Author

R. Nenutil

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Cancer Biology· 3 Pathology· 1

Signature Assays, Organisms & Methods

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Research Focus:cell type annotation· 4 Organism:human· 4 Research Focus:differential expression· 2 Approach:experimental assay· 2 Assay:imaging· 2 Assay:bulk RNA-seq· 1 Research Focus:cancer & tumor microenvironment· 1 Approach:deep learning· 1

Frequent Co-Authors

E. Budinska· 3 shared V. Popovici· 2 shared B. Bencsikova· 1 shared D. Al Tukmachi· 1 shared D. Horst· 1 shared F. Bosman· 1 shared H. A. Ebhardt· 1 shared H. Imrichova· 1 shared

Activity by Year

2019-2024 · peak 1/yr

Co-Author Collaboration Network

10 top collaborators · 21 mutual co-author links

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3 shared papersCancer Biology

E. Budinska

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Author profile →

4 papers

Recent·Most cited

A quantitative tumor-wide analysis of morphological heterogeneity of colorectal adenocarcinoma

M. P. Dragomir, V. Popovici, S. Schallenberg, M. Carnogurska, D. Horst, R. Nenutil, F. Bosman, E. Budinska

The paper quantitatively analyzes morphological heterogeneity in colorectal adenocarcinoma, finding that specific morphotypes correlate with clinical outcomes.

bioRxiv · Apr 10, 2024Cancer Biology

Molecular portraits of colorectal cancer morphological regions

E. Budinska, M. Hrivnakova, T. Catela Ivkovic, M. Madrzyk, R. Nenutil, B. Bencsikova, D. Al Tukmachi, M. Ruckova, L. Zdrazilova Dubska, O. Slaby, J. Feit, M.-P. Dragomir, P. Borilova Linhartova, S. Tejpar, V. Popovici

The paper investigates how morphological patterns in colorectal cancer influence molecular profiles and shows that morphotype-based sampling reveals molecular features missed by whole-tumor analysis.

bioRxiv · Jan 24, 2023Cancer Biology

Shedding Light on the Black Box of a Neural Network Used to Detect Prostate Cancer in Whole Slide Images by Occlusion-Based Explainability

V. Krajnansky, M. Gallo, R. Nenutil, M. Nemecek, P. Holub, T. Brazdil

This paper presents a deep learning system for prostate cancer detection in whole slide images and uses occlusion-based explainability to identify key histomorphological features used for classification.

bioRxiv · Mar 31, 2022 · PreprintPathology

Breast cancer classification based on proteotypes obtained by SWATH mass spectrometry

P. Bouchal, O. T. Schubert, J. Faktor, L. Capkova, H. Imrichova, K. Zoufalova, V. Paralova, R. Hrstka, Y. Liu, H. A. Ebhardt, E. Budinska, R. Nenutil, R. Aebersold

This study uses SWATH mass spectrometry to classify breast cancer subtypes and identifies key proteins that improve patient stratification for precision medicine.

bioRxiv · Mar 26, 2019Cancer Biology