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Methods in Cell Biology|July 19, 2025
Next-generation deconvolution of the tumor microenvironment with omnideconvLorenzo Merotto, Alexander Dietrich, Markus List, et al.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.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.International Review of Cell and Molecular Biology|January 15, 2024
Next-generation deconvolution of transcriptomic data to investigate the tumor microenvironmentLorenzo Merotto, Maria Zopoglou, Constantin Zackl, et al.Methods in Molecular Biology (Clifton, N.J.)|March 4, 2020
In Silico Cell-Type Deconvolution Methods in Cancer ImmunotherapyGregor Sturm, Francesca Finotello, Markus ListMethods 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 ListBioinformatics (Oxford, England)|September 13, 2019
Comprehensive evaluation of transcriptome-based cell-type quantification methods for immuno-oncologyGregor Sturm, Francesca Finotello, Florent Petitprez, et al.Cancer Immunology, Immunotherapy : CII|March 16, 2018
Quantifying tumor-infiltrating immune cells from transcriptomics dataFrancesca Finotello, Zlatko TrajanoskiMethods in Molecular Biology (Clifton, N.J.)|March 4, 2020
In Silico Prediction of Tumor Neoantigens with TIminerAlexander Kirchmair, Francesca FinotelloPageof 30