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Mateusz Garbulowski · SciRah

Researcher profile · Semantic Scholar

Mateusz Garbulowski

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Mateusz Garbulowski — researcher profile on SciRah

h-index: 5
Works: 18
Citations: 91

Most-cited papers

Transcriptomic analysis reveals proinflammatory signatures associated with acute myeloid leukemia progression
Svea Stratmann, S. Yones, Mateusz Garbulowski, Ji-Tong Sun +16 more
2021Blood Advances35 citations Open access
Semantic Scholar
R.ROSETTA: an interpretable machine learning framework
Mateusz Garbulowski, Klev Diamanti, Karolina Smolinska, N. Baltzer +5 more
2019BMC Bioinformatics19 citations Open access
Semantic Scholar
Interpretable Machine Learning Reveals Dissimilarities Between Subtypes of Autism Spectrum Disorder
Mateusz Garbulowski, Karolina Smolinska, Klev Diamanti, G. Pan +3 more
2021Frontiers in Genetics10 citations Open access
Semantic Scholar
GeneSPIDER2: large scale GRN simulation and benchmarking with perturbed single-cell data
Mateusz Garbulowski, Thomas Hillerton, Daniel C Morgan, Deniz Seçilmiş +4 more
2024NAR Genomics and Bioinformatics7 citations Open access
Semantic Scholar
RareVariantVis: new tool for visualization of causative variants in rare monogenic disorders using whole genome sequencing data
T. Stokowy, Mateusz Garbulowski, T. Fiskerstrand, Rita Holdhus +8 more
2016Bioinform.6 citations Open access
Semantic Scholar
Coalescence computations for large samples drawn from populations of time-varying sizes
A. Polański, Agnieszka Szczȩsna, Mateusz Garbulowski, M. Kimmel
2017PLoS ONE5 citations Open access
Semantic Scholar
Machine Learning-Based Analysis of Glioma Grades Reveals Co-Enrichment
Mateusz Garbulowski, Karolina Smolinska, Uğur Çabuk, S. Yones +6 more
2022Cancers4 citations Open access
Semantic Scholar
GeneSNAKE: a Python package for simulation of gene regulatory networks and perturbation-induced expression data
Thomas Hillerton, Anton Björk, Nils Lundqvist, Erik K. Zhivkoplias +2 more
2026Bioinformatics Advances1 citations Open access
Semantic Scholar
Topology-based metrics for finding the optimal sparsity in gene regulatory network inference
Nils Lundqvist, Mateusz Garbulowski, Thomas Hillerton, Erik L. L. Sonnhammer
2025Bioinform.1 citations Open access
Semantic Scholar
BiGSM: Bayesian inference of gene regulatory network via sparse modelling
Hang Qin, Mateusz Garbulowski, Erik L. L. Sonnhammer, S. Chatterjee
2025Bioinform.1 citations Open access
Semantic Scholar
Comprehensive analysis of the RBP regulome reveals functional modules and drug candidates in liver cancer
Mateusz Garbulowski, R. Mosca, Carlos J. Gallardo-Dodd, C. Kutter +1 more
2024bioRxiv1 citations Open access
Semantic Scholar
R.ROSETTA: a package for analysis of rule-based classification models
Mateusz Garbulowski, Klev Diamanti, Karolina Smoli, Ska +4 more
20191 citations
Semantic Scholar
GeneSNAKE: a Python package for benchmarking and simulation of gene regulatory networks and perturbation-induced expression data
Thomas Hillerton, Anton Björk, Nils Lundqvist, Erik K. Zhivkoplias +2 more
2025bioRxiv0 citations Open access
Semantic Scholar
Patterns in big data bioinformatics: Understanding complex diseases with interpretable machine learning
Mateusz Garbulowski
20210 citations
Semantic Scholar
Consensus Approach for Detection of Cancer Somatic Mutations
Katarzyna Sieradzka, Kinga Leszczorz, Mateusz Garbulowski, A. Polański
2017International Conference on Man-Machine Interactions0 citations
Semantic Scholar
A model of genome length estimation based on k-mers detection
Mateusz Garbulowski, A. Polański
20150 citations
Semantic Scholar
Impact of the ultrasonic preconditioning onto sedimentation process
Rafał Sancewicz, M. Lemanowicz, A. Gierczycki, Mateusz Garbulowski
20150 citations
Semantic Scholar
A system for simulation of DNA coverage in shotgun sequencing processes
Mateusz Garbulowski, A. Polański
20140 citations
Semantic Scholar

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