Chapter 8: Biological Knowledge Assembly and Interpretation

Collection with item attached
2012
Item details URL
http://open-repository.kisti.re.kr/cube/handle/open_repository/475849.do
DOI
10.1371/journal.pcbi.1002858
Title
Chapter 8: Biological Knowledge Assembly and Interpretation
Description
This work was supported by the basic science research program throughthe National Research Foundation of Korea (NRF) funded by the Ministryof Education, Science and Technology (2010-0028631). The funders had norole in the preparation of the manuscript.
abstract
Most methods for large-scale gene expression microarray and RNA-Seq data analysis are designed to determine the lists of genes or gene products that show distinct patterns and/or significant differences. The most challenging and rate-liming step, however, is to determine what the resulting lists of genes and/or transcripts biologically mean. Biomedical ontology and pathway-based functional enrichment analysis is widely used to interpret the functional role of tightly correlated or differentially expressed genes. The groups of genes are assigned to the associated biological annotations using Gene Ontology terms or biological pathways and then tested if they are significantly enriched with the corresponding annotations. Unlike previous approaches, Gene Set Enrichment Analysis takes quite the reverse approach by using pre-defined gene sets. Differential co-expression analysis determines the degree of co-expression difference of paired gene sets across different conditions. Outcomes in DNA microarray and RNA-Seq data can be transformed into the graphical structure that represents biological semantics. A number of biomedical annotation and external repositories including clinical resources can be systematically integrated by biological semantics within the framework of concept lattice analysis. This array of methods for biological knowledge assembly and interpretation has been developed during the past decade and clearly improved our biological understanding of large-scale genomic data from the high-throughput technologies.
provenance
Made available in Cube on 2018-09-28T11:23:50Z (GMT). No. of bitstreams: 0
language
English
author
Kim, Ju Han
accessioned
2018-09-28T11:23:50Z
available
2018-09-28T11:23:50Z
issued
2012
citation
PLOS COMPUTATIONAL BIOLOGY(8): 12
issn
1553-7358
uri
http://open-repository.kisti.re.kr/cube/handle/open_repository/475849.do
Funder
교육과학기술부
Funding Program
선도연구센터지원
Project ID
1345166332
Jurisdiction
Rep.of Korea
Project Name
Genomic Self: Translational Bioinformatics for Genomic Health and Molecular Medicine
rights
openAccess
type
article


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