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Bioinformatics (Oxford, England)|November 30, 2020
A framework for modeling epistatic interactionDavid B Blumenthal, Jan Baumbach, Markus Hoffmann, et al.Scientific Reports|June 12, 2024
Single-cell transcriptome analysis reveals secretin as a hallmark of human enteroendocrine cell maturationFranc Hysenaj, Michael Lauber, Andrea Bast-Habersbrunner, et al.Bioinformatics (Oxford, England)|July 15, 2025
Deep learning models for unbiased sequence-based PPI prediction plateau at an accuracy of 0.65Timo Reim, Anne Hartebrodt, David B Blumenthal, et al.Gigascience|November 9, 2025
NApy: efficient statistics in Python for large-scale heterogeneous data with enhanced support for missing dataFabian Woller, Lis Arend, Christian Fuchsberger, et al.Microbial Biotechnology|November 2, 2024
AI in microbiome-related healthcareNiklas Probul, Zihua Huang, Christina Caroline Saak, et al.Cell Reports|January 5, 2017
Pan-cancer Immunogenomic Analyses Reveal Genotype-Immunophenotype Relationships and Predictors of Response to Checkpoint BlockadePornpimol Charoentong, Francesca Finotello, Mihaela Angelova, et al.Nature Communications|May 12, 2026
Critical evaluation of drug response prediction models with DrEvalJudith Bernett, Pascal Iversen, Mario Picciani, et al.Journal for Immunotherapy of Cancer|January 18, 2022
CD161 expression and regulation defines rapidly responding effector CD4+ T cells associated with improved survival in HPV16-associated tumorsChantal L Duurland, Saskia J Santegoets, Ziena Abdulrahman, et al.BMC Bioinformatics|February 26, 2014
Reducing bias in RNA sequencing data: a novel approach to compute countsFrancesca Finotello, Enrico Lavezzo, Luca Bianco, et al.Biorxiv : the Preprint Server for Biology|April 10, 2026
Detection of Candidate Circular RNAs to Monitor Anti-Hormonal Response in the Mammary GlandNico Trummer, Malte Weyrich, Paige Ryan, et al.Pageof 21