LRT-CLUSTER: A New Clustering Algorithm Based on Likelihood Ratio Test to Identify Driving Genes

Somatic mutations often occur at high relapse sites in protein sequences, which indicates that the location clustering of somatic missense mutations can be used to identify driving genes. However, the traditional clustering algorithm has such problems as the background signal over-fitting, the clust...

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Bibliographic Details
Published in:	Interdisciplinary sciences : computational life sciences Vol. 15; no. 2; pp. 217 - 230
Main Authors:	Quan, Chenxu, Liu, Fenghui, Qi, Lin, Tie, Yun
Format:	Journal Article
Language:	English
Published:	Singapore Springer Nature Singapore 01.06.2023 Springer Nature B.V
Subjects:	Algorithms Biomedical and Life Sciences Cancer Chemotherapy Cluster Analysis Clustering Computational Biology/Bioinformatics Computational Science and Engineering Computer Appl. in Life Sciences Computer Simulation Datasets Drug therapy Gene frequency Genes Genomes Health Sciences Humans Knowledge Life Sciences Likelihood Functions Likelihood ratio Mathematical and Computational Physics Medicine Methods Missense mutation Monte Carlo simulation Mutation Mutation - genetics Mutation rates Neoplasms - genetics Nucleotides Original Research Article Proteins Segments Statistical analysis Statistics Statistics for Life Sciences Theoretical Theoretical and Computational Chemistry Somatic mutation Kernel density estimation Bioinformatics Genomics Likelihood ratio test Cancer driver
ISSN:	1913-2751, 1867-1462, 1867-1462
Online Access:	Get full text
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