Showing results (1-10 of 203) with videos related to

Sort By:
Pageof 21
Methods in Molecular Biology (Clifton, N.J.)|March 4, 2020
In Silico Cell-Type Deconvolution Methods in Cancer ImmunotherapyGregor Sturm, Francesca Finotello, Markus List
Methods in Molecular Biology (Clifton, N.J.)|March 4, 2020
Immunedeconv: An R Package for Unified Access to Computational Methods for Estimating Immune Cell Fractions from Bulk RNA-Sequencing DataGregor Sturm, Francesca Finotello, Markus List
Bioinformatics Advances|March 11, 2024
Making mouse transcriptomics deconvolution accessible with immunedeconvLorenzo Merotto, Gregor Sturm, Alexander Dietrich, et al.
Bioinformatics (Oxford, England)|September 20, 2022
SimBu: bias-aware simulation of bulk RNA-seq data with variable cell-type compositionAlexander Dietrich, Gregor Sturm, Lorenzo Merotto, et al.
Bioinformatics (Oxford, England)|September 13, 2019
Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncologyGregor Sturm, Francesca Finotello, Florent Petitprez, et al.
Methods in Cell Biology|July 19, 2025
Next-generation deconvolution of the tumor microenvironment with omnideconvLorenzo Merotto, Alexander Dietrich, Markus List, et al.
NAR Genomics and Bioinformatics|September 13, 2021
Tissue heterogeneity is prevalent in gene expression studiesGregor Sturm, Markus List, Jitao David Zhang
Genome Biology|January 25, 2026
omnideconv: a unifying framework for using and benchmarking single-cell-informed deconvolution of bulk RNA-seq dataAlexander Dietrich, Lorenzo Merotto, Konstantin Pelz, et al.
Briefings in Bioinformatics|August 12, 2025
Single-cell differential expression analysis between conditions within nested settingsLeon Hafner, Gregor Sturm, Sarah Lumpp, et al.
Bioinformatics (Oxford, England)|July 3, 2020
Scirpy: a Scanpy extension for analyzing single-cell T-cell receptor-sequencing dataGregor Sturm, Tamas Szabo, Georgios Fotakis, et al.
Pageof 21