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» Pertinent Background Knowledge for Learning Protein Grammars
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BMCBI
2005
125views more  BMCBI 2005»
13 years 5 months ago
A simple approach for protein name identification: prospects and limits
Background: Significant parts of biological knowledge are available only as unstructured text in articles of biomedical journals. By automatically identifying gene and gene produc...
Katrin Fundel, Daniel Güttler, Ralf Zimmer, J...
BMCBI
2008
100views more  BMCBI 2008»
13 years 5 months ago
High-precision high-coverage functional inference from integrated data sources
Background: Information obtained from diverse data sources can be combined in a principled manner using various machine learning methods to increase the reliability and range of k...
Bolan Linghu, Evan S. Snitkin, Dustin T. Holloway,...
BMCBI
2006
127views more  BMCBI 2006»
13 years 5 months ago
Automatic discovery of cross-family sequence features associated with protein function
Background: Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomic...
Markus Brameier, Josien Haan, Andrea Krings, Rober...
BMCBI
2008
134views more  BMCBI 2008»
13 years 5 months ago
Identification of transcription factor contexts in literature using machine learning approaches
Background: Availability of information about transcription factors (TFs) is crucial for genome biology, as TFs play a central role in the regulation of gene expression. While man...
Hui Yang, Goran Nenadic, John A. Keane
SEMWEB
2009
Springer
14 years 9 days ago
What Four Million Mappings Can Tell You about Two Hundred Ontologies
The field of biomedicine has embraced the Semantic Web probably more than any other field. As a result, there is a large number of biomedical ontologies covering overlapping area...
Amir Ghazvinian, Natalya Fridman Noy, Clement Jonq...