Analysis of Important Gene Ontology Terms and Biological Pathways Related to Pancreatic Cancer.
Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlying this disease. However, it is far from complete....
| Publicado en: | BioMed Research International Vol. 2016; pp. 1 - 11 |
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| Autores principales: | , , , , |
| Formato: | equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
11/9/2016
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=119356241&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 119356241 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 23146133 FT2T jtl: BioMed Research International issn: 23146133 maglogo: N pubinfo: dt: 11/9/2016 vid: 2016 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 119356241 119356241 119356241 10.1155/2016/7861274 119356241 ppf: 1 ppct: 10 formats: fmt: @attributes: type: P tig: atl: Analysis of Important Gene Ontology Terms and Biological Pathways Related to Pancreatic Cancer. aug: au: Yin, Hang Wang, ShaoPeng Zhang, Yu-Hang Cai, Yu-Dong Liu, Hailin affil: Department of Gastroenterology, Ninth People’s Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai 200011, China sug: subj: Pancreatic Neoplasms Familial and Genetic Ontologies Genetic Research Bioinformatics Descriptive Statistics P-Value Pancreatic Neoplasms Classification Signal Transduction Protein Kinases Funding Source ab: Pancreatic cancer is a serious disease that results in more than thirty thousand deaths around the world per year. To design effective treatments, many investigators have devoted themselves to the study of biological processes and mechanisms underlying this disease. However, it is far from complete. In this study, we tried to extract important gene ontology (GO) terms and KEGG pathways for pancreatic cancer by adopting some existing computational methods. Genes that have been validated to be related to pancreatic cancer and have not been validated were represented by features derived from GO terms and KEGG pathways using the enrichment theory. A popular feature selection method, minimum redundancy maximum relevance, was employed to analyze these features and extract important GO terms and KEGG pathways. An extensive analysis of the obtained GO terms and KEGG pathways was provided to confirm the correlations between them and pancreatic cancer. pubtype: Academic Journal doctype: equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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