Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Tytuł pozycji:

Bayesian Gene Selection Based on Pathway Information and Network-Constrained Regularization.

Tytuł:
Bayesian Gene Selection Based on Pathway Information and Network-Constrained Regularization.
Autorzy:
Cao M; Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.; School of Mathematics and Statistics, Shaanxi Xueqian Normal University, Xi'an 710100, China.
Fan Y; Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Peng Q; Faculty of Electronic and Information Engineering, Xi'an Jiaotong University, Xi'an 710049, China.
Źródło:
Computational and mathematical methods in medicine [Comput Math Methods Med] 2021 Aug 04; Vol. 2021, pp. 7471516. Date of Electronic Publication: 2021 Aug 04 (Print Publication: 2021).
Typ publikacji:
Journal Article
Język:
English
Imprint Name(s):
Publication: 2011- : New York : Hindawi
Original Publication: London : Taylor & Francis, c2006-
MeSH Terms:
Bayes Theorem*
Gene Regulatory Networks*
Genetic Markers*
Biomarkers, Tumor/genetics ; Computational Biology ; Computer Simulation ; Databases, Genetic/statistics & numerical data ; Female ; Gene Expression Profiling ; Genetic Predisposition to Disease ; Humans ; Male ; Models, Genetic ; Neoplasms/genetics ; Oligonucleotide Array Sequence Analysis/statistics & numerical data
References:
Oncotarget. 2017 Mar 28;8(13):20925-20938. (PMID: 28178648)
Cancer Cell. 2002 Mar;1(2):203-9. (PMID: 12086878)
Cancer Res. 2006 Nov 1;66(21):10292-301. (PMID: 17079448)
Comput Math Methods Med. 2017;2017:8307530. (PMID: 28133490)
PLoS One. 2009 Dec 07;4(12):e8161. (PMID: 19997592)
Mol Carcinog. 2008 Jan;47(1):56-65. (PMID: 17620309)
J Pharm Bioallied Sci. 2012 Aug;4(Suppl 2):S310-2. (PMID: 23066278)
Lab Invest. 2019 Sep;99(9):1275-1286. (PMID: 30996295)
Nat Med. 2002 Jan;8(1):68-74. (PMID: 11786909)
Bioinformatics. 2008 May 1;24(9):1175-82. (PMID: 18310618)
Endocr Relat Cancer. 2014 Oct;21(5):R345-56. (PMID: 24981109)
Exp Cell Res. 2016 Nov 15;349(1):15-22. (PMID: 27693451)
Science. 1999 Oct 15;286(5439):531-7. (PMID: 10521349)
IEEE Trans Pattern Anal Mach Intell. 2005 Aug;27(8):1226-38. (PMID: 16119262)
Nat Genet. 2003 May;34(1):85-90. (PMID: 12704389)
Hum Mol Genet. 2015 Jan 1;24(1):142-53. (PMID: 25149476)
Oncotarget. 2016 Sep 6;7(36):57633-57650. (PMID: 27192118)
Breast Cancer Res Treat. 2006 Sep;99(1):71-6. (PMID: 16541315)
Nature. 2002 Jan 31;415(6871):530-6. (PMID: 11823860)
J Cell Physiol. 2019 May;234(5):7070-7077. (PMID: 30378112)
PLoS One. 2011;6(10):e25364. (PMID: 22046239)
Mol Cells. 2013 Dec;36(6):548-55. (PMID: 24241683)
Iran J Public Health. 2016 Dec;45(12):1618-1624. (PMID: 28053928)
BMC Bioinformatics. 2016 Feb 27;17:108. (PMID: 26921029)
Genet Epidemiol. 2013 Feb;37(2):173-83. (PMID: 23161517)
BMC Bioinformatics. 2021 Feb 3;22(1):44. (PMID: 33535967)
Ann Appl Stat. 2010 Sep 1;4(3):1498-1516. (PMID: 22916087)
Biochim Biophys Acta. 2016 Sep;1862(9):1472-84. (PMID: 27208794)
BMC Genomics. 2013;14 Suppl 8:S7. (PMID: 24564637)
J Biomed Inform. 2019 Jul;95:103213. (PMID: 31128258)
Apoptosis. 2017 Mar;22(3):357-368. (PMID: 27798717)
Nucleic Acids Res. 2008 Jan;36(Database issue):D480-4. (PMID: 18077471)
PLoS One. 2015 Mar 16;10(3):e0120361. (PMID: 25774687)
Biosci Rep. 2019 Feb 5;39(2):. (PMID: 29769411)
Substance Nomenclature:
0 (Biomarkers, Tumor)
0 (Genetic Markers)
Entry Date(s):
Date Created: 20210816 Date Completed: 20211124 Latest Revision: 20211124
Update Code:
20240105
PubMed Central ID:
PMC8360753
DOI:
10.1155/2021/7471516
PMID:
34394707
Czasopismo naukowe
High-throughput data make it possible to study expression levels of thousands of genes simultaneously under a particular condition. However, only few of the genes are discriminatively expressed. How to identify these biomarkers precisely is significant for disease diagnosis, prognosis, and therapy. Many studies utilized pathway information to identify the biomarkers. However, most of these studies only incorporate the group information while the pathway structural information is ignored. In this paper, we proposed a Bayesian gene selection with a network-constrained regularization method, which can incorporate the pathway structural information as priors to perform gene selection. All the priors are conjugated; thus, the parameters can be estimated effectively through Gibbs sampling. We present the application of our method on 6 microarray datasets, comparing with Bayesian Lasso, Bayesian Elastic Net, and Bayesian Fused Lasso. The results show that our method performs better than other Bayesian methods and pathway structural information can improve the result.
Competing Interests: The authors declare that there is no conflict of interest regarding the publication of this paper.
(Copyright © 2021 Ming Cao et al.)
Zaloguj się, aby uzyskać dostęp do pełnego tekstu.

Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies