiv.org
www.nature.com/articles/s41...
Mechanical confinement governs phenotypic plasticity in melanoma - Nature
Mechanical confinement of cancer cells at the tumour–microenvironment interface induces phenotype switching through chromatin remodelling by HMGB2, leading to a more invasive and drug-resistant state ...
nature.com
A new review on the challenges of identifying cancer cells in single-cell data, summarizing current computational solutions as well as underexplored features of malignancy. From scientists @sib.swiss www.nature.com/articles/s42...
Identification of malignant cells in single-cell transcriptomics data - Communications Biology
This review article discusses the challenges of identifying cancer cells in single-cell data, summarizing current computational solutions as well as underexplored features of malignancy.
nature.com
Identifying malignant cells in single-cell transcriptomics data – from first principles to computational solutions, framed around the hallmarks of cancer www.nature.com/articles/s42...
Identification of malignant cells in single-cell transcriptomics data - Communications Biology
This review article discusses the challenges of identifying cancer cells in single-cell data, summarizing current computational solutions as well as underexplored features of malignancy.
nature.com
Interested in T cell immunity in TB? Check out our new pre-print on antigen-agnostic identification of generalisable human in vivo Mtb-reactive T cell responses: www.biorxiv.org/content/10.1... with @qimmuno.bsky.social & @innate2adaptive.bsky.social
Evolution of T cell responses in the tuberculin skin test reveals generalisable Mtb-reactive T cell metaclones.
T cells contribute to immune protection and pathogenesis in tuberculosis, but measurements of polyclonal responses have failed to resolve correlates of outcome. We report the first temporal…
biorxiv.org
Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases www.biorxiv.org/content/10.1...
Foundation Model Attributions Reveal Shared Inflammatory Program Across Diseases
Determining a gene’s functional significance within a specific cellular context has long been a challenge. We introduce a framework for quantifying gene importance by leveraging attributions learned b...
biorxiv.org
📢 We have an open position at University of Geneva for a PhD student with CS/Math/Physics background to study adaptive immune responses using deep learning. If interested please contact me directly!
Check out how we tackled one of the fundamental challenges in immunology, out today @cp-cellsystems.bsky.social: www.cell.com/cell-systems.... Our major innovations are BATCAVE and BATMAN, two new players to get us closer to solving TCR-pMHC predictions!
T cell receptor cross-reactivity prediction improved by a comprehensive mutational scan database
Banerjee et al. present a comprehensive T cell receptor cross-reactivity database and a hierarchical Bayesian framework to predict T cell receptor targets. Together, they reveal structural and biochem...
cell.com
AI-driven predictive biomarker discovery with contrastive learning to improve clinical trial outcomes: Cancer Cell www.cell.com/cancer-cell/...
AI-driven predictive biomarker discovery with contrastive learning to improve clinical trial outcomes
Arango-Argoty et al. introduce the Predictive Biomarker Modeling Framework (PBMF), an AI-driven contrastive learning framework to identify putative predictive, rather than prognostic, biomarkers for c...
cell.com
Excited to share our new study revealing the intricate dynamics of pregnancy & postpartum physiology! We analyzed 40M lab tests from 300K pregnancies and 160K women (cross-sectional) and mapped week-by-week changes starting from preconception to months-long postpartum recovery.
Exited to share our recent work on TF isoforms! Amazing work by @kaiamattioli.bsky.social Luke Lambourne and Clarissa Santoso and many other collaborators.
Kaia Mattioli@kaiamattioli.bsky.social · last yr.our work on the molecular differences between transcription factor isoforms is out now in Molecular Cell! key point: 2/3rds of TF isos differ in properties like DNA binding & transcriptional activity many are "negative regulators" & misexpressed in cancer www.sciencedirect.com/science/arti...
scRepertoire 2: Enhanced and Efficient Toolkit for Single-Cell Immune Profiling www.biorxiv.org/content/10.1...
The recent "Mal-ID" paper in Science diagnoses diseases from immune repertoires. But a powerful model like Mal-ID can learn differences between groups of immune repertoires that are unrelated to the diseases of interest. We explore these pitfalls in our eLetter response.
Disease diagnostics using machine learning of B cell and T cell receptor sequences
Clinical diagnosis typically incorporates physical examination, patient history, various laboratory tests, and imaging studies but makes limited use of the human immune system’s own record of antigen ...
science.org
🔥 Unveiling the Future of Genomics with Genome Language Models (gLMs)! 🔥 Our comprehensive review, "Transformers and genome language models," is finally published in Nature Machine Intelligence! Link: nature.com/articles/s42...
Transformers and genome language models - Nature Machine Intelligence
Micaela Consens et al. discuss and review the recent rise of transformer-based and large language models in genomics. They also highlight promising directions for genome language models beyond the tra...
nature.com
Comparison and evaluation of methods to infer gene regulatory networks from multimodal single-cell data | bioRxiv www.biorxiv.org/content/10.1...
Comparison and evaluation of methods to infer gene regulatory networks from multimodal single-cell data
Cells regulate their functions through gene expression, driven by a complex interplay of transcription factors and other regulatory mechanisms that together can be modeled as gene regulatory networks ...
biorxiv.org
1) I am delighted to share a manuscript long in the making (7 years), elucidating the forces that shape metastatic adaptation PDAC using scRNA-seq across multiple organs from a rapid autopsy combined with a powerful new clonal phylogeny inference algorithm www.biorxiv.org/content/10.1...
Transcriptomic plasticity is a hallmark of metastatic pancreatic cancer
Metastasis is the leading cause of cancer deaths; nonetheless, how tumor cells adapt to vastly different organ contexts is largely unknown. To investigate this question, we generated a transcriptomic ...
biorxiv.org
Cool www.nature.com/articles/s41...
Clonal dynamics and somatic evolution of haematopoiesis in mouse - Nature
Isolating and studying haematopoietic stem cells in young and aged mice demonstrates evolutionary processes related to blood production and provides a framework for interpreting future work using labo...
nature.com
Thrilled to share new work led by @jieyang437.bsky.social in the lab published today in @Nature. We find that Aspirin prevents metastasis by releasing T cells from immune suppression by platelet TXA2. @Cambridge_Uni @CRUKCamCentre rdcu.be/eci1U
