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BMCBI
2010
105views more  BMCBI 2010»
14 years 10 months ago
Evaluation of fecal mRNA reproducibility via a marginal transformed mixture modeling approach
Background: Developing and evaluating new technology that enables researchers to recover gene-expression levels of colonic cells from fecal samples could be key to a non-invasive ...
Nysia I. George, Joanne R. Lupton, Nancy D. Turner...
BMCBI
2010
130views more  BMCBI 2010»
14 years 10 months ago
MLPAinter for MLPA interpretation: an integrated approach for the analysis, visualisation and data management of Multiplex Ligat
Background: Multiplex Ligation-Dependent Probe Amplification (MLPA) is an application that can be used for the detection of multiple chromosomal aberrations in a single experiment...
Ronald van Eijk, Paul H. C. Eilers, Remco Natt&eac...
BMCBI
2010
118views more  BMCBI 2010»
14 years 10 months ago
From learning taxonomies to phylogenetic learning: Integration of 16S rRNA gene data into FAME-based bacterial classification
Background: Machine learning techniques have shown to improve bacterial species classification based on fatty acid methyl ester (FAME) data. Nonetheless, FAME analysis has a limit...
Bram Slabbinck, Willem Waegeman, Peter Dawyndt, Pa...
BMCBI
2010
151views more  BMCBI 2010»
14 years 10 months ago
Classification of G-protein coupled receptors based on support vector machine with maximum relevance minimum redundancy and gene
Background: Because a priori knowledge about function of G protein-coupled receptors (GPCRs) can provide useful information to pharmaceutical research, the determination of their ...
Zhanchao Li, Xuan Zhou, Zong Dai, Xiaoyong Zou
BMCBI
2010
105views more  BMCBI 2010»
14 years 10 months ago
A knowledge-guided strategy for improving the accuracy of scoring functions in binding affinity prediction
Background: Current scoring functions are not very successful in protein-ligand binding affinity prediction albeit their popularity in structure-based drug designs. Here, we propo...
Tiejun Cheng, Zhihai Liu, Renxiao Wang
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