MADGiC: a model-based approach for identifying driver genes in cancer
KD Korthauer, C Kendziorski - Bioinformatics, 2015 - academic.oup.com
Motivation: Identifying and prioritizing somatic mutations is an important and challenging
area of cancer research that can provide new insights into gene function as well as new …
area of cancer research that can provide new insights into gene function as well as new …
[HTML][HTML] Comprehensive assessment of computational algorithms in predicting cancer driver mutations
Background The initiation and subsequent evolution of cancer are largely driven by a
relatively small number of somatic mutations with critical functional impacts, so-called driver …
relatively small number of somatic mutations with critical functional impacts, so-called driver …
[HTML][HTML] Finding driver mutations in cancer: Elucidating the role of background mutational processes
Identifying driver mutations in cancer is notoriously difficult. To date, recurrence of a mutation
in patients remains one of the most reliable markers of mutation driver status. However …
in patients remains one of the most reliable markers of mutation driver status. However …
Evaluating the evaluation of cancer driver genes
CJ Tokheim, N Papadopoulos… - Proceedings of the …, 2016 - National Acad Sciences
Sequencing has identified millions of somatic mutations in human cancers, but
distinguishing cancer driver genes remains a major challenge. Numerous methods have …
distinguishing cancer driver genes remains a major challenge. Numerous methods have …
Comprehensive evaluation of computational methods for predicting cancer driver genes
Optimal methods could effectively improve the accuracy of predicting and identifying
candidate driver genes. Various computational methods based on mutational frequency …
candidate driver genes. Various computational methods based on mutational frequency …
Machine learning methods for prediction of cancer driver genes: a survey paper
R Andrades… - Briefings in …, 2022 - academic.oup.com
Identifying the genes and mutations that drive the emergence of tumors is a critical step to
improving our understanding of cancer and identifying new directions for disease diagnosis …
improving our understanding of cancer and identifying new directions for disease diagnosis …
[HTML][HTML] An evolutionary approach for identifying driver mutations in colorectal cancer
The traditional view of cancer as a genetic disease that can successfully be treated with
drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in …
drugs targeting mutant onco-proteins has motivated whole-genome sequencing efforts in …
[HTML][HTML] A new machine learning method for cancer mutation analysis
It is complicated to identify cancer-causing mutations. The recurrence of a mutation in
patients remains one of the most reliable features of mutation driver status. However, some …
patients remains one of the most reliable features of mutation driver status. However, some …
Cancer driver gene discovery through an integrative genomics approach in a non-parametric Bayesian framework
Motivation Comprehensive catalogue of genes that drive tumor initiation and progression in
cancer is key to advancing diagnostics, therapeutics and treatment. Given the complexity of …
cancer is key to advancing diagnostics, therapeutics and treatment. Given the complexity of …
Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks
M Nourbakhsh, K Degn, A Saksager… - Briefings in …, 2024 - academic.oup.com
The vast amount of available sequencing data allows the scientific community to explore
different genetic alterations that may drive cancer or favor cancer progression. Software …
different genetic alterations that may drive cancer or favor cancer progression. Software …