Title
Knowledge-based framework for hypothesis formation in biochemical networks.
Abstract
The current knowledge about biochemical networks is largely incomplete. Thus biologists constantly need to revise or extend existing knowledge. The revision and/or extension are first formulated as theoretical hypotheses, then verified experimentally. Recently, biological data have been produced in great volumes and in diverse formats. It is a major challenge for biologists to process these data to reason about hypotheses. Many computer-aided systems have been developed to assist biologists in undertaking this challenge. The majority of the systems help in finding 'pattern' in data and leave the reasoning to biologists. A few systems have tried to automate the reasoning process of hypothesis formation. These systems generate hypotheses from a knowledge base and given observations. A main drawback of these knowledge-based systems is the knowledge representation formalisms they use. These formalisms are mostly monotonic and are now known to be not quite suitable for knowledge representation, especially in dealing with the inherently incomplete knowledge about biochemical networks.We present a knowledge-based framework for hypothesis formation for biochemical networks. The framework has been implemented by extending BioSigNet-RR-a knowledge based system that supports elaboration-tolerant representation and non-monotonic reasoning. Features of the extended system are illustrated by a case study of the p53 signal network.http://www.biosignet.org
Year
DOI
Venue
2005
10.1093/bioinformatics/bti1134
ECCB/JBI
Keywords
Field
DocType
existing knowledge,knowledge base,current knowledge,biological data,knowledge-based framework,hypothesis formation,biochemical network,knowledge representation,incomplete knowledge,non-monotonic reasoning,elaboration-tolerant representation,knowledge based system
Data mining,Body of knowledge,Knowledge representation and reasoning,Domain knowledge,Computer science,Knowledge-based systems,Knowledge extraction,Bioinformatics,Knowledge base,Rotation formalisms in three dimensions,Open Knowledge Base Connectivity
Conference
Volume
Issue
ISSN
21 Suppl 2
2
1367-4811
Citations 
PageRank 
References 
8
0.72
21
Authors
4
Name
Order
Citations
PageRank
Nam Tran11157.51
Chitta Baral22353269.58
Vinay J. Nagaraj3101.16
Lokesh Joshi4142.28