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» Biological Network Inference Using Redundancy Analysis
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BMCBI
2008
100views more  BMCBI 2008»
14 years 10 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
2008
121views more  BMCBI 2008»
14 years 10 months ago
Modularization of biochemical networks based on classification of Petri net t-invariants
Background: Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from ...
Eva Grafahrend-Belau, Falk Schreiber, Monika Heine...
CLADE
2008
IEEE
15 years 4 months ago
SWARM: a scientific workflow for supporting bayesian approaches to improve metabolic models
With the exponential growth of complete genome sequences, the analysis of these sequences is becoming a powerful approach to build genome-scale metabolic models. These models can ...
Xinghua Shi, Rick Stevens
AI
2006
Springer
14 years 9 months ago
Controlled generation of hard and easy Bayesian networks: Impact on maximal clique size in tree clustering
This article presents and analyzes algorithms that systematically generate random Bayesian networks of varying difficulty levels, with respect to inference using tree clustering. ...
Ole J. Mengshoel, David C. Wilkins, Dan Roth
KDD
2012
ACM
201views Data Mining» more  KDD 2012»
13 years 6 days ago
Low rank modeling of signed networks
Trust networks, where people leave trust and distrust feedback, are becoming increasingly common. These networks may be regarded as signed graphs, where a positive edge weight cap...
Cho-Jui Hsieh, Kai-Yang Chiang, Inderjit S. Dhillo...