Author

Lodewyk Wessels

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

Biology Disciplines

Click to filter author papers

Bioinformatics· 3 Cancer Biology· 1

Signature Assays, Organisms & Methods

Click to filter · or open tag

Organism:human· 3 Research Focus:differential expression· 2 Research Focus:drug response / drug discovery· 2 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Assay:CUT&Tag· 1 Assay:DNA methylation· 1 Approach:experimental assay· 1

Frequent Co-Authors

Francesco IorioiD· 2 shared Ultan McDermottiD· 2 shared Aida Shahrabi· 1 shared Andreas Schlicker· 1 shared Anneliese O. SpeakiD· 1 shared Anton Enright· 1 shared Antonia Pritchard· 1 shared Chi Wong· 1 shared

Activity by Year

2016-2017 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 36 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

2 shared papersCancer Biology

Francesco IorioORCID

Mutual co-authors in cluster

Author profile →

4 papers

Recent·Most cited

A screen for combination therapies in BRAF/NRAS wild type melanoma identifies nilotinib plus MEK inhibitor as a synergistic combination

Marco Ranzani, Kristel Kemper, Magali Michaut, Oscar Krijgsman, Nanne Aben, Vivek Iyer, Kim Wong, Theodoros I. Roumeliotis, Martin Del Castillo Velasco-Herrera, Jérémie Nsengimana, Gemma Turner, Nicola Thompson, Aida Shahrabi, Marcela Sjoberg, Mamunur Rashid, , David J. Adams

bioRxiv · Sep 28, 2017 · PreprintCancer Biology

Logic models to predict continuous outputs based on binary inputs with an application to personalized cancer therapy

Theo Knijnenburg, Gunnar Klau, Francesco Iorio, Mathew Garnett, Ultan McDermott, Ilya Shmulevich, Lodewyk Wessels

The paper introduces LOBICO, a logic modeling approach for binary inputs predicting continuous outputs, showing it outperforms single-gene predictors in cancer drug response.

Scientific Reports · Nov 23, 2016Peer-reviewedBioinformatics

A novel independence test for somatic alterations in cancer shows that biology drives mutual exclusivity but chance explains co-occurrence

Sander Canisius, John Martens, Lodewyk Wessels

This paper introduces DISCOVER, a new statistical test for analyzing somatic alterations in cancer, showing it outperforms existing methods and reveals more mutual exclusivity than co-occurrence.

bioRxiv · Aug 3, 2016Bioinformatics

OncoScape: Exploring the cancer aberration landscape by genomic data fusion

Andreas Schlicker, Magali Michaut, Rubayte Rahman, Lodewyk Wessels

OncoScape integrates five genomic data types across 11 cancer types to identify new candidate cancer genes and reveals discrepancies between cell line and tumor aberrations.

bioRxiv · Mar 2, 2016Bioinformatics