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Sentil Balaji

dblp:39/11003 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2012
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Bioinformatics and computational biology · 100%
Databases, data mining, and information retrieval
1 paper
Data integration and cleaning · 100%

Topics — the 2 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biomedical text mining
0.112012
IMID: integrated molecular interaction database · Bioinform. 2012
Bioinformatics and computational biology › biomedical text mining
information extraction
0.112012
IMID: integrated molecular interaction database · Bioinform. 2012

Methods — techniques the papers use, named apart from their topics

manual annotation · 0.3automatic information extraction · 0.3
YearPublicationVenuePosition
2012 IMID: integrated molecular interaction database
abstract
MOTIVATION: Molecular interaction information, such as protein-protein interactions and protein-small molecule interactions, is indispensable for understanding the mechanism of biological processes and discovering treatments for diseases. Many databases have been built by manual annotation of literature to organize such information into structured form. However, most databases focus on only one type of interactions, which are often not well annotated and integrated with related functional information. RESULTS: In this study, we integrate molecular interaction information from literature by automatic information extraction and from manually annotated databases. We further integrate the relationships between protein/gene and other bio-entity terms including gene ontology terms, pathways, species and diseases to build an integrated molecular interaction database (IMID). Interactions can be selected by their associated probabilities. IMID allows complex and versatile queries for context-specific molecular interactions, which are not available currently in other molecular interaction databases. AVAILABILITY: The database is located at www.integrativebiology.org.
Sentil Balaji, Charles Mcclendon, Rajesh Chowdhary, Jun S. Liu
Bioinform.1