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MEXCOwalk: mutual exclusion and coverage based random walk to identify cancer modules
(Bioinformatics, 2019)
Motivation: Genomic analyses from large cancer cohorts have revealed the mutational heterogeneity problem
which hinders the identification of driver genes based only on mutation profiles. One way to tackle this problem ...
Ranking cancer drivers via betweenness-based outlier detection and random walks
(BMC Bioinformatics, 2021)
Background Recent cancer genomic studies have generated detailed molecular data on a large number of cancer patients. A key remaining problem in cancer genomics is the identification of driver genes. Results
We propose ...
Identification and prioritization of personalized cancer drivers
(German Conference on Bioinformatics, 2022)
SCITUNA: a network alignment approach for integrating multiple single-cell RNA-Seq datasets
(15th International Symposium on Health Informatics and Bioinformatics, 2022)
The throughput and cost of single-cell RNA sequencing (scRNA-seq) are in continuous improvement, and so is the demand for larger-scale scRNA-seq data, which could require integrating multiple datasets from different ...
A network-centric framework for the evaluation of mutual exclusivity tests on cancer drivers
(Frontiers in Genetics, 2021)
One of the key concepts employed in cancer driver gene identification is that of mutual exclusivity (ME); a driver mutation is less likely to occur in case of an earlier mutation that has common functionality in the same ...
DriveWays: a method for identifying possibly overlapping driver pathways in cancer
(Nature Research, 2020)
The majority of the previous methods for identifying cancer driver modules output nonoverlapping modules. This assumption is biologically inaccurate as genes can participate in multiple molecular pathways. This is particularly ...
PersonaDrive: a method for the identification and prioritization of personalized cancer drivers
(Bioinformatics, 2022)
Motivation:
A major challenge in cancer genomics is to distinguish the driver mutations that are causally linked to cancer from passenger mutations that do not contribute to cancer development. The majority of existing ...