We are recruiting!!! PhD and post-doc positions in my group gfellerlab.org/#OpenPositions.

Sensitive identification of neoantigens and cognate TCRs in human solid tumors go.nature.com/3kH1kb8

Le Journal des Sciences France Culture Selon une étude parue hier dans la revue PNASNews , il est possible de prédire les mutations d’un virus, et notamment celles du #SARSCoV2 Natacha Triou Nicolas Martin @lamethodeFC franceculture.fr/emissions/le-j…

New PhD postionS in the lab. Come and join us to work on modeling/predicting T-cell recognition of cancer cells or single-cell genomics in computational oncoimmunology. gfellerlab.org/#OpenPositions

JOB ALERT #Switzerland #bioinformatics #immunooncology #singlecell Please RT! We are looking for a computational biologist (Postdoc/PhD) to join our team at Université de Lausanne SIB Ludwig Cancer Oncology UNIL CHUV to develop single-cell methods for precision IO Job ad soon, please DM for +info

Very happy to share our new manuscript studying MHC-II binding specificities in depth. This was possible thanks to a great collaboration between our lab (David Gfeller), Alexandre Harari, Michal Bassani-Sternberg ,Florence Pojer and Vincent Zoete : biorxiv.org/content/10.110…

If you’re curious about how interactions between amino acids constrain the emergence of polymorphism, you can have a look at our recent article written with GiancarloCroce 👇

Awesome work by GiancarloCroce: Deep learning predictions of TCR-epitope interactions reveal epitope-specific chains in dual alpha T cells biorxiv.org/content/10.110…

New paper out: "Benchmarking data-driven filtering for denoising of TCRpMHC single-cell data" - "We find that both methods identified approximately 75% of the raw data as noise." Tag: #Tcell #SingleCell #bioinformatics for #immunoTherapy Application nature.com/articles/s4159…

Malcolm Sim A word of caution: In TCR-epitope interaction predictions, AUC>0.5 (and even AUC>>0.5) can be obtained on new/unseen epitopes if negatives are easy to predict. When using TCRs binding to other epitopes, AI can be quite good at “learning the negatives”.

Tired of long computations and exploding memory with your single-cell data? Interested in the idea of metacells, but unsure how to use them correctly? Check our review/tutorial "Building and analyzing metacells in single-cell genomics data" biorxiv.org/content/10.110…

Published version of the MixTCRpred paper: rdcu.be/dEKRs. Great work by the fantastic GiancarloCroce . Stay tuned - his next story is coming out shortly 😉.

💡NEW study by GiancarloCroce , David Gfeller et al., in Nature Communications 🤖 AI: a powerful ally to understand the immune sytem! GfellerLab developed #MixTCRpred, a deep-learning tool that analyzes big datasets of TCRs. ➡️shorturl.at/fijvZ Ludwig Cancer Université de Lausanne CHUV / Centre hospitalier universitaire vaudois

Thrilled to share the beautiful manuscript of GiancarloCroce describing a highly collaborative project with Steven Dunn at CHUV: Phage display profiling of CDR3β loops enables machine learning predictions of NY-ESO-1 specific TCRs biorxiv.org/content/10.110…