Author

Rosa D. Hernansaiz-Ballesteros

Heidelberg UniversityORCID 0000-0001-8536-8848Unclaimed ORCID profile · follow to get notified of new preprints

Additional preprints under this name without ORCID

Rosa D. Hernansaiz-Ballesteros1 paper

Biology Disciplines

Click to filter author papers

Immunology· 1 Systems Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Assay:bulk RNA-seq· 2 Approach:statistical model· 2 Research Focus:differential expression· 1 Research Focus:drug response / drug discovery· 1 Research Focus:gene regulatory network inference· 1 Assay:long-read sequencing· 1 Organism:virus· 1

Frequent Co-Authors

Andreas BenderiD· 1 shared Anika LiuiD· 1 shared Attila GáboriD· 1 shared David Andrew CollieriD· 1 shared Gurdeep SinghiD· 1 shared Howard B. BroughtoniD· 1 shared Layla Hosseini-GeramiiD· 1 shared Simon BoudreaultiD· 1 shared

Activity by Year

2023-2026 · peak 1/yr

Co-Author Collaboration Network

9 top collaborators · 16 mutual co-author links

Click any collaborator node to inspect or filter shared papers

Focal author (center)Selected co-authorORCID co-authorUnlinked name

Curved chords = mutual co-authorship

1 shared paperSystems Biology

Andreas BenderORCID

Mutual co-authors in cluster

Author profile →

2 papers

Recent·Most cited

ImmunologybioRxivPreprintSep 24, 2026

Mapping global transcript isoform landscapes of influenza A virus infection and interferon stimulation reveals RNA-binding protein networks associated with immune remodeling

Simon Boudreault, Rosa D. Hernansaiz-Ballesteros, Attila Gábor…·Steven F. Baker

The paper uses hybrid RNA sequencing to analyze transcript isoform changes during influenza infection and interferon treatment, identifying RNA-binding proteins involved in immune remodeling.

DOI 10.64898/2026.09.22.753599

virusbulk RNA-seq

𝕏 PostBluesky

Systems BiologyBMC BioinformaticsPeer-reviewedSep 15, 2023

MAVEN: Compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny

Layla Hosseini-Gerami, Rosa D. Hernansaiz-Ballesteros, Anika Liu…·Andreas Bender

MAVEN is an R/Shiny app that predicts drug targets and visualizes compound mechanisms of action using transcriptomics and chemical structure data, enabling hypothesis generation for wet-lab scientists.

4 citations

bulk RNA-seqstatistical model

𝕏 PostBluesky