Literature DB >> 19957156

Algorithms and methods for correlating experimental results with annotation databases.

Michael Hackenberg1, Rune Matthiesen.   

Abstract

An important procedure in biomedical research is the detection of genes that are differentially expressed under pathologic conditions. These genes, or at least a subset of them, are key biomarkers and are thought to be important to describe and understand the analyzed biological system (the pathology) at a molecular level. To obtain this understanding, it is indispensable to link those genes to biological knowledge stored in databases. Ontological analysis is nowadays a standard procedure to analyze large gene lists. By detecting enriched and depleted gene properties and functions, important insights on the biological system can be obtained. In this chapter, we will give a brief survey of the general layout of the methods used in an ontological analysis and of the most important tools that have been developed.

Mesh:

Year:  2010        PMID: 19957156     DOI: 10.1007/978-1-60327-194-3_15

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  2 in total

1.  WordCluster: detecting clusters of DNA words and genomic elements.

Authors:  Michael Hackenberg; Pedro Carpena; Pedro Bernaola-Galván; Guillermo Barturen; Angel M Alganza; José L Oliver
Journal:  Algorithms Mol Biol       Date:  2011-01-24       Impact factor: 1.405

2.  New insights into functional regulation in MS-based drug profiling.

Authors:  Ana Sofia Carvalho; Henrik Molina; Rune Matthiesen
Journal:  Sci Rep       Date:  2016-01-08       Impact factor: 4.379

  2 in total

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