Author

Cesim Erten

Antalya Bilim ÜniversitesiORCID 0000-0002-8149-7113Unclaimed ORCID profile · follow to get notified of new preprints

Biology Disciplines

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Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Research Focus:differential expression· 3 Organism:human· 3 Assay:whole-exome sequencing· 3 Research Focus:benchmarking· 2 Research Focus:gene regulatory network inference· 2 Approach:graph neural network· 1 Approach:optimal transport· 1

Frequent Co-Authors

Hilal KazaniD· 5 shared Aissa HoudjedjiD· 3 shared Ilyes BaaliiD· 2 shared Rafsan AhmediD· 2 shared Ahmed Amine Taleb Bahmed· 1 shared Cansu YalçıniD· 1 shared Evis Hoxha· 1 shared

Activity by Year

2019-2022 · peak 2/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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5 shared papersBioinformatics

Hilal KazanORCID

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Author profile →

5 papers

Recent·Most cited

PersonaDrive: A Method for the Identification and Prioritization of Personalized Cancer Drivers

Cesim Erten, Aissa Houdjedj, Hilal Kazan, Ahmed Amine Taleb Bahmed

PersonaDrive identifies and prioritizes patient-specific cancer drivers by integrating genomic data, pathways, and protein connectivity, outperforming existing methods on TCGA and cell-line data.

Bioinformatics · May 11, 2022Peer-reviewedBioinformatics

A Network-centric Framework for theEvaluation of Mutual Exclusivity Tests onCancer Drivers

Rafsan Ahmed, Cesim Erten, Aissa Houdjedj, Hilal Kazan, Cansu Yalçın

The paper introduces a network-centric framework to evaluate mutual exclusivity tests for cancer drivers, addressing limitations in current evaluation methods by incorporating network knowledge and resolving confounding factors.

Frontiers in Genetics · Nov 26, 2021Peer-reviewedBioinformatics

Ranking Cancer Drivers via Betweenness-based Outlier Detection and Random Walks

Cesim Erten, Aissa Houdjedj, Hilal Kazan

BetweenNet identifies cancer driver genes by integrating genomic data with protein-protein interaction networks using betweenness centrality and random walks, outperforming existing methods in recovering known cancer genes.

BMC Bioinformatics · Feb 10, 2021Peer-reviewedBioinformatics

DriveWays: A Method for Identifying Possibly Overlapping Driver Pathways in Cancer

Ilyes Baali, Cesim Erten, Hilal Kazan

DriveWays identifies overlapping cancer driver pathways by solving an NP-hard optimization problem, outperforming existing methods on TCGA data.

Scientific Reports · Dec 15, 2020Peer-reviewedBioinformatics

MEXCOWalk: Mutual Exclusion and Coverage Based Random Walk to Identify Cancer Modules

Rafsan Ahmed, Ilyes Baali, Cesim Erten, Evis Hoxha, Hilal Kazan

MEXCOWalk identifies cancer driver modules using mutual exclusion and coverage in protein-protein interaction networks, outperforming existing methods on TCGA data.

Bioinformatics · Aug 19, 2019Peer-reviewedBioinformatics