Author

Karolina Smolińska

Uppsala UniversityORCID 0000-0003-0907-5298Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Organism:human· 2 Assay:bulk RNA-seq· 1 Assay:ChIP-seq· 1 Research Focus:differential expression· 1 Research Focus:gene regulatory network inference· 1 Approach:machine learning (classical)· 1 Approach:statistical model· 1

Frequent Co-Authors

Jan KomorowskiiD· 2 shared Aleksander Øhrn· 1 shared Claes WadeliusiD· 1 shared Husen Muhammad UmeriD· 1 shared Klev DiamantiiD· 1 shared Lars FeukiD· 1 shared Mateusz GarbulowskiiD· 1 shared Nicholas BaltzeriD· 1 shared

Activity by Year

2019-2020 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 27 mutual co-author links

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2 shared papersBioinformatics

Jan KomorowskiORCID

Mutual co-authors in cluster

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2 papers

Recent·Most cited

BioinformaticsbioRxivPreprintJun 10, 2020

R.ROSETTA: an interpretable machine learning framework

Mateusz Garbulowski, Klev Diamanti, Karolina Smolińska…·Jan Komorowski

R.ROSETTA is an interpretable machine learning framework that identifies biological semantics from omics data, revealing potential gene interdependencies in autism case-control studies.

4 citations

humanbulk RNA-seq

𝕏 PostBluesky

GenomicsbioRxivPreprintJun 27, 2019

funMotifs: Tissue-specific transcription factor motifs

Husen Muhammad Umer, Karolina Smolinska Garbulowska, Nour‐Al‐Dain Marzouka…·Jan Komorowski

The paper introduces funMotifs, a framework to identify tissue-specific functional transcription factor motifs using genomic annotations and regulatory element activity scores, enabling variant analysis across multiple datasets.

7 citations

humanChIP-seq

𝕏 PostBluesky