A noise reducing sampling approach for uncovering critical properties in large scale biological networks

Proceedings of the 2011 International Conference on High Performance Computing and Simulation, HPCS 2011

Volumn , Issue , 2011, Pages 721-728

  Duraisamy, K ^a   Dempsey, K ^a   Ali, H ^a   Bhowmick, S ^a  

^a UNIVERSITY OF NEBRASKA AT OMAHA   (United States)

Author keywords

bioinformatics; biological properties; chordal graphs; correlation networks; graph theory; noise reduction; parallel algorithms

Indexed keywords

BIOLOGICAL NETWORKS; BIOLOGICAL PROPERTIES; CHORDAL GRAPHS; CORRELATION NETWORK; CORRELATION NETWORKS; CRITICAL PROPERTIES; EXPRESSION LEVELS; GENE PRODUCTS; GRAPH-BASED REPRESENTATIONS; HIGH-THROUGHPUT; IN-DEPTH ANALYSIS; IN-SILICO MODELS; MULTIPLE SAMPLES; NETWORK SIZE; NETWORK STRUCTURES; NOISE REDUCING; NOISE REDUCTIONS; PEARSON CORRELATION COEFFICIENTS; POWER-LAW DEGREE DISTRIBUTION; REDUCING NOISE; REMOVE NOISE; SCALE-FREE;

BIOINFORMATICS; COMPUTER SOFTWARE SELECTION AND EVALUATION; CORRELATION METHODS; GENE EXPRESSION; GRAPH THEORY; PARALLEL ALGORITHMS;

COMPUTER SIMULATION;

EID: 80053039112     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/HPCSim.2011.5999898     Document Type: Conference Paper

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