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Archit Verma

Showing results (1-10 of 8) with videos related to

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BMC Bioinformatics|July 23, 2020
A robust nonlinear low-dimensional manifold for single cell RNA-seq dataArchit Verma, Barbara E Engelhardt
BMC Bioinformatics|September 4, 2024
Answering open questions in biology using spatial genomics and structured methodsSiddhartha G Jena, Archit Verma, Barbara E Engelhardt
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 13, 2024
Understanding TCR T cell knockout behavior using interpretable machine learningMarcus Blennemann, Archit Verma, Stefanie Bachl, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 7, 2021
A self-exciting point process to study multicellular spatial signaling patternsArchit Verma, Siddhartha G Jena, Danielle R Isakov, et al.
Biorxiv : the Preprint Server for Biology|June 12, 2025
Live-cell analyses with unsegmented images to study cancer cell response to modified T cell therapyLeo Epstein, Adam C Weiner, Archit Verma, et al.
Scientific Reports|June 30, 2026
Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamicsLeo Epstein, Adam C Weiner, Archit Verma, et al.
Cell Systems|April 2, 2026
Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease statesTianyu Liu, Edward De Brouwer, Archit Verma, et al.
Biorxiv : the Preprint Server for Biology|November 28, 2024
Cellular behavior analysis from live-cell imaging of TCR T cell-cancer cell interactionsArchit Verma, Changhua Yu, Stefanie Bachl, et al.
Pageof 1

Showing results (1-10 of 8) with videos related to

Sort By:
Pageof 1
BMC Bioinformatics|July 23, 2020
A robust nonlinear low-dimensional manifold for single cell RNA-seq dataArchit Verma, Barbara E Engelhardt
BMC Bioinformatics|September 4, 2024
Answering open questions in biology using spatial genomics and structured methodsSiddhartha G Jena, Archit Verma, Barbara E Engelhardt
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing|December 13, 2024
Understanding TCR T cell knockout behavior using interpretable machine learningMarcus Blennemann, Archit Verma, Stefanie Bachl, et al.
Proceedings of the National Academy of Sciences of the United States of America|August 7, 2021
A self-exciting point process to study multicellular spatial signaling patternsArchit Verma, Siddhartha G Jena, Danielle R Isakov, et al.
Biorxiv : the Preprint Server for Biology|June 12, 2025
Live-cell analyses with unsegmented images to study cancer cell response to modified T cell therapyLeo Epstein, Adam C Weiner, Archit Verma, et al.
Scientific Reports|June 30, 2026
Segmentation-free analysis of live-cell imaging data reveals how T cell modifications influence cancer cell aggregation dynamicsLeo Epstein, Adam C Weiner, Archit Verma, et al.
Cell Systems|April 2, 2026
Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease statesTianyu Liu, Edward De Brouwer, Archit Verma, et al.
Biorxiv : the Preprint Server for Biology|November 28, 2024
Cellular behavior analysis from live-cell imaging of TCR T cell-cancer cell interactionsArchit Verma, Changhua Yu, Stefanie Bachl, et al.
Pageof 1