ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation-Reference-Cited by-同舟云学术

ncdDetect2: improved models of the site-specific mutation rate in cancer and driver detection with robust significance evaluation

Published:2018-06-26 Issue:2 Volume:35 Page:189-199
ISSN:1367-4803
Container-title:Bioinformatics
language:en
Short-container-title:

Author:

Juul Malene¹²^ORCID,Madsen Tobias¹²,Guo Qianyun²,Bertl Johanna¹,Hobolth Asger²,Kellis Manolis³,Pedersen Jakob Skou¹²

Affiliation:

1. Department of Molecular Medicine, Aarhus University, Palle Juul-Jensens Boulevard 99, DK-8200 Aarhus N, Denmark

2. Bioinformatics Research Centre, Aarhus University, C.F. Mollers Alle 8, DK-8000 Aarhus C, Denmark

3. Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA

Funder

Sapere Aude

JSP

Innovation Fund Denmark

Independent Research Fund Denmark

Publisher

Oxford University Press (OUP)

Subject

Computational Mathematics,Computational Theory and Mathematics,Computer Science Applications,Molecular Biology,Biochemistry,Statistics and Probability

Link

http://academic.oup.com/bioinformatics/article-pdf/35/2/189/27496990/bty511.pdf

Reference31 articles.

1. Controlling the false discovery rate: a practical and powerful approach to multiple testing;Benjamini;J. R. Stat. Soc. Ser. B (Methodological),1995

2. A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data;Bertl;BMC Bioinformatics,2018

3. Impact of replication timing on non-CpG and CpG substitution rates in mammalian genomes;Chen;Genome Res,2010

4. An integrated encyclopedia of DNA elements in the human genome;ENCODE Project Consortium and others;Nature,2012

Cited by 6 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Gsw-fi: a GLM model incorporating shrinkage and double-weighted strategies for identifying cancer driver genes with functional impact;BMC Bioinformatics;2024-03-06

2. The Search for Cancer Drivers;Lecture Notes in Computer Science;2024

3. DeepAlloDriver: a deep learning-based strategy to predict cancer driver mutations;Nucleic Acids Research;2023-04-20

4. Genome-wide analysis of somatic noncoding mutation patterns in cancer;Science;2022-04-08

5. Non-coding driver mutations in human cancer;Nature Reviews Cancer;2021-07-06