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» Maximum entropy methods for biological sequence modeling
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GECCO
2008
Springer
179views Optimization» more  GECCO 2008»
13 years 10 months ago
Evolution of discrete gene regulatory models
Gene regulatory networks (GRNs) are complex control systems that govern the interaction of genes, which ultimately control cellular processes at the protein level. GRNs can be ted...
Afshin Esmaeili, Christian Jacob
BMCBI
2006
195views more  BMCBI 2006»
13 years 9 months ago
Hubs of knowledge: using the functional link structure in Biozon to mine for biologically significant entities
Background: Existing biological databases support a variety of queries such as keyword or definition search. However, they do not provide any measure of relevance for the instance...
Paul Shafer, Timothy Isganitis, Golan Yona
IBPRIA
2009
Springer
14 years 1 months ago
Variable Order Finite-Context Models in DNA Sequence Coding
Abstract. Being an essential key in biological research, the DNA sequences are often shared between researchers and digitally stored for future use. As these sequences grow in volu...
Daniel A. Martins, António J. R. Neves, Arm...
BMCBI
2005
125views more  BMCBI 2005»
13 years 9 months ago
Multiple sequence alignments of partially coding nucleic acid sequences
Background: High quality sequence alignments of RNA and DNA sequences are an important prerequisite for the comparative analysis of genomic sequence data. Nucleic acid sequences, ...
Roman R. Stocsits, Ivo L. Hofacker, Claudia Fried,...
CVIU
2006
222views more  CVIU 2006»
13 years 9 months ago
Conditional models for contextual human motion recognition
We present algorithms for recognizing human motion in monocular video sequences, based on discriminative Conditional Random Field (CRF) and Maximum Entropy Markov Models (MEMM). E...
Cristian Sminchisescu, Atul Kanaujia, Dimitris N. ...