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BMCBI
2010
143views more  BMCBI 2010»
13 years 10 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli
BMCBI
2010
136views more  BMCBI 2010»
13 years 10 months ago
A hub-attachment based method to detect functional modules from confidence-scored protein interactions and expression profiles
Background: Many research results show that the biological systems are composed of functional modules. Members in the same module usually have common functions. This is useful inf...
Chia-Hao Chin, Shu-Hwa Chen, Chin-Wen Ho, Ming-Tat...
BMCBI
2008
165views more  BMCBI 2008»
13 years 10 months ago
Peak intensity prediction in MALDI-TOF mass spectrometry: A machine learning study to support quantitative proteomics
Background: Mass spectrometry is a key technique in proteomics and can be used to analyze complex samples quickly. One key problem with the mass spectrometric analysis of peptides...
Wiebke Timm, Alexandra Scherbart, Sebastian Bö...
BMCBI
2010
130views more  BMCBI 2010»
13 years 10 months ago
A statistical approach to finding overlooked genetic associations
Background: Complexity and noise in expression quantitative trait loci (eQTL) studies make it difficult to distinguish potential regulatory relationships among the many interactio...
Andrew K. Rider, Geoffrey Siwo, Nitesh V. Chawla, ...
BMCBI
2007
131views more  BMCBI 2007»
13 years 10 months ago
FUNC: a package for detecting significant associations between gene sets and ontological annotations
Background: Genome-wide expression, sequence and association studies typically yield large sets of gene candidates, which must then be further analysed and interpreted. Informatio...
Kay Prüfer, Bjoern Muetzel, Hong Hai Do, Gunt...