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» Statistical significance in biological sequence analysis
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RECOMB
2010
Springer
13 years 9 months ago
Leveraging Sequence Classification by Taxonomy-Based Multitask Learning
In this work we consider an inference task that biologists are very good at: deciphering biological processes by bringing together knowledge that has been obtained by experiments u...
Christian Widmer, Jose Leiva, Yasemin Altun, Gunna...
BMCBI
2007
139views more  BMCBI 2007»
13 years 7 months ago
XSTREAM: A practical algorithm for identification and architecture modeling of tandem repeats in protein sequences
Background: Biological sequence repeats arranged in tandem patterns are widespread in DNA and proteins. While many software tools have been designed to detect DNA tandem repeats (...
Aaron M. Newman, James B. Cooper
BMCBI
2005
212views more  BMCBI 2005»
13 years 7 months ago
PAGE: Parametric Analysis of Gene Set Enrichment
Background: Gene set enrichment analysis (GSEA) is a microarray data analysis method that uses predefined gene sets and ranks of genes to identify significant biological changes i...
Seon-Young Kim, David J. Volsky
BMCBI
2008
135views more  BMCBI 2008»
13 years 7 months ago
Knowledge-guided multi-scale independent component analysis for biomarker identification
Background: Many statistical methods have been proposed to identify disease biomarkers from gene expression profiles. However, from gene expression profile data alone, statistical...
Li Chen, Jianhua Xuan, Chen Wang, Ie-Ming Shih, Yu...
BMCBI
2010
171views more  BMCBI 2010»
13 years 7 months ago
PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data
Background: Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers...
Benjamin Georgi, Ivan Gesteira Costa, Alexander Sc...