Author

J. Nulsen

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

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Cancer Biology· 4

Signature Assays, Organisms & Methods

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Research Focus:variant calling· 4 Assay:whole-exome sequencing· 4 Research Focus:gene regulatory network inference· 3 Organism:human· 3 Research Focus:database / resource· 2 Approach:machine learning (classical)· 2 Approach:benchmark study· 1 Approach:experimental assay· 1

Frequent Co-Authors

F. D. Ciccarelli· 4 shared C. Yau· 2 shared D. Repana· 2 shared H. Misetic· 2 shared L. Dressler· 2 shared M. Bortolomeazzi· 2 shared A. Acha-Sagredo· 1 shared A. Strange· 1 shared

Activity by Year

2018-2021 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 32 mutual co-author links

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4 shared papersCancer Biology

F. D. Ciccarelli

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Author profile →

4 papers

Recent·Most cited

Comparative assessment of genes driving cancer and somatic evolution.

L. Dressler, M. Bortolomeazzi, M. R. Keddar, H. Misetic, G. Sartini, A. Acha-Sagredo, L. Montorsi, N. Wijewardhane, D. Repana, J. Nulsen, J. Goldman, M. Pollit, P. Davis, A. Strange, K. Ambrose, F. D. Ciccarelli

The paper assesses genes driving cancer and somatic evolution, revealing gaps in driver gene compendiums and identifying conserved genes that promote clonal expansion without malignancy.

bioRxiv · Aug 31, 2021 · PreprintCancer Biology

Pan-cancer detection of driver genes at the single-patient resolution

J. Nulsen, H. Misetic, C. Yau, F. D. Ciccarelli

This paper introduces sysSVM2, a machine learning tool to predict driver genes in individual cancer patients, showing it has low false positives and identifies known cancer pathways.

bioRxiv · Jun 12, 2020Cancer Biology

The Network of Cancer Genes (NCG): a comprehensive catalogue of known and candidate cancer genes from cancer sequencing screens.

D. Repana, J. Nulsen, L. Dressler, M. Bortolomeazzi, S. Kuppili Venkata, A. Tourna, A. Yakovleva, T. Palmieri, F. D. Ciccarelli

The paper curates a comprehensive list of 2,372 cancer-related genes from 275 publications, including sequencing screens of 119 cancer types, and provides annotations on their properties.

bioRxiv · Dec 1, 2018Cancer Biology

Patient-specific detection of cancer genes reveals recurrently perturbed processes in esophageal adenocarcinoma

T. Mourikis, L. Benedetti, E. Foxall, D. Temelkovski, J. Nulsen, J. Perner, M. Cereda, J. Lagergren, M. Howell, C. Yau, R. Fitzgerald, P. Scaffidi, F. D. Ciccarelli

This study identifies patient-specific cancer genes in esophageal adenocarcinoma using machine learning, revealing recurrent process perturbations that suggest therapeutic targets.

bioRxiv · Oct 17, 2018 · PreprintCancer Biology