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Full-Text Articles in Biochemistry, Biophysics, and Structural Biology
Generating A Focused View Of Disease Ontology Cancer Terms For Pan-Cancer Data Integration And Analysis., Tsung-Jung Wu, Lynn M. Schriml, Qing-Rong Chen, Maureen Colbert, Daniel J. Crichton, Raja Mazumder, Ying Hu, + 10 More
Generating A Focused View Of Disease Ontology Cancer Terms For Pan-Cancer Data Integration And Analysis., Tsung-Jung Wu, Lynn M. Schriml, Qing-Rong Chen, Maureen Colbert, Daniel J. Crichton, Raja Mazumder, Ying Hu, + 10 More
Biochemistry and Molecular Medicine Faculty Publications
Bio-ontologies provide terminologies for the scientific community to describe biomedical entities in a standardized manner. There are multiple initiatives that are developing biomedical terminologies for the purpose of providing better annotation, data integration and mining capabilities. Terminology resources devised for multiple purposes inherently diverge in content and structure. A major issue of biomedical data integration is the development of overlapping terms, ambiguous classifications and inconsistencies represented across databases and publications. The disease ontology (DO) was developed over the past decade to address data integration, standardization and annotation issues for human disease data. We have established a DO cancer project to …
Bioxpress: An Integrated Rna-Seq-Derived Gene Expression Database For Pan-Cancer Analysis., Quan Wan, Hayley Dingerdissen, Yu Fan, Naila Gulzar, Yang Pan, Tsung-Jung Wu, Cheng Yan, Haichen Zhang, Raja Mazumder
Bioxpress: An Integrated Rna-Seq-Derived Gene Expression Database For Pan-Cancer Analysis., Quan Wan, Hayley Dingerdissen, Yu Fan, Naila Gulzar, Yang Pan, Tsung-Jung Wu, Cheng Yan, Haichen Zhang, Raja Mazumder
Biochemistry and Molecular Medicine Faculty Publications
BioXpress is a gene expression and cancer association database in which the expression levels are mapped to genes using RNA-seq data obtained from The Cancer Genome Atlas, International Cancer Genome Consortium, Expression Atlas and publications. The BioXpress database includes expression data from 64 cancer types, 6361 patients and 17 469 genes with 9513 of the genes displaying differential expression between tumor and normal samples. In addition to data directly retrieved from RNA-seq data repositories, manual biocuration of publications supplements the available cancer association annotations in the database. All cancer types are mapped to Disease Ontology terms to facilitate a uniform …