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» Learning Methods for DNA Binding in Computational Biology
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BMCBI
2011
13 years 3 days ago
Learning sparse models for a dynamic Bayesian network classifier of protein secondary structure
Background: Protein secondary structure prediction provides insight into protein function and is a valuable preliminary step for predicting the 3D structure of a protein. Dynamic ...
Zafer Aydin, Ajit Singh, Jeff Bilmes, William Staf...
ECAL
2005
Springer
14 years 2 months ago
A Self-organising, Self-adaptable Cellular System
Abstract. Inspired by the recent advances in evolutionary biology, we have developed a self-organising, self-adaptable cellular system for multitask learning. The main aim of our p...
Lucien Epiney, Mariusz Nowostawski
COMPLIFE
2006
Springer
14 years 7 days ago
Relational Subgroup Discovery for Descriptive Analysis of Microarray Data
Abstract. This paper presents a method that uses gene ontologies, together with the paradigm of relational subgroup discovery, to help find description of groups of genes different...
Igor Trajkovski, Filip Zelezný, Jakub Tolar...
ICIP
2010
IEEE
13 years 6 months ago
Saliency detection based on short-term sparse representation
Representation and measurement are two important issues for saliency models. Different with previous works that learnt sparse features from large scale natural statistics, we prop...
Xiaoshuai Sun, Hongxun Yao, Rongrong Ji, Pengfei X...
BIOINFORMATICS
2005
140views more  BIOINFORMATICS 2005»
13 years 8 months ago
Profile-based direct kernels for remote homology detection and fold recognition
Motivation: Remote homology detection between protein sequences is a central problem in computational biology. Supervised learning algorithms based on support vector machines are ...
Huzefa Rangwala, George Karypis