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» The Factor Graph Network Model for Biological Systems
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SODA
2001
ACM
79views Algorithms» more  SODA 2001»
15 years 4 months ago
Learning Markov networks: maximum bounded tree-width graphs
Markov networks are a common class of graphical models used in machine learning. Such models use an undirected graph to capture dependency information among random variables in a ...
David R. Karger, Nathan Srebro
RECOMB
2006
Springer
16 years 3 months ago
Assessing Significance of Connectivity and Conservation in Protein Interaction Networks
Computational and comparative analysis of protein-protein interaction (PPI) networks enable understanding of the modular organization of the cell through identification of functio...
Mehmet Koyutürk, Ananth Grama, Wojciech Szpan...
SIGSOFT
2009
ACM
16 years 4 months ago
Improving bug triage with bug tossing graphs
A bug report is typically assigned to a single developer who is then responsible for fixing the bug. In Mozilla and Eclipse, between 37%-44% of bug reports are "tossed" ...
Gaeul Jeong, Sunghun Kim, Thomas Zimmermann
156
Voted
BIOCOMP
2008
15 years 4 months ago
Reverse Engineering Module Networks by PSO-RNN Hybrid Modeling
Background: Inferring a gene regulatory network (GRN) from high throughput biological data is often an under-determined problem and is a challenging task due to the following reas...
Yuji Zhang, Jianhua Xuan, Benildo de los Reyes, Ro...
BIBE
2008
IEEE
111views Bioinformatics» more  BIBE 2008»
15 years 5 months ago
Structure learning for biomolecular pathways containing cycles
Bayesian network structure learning is a useful tool for elucidation of regulatory structures of biomolecular pathways. The approach however is limited by its acyclicity constraint...
S. Itani, Karen Sachs, Garry P. Nolan, M. A. Dahle...