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» Maximum entropy methods for biological sequence modeling
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CDC
2010
IEEE
150views Control Systems» more  CDC 2010»
13 years 4 months ago
Nonlinear hybrid system identification with kernel models
Abstract-- This paper focuses on the identification of nonlinear hybrid systems involving unknown nonlinear dynamics. The proposed method extends the framework of [1] by introducin...
Fabien Lauer, Gérard Bloch, René Vid...
RECOMB
2007
Springer
14 years 9 months ago
A Feature-Based Approach to Modeling Protein-DNA Interactions
Transcription factor (TF) binding to its DNA target site is a fundamental regulatory interaction. The most common model used to represent TF binding specificities is a position spe...
Eilon Sharon, Eran Segal
ICASSP
2011
IEEE
13 years 27 days ago
Named entity recognition from Conversational Telephone Speech leveraging Word Confusion Networks for training and recognition
Named Entity (NE) recognition from the results of Automatic Speech Recognition (ASR) is challenging because of ASR errors. To detect NEs, one of the options is to use a statistica...
Gakuto Kurata, Nobuyasu Itoh, Masafumi Nishimura, ...
RECOMB
2007
Springer
14 years 9 months ago
Support Vector Training of Protein Alignment Models
Abstract. Sequence to structure alignment is an important step in homology modeling of protein structures. Incorporation of features like secondary structure, solvent accessibility...
Chun-Nam John Yu, Thorsten Joachims, Ron Elber, Ja...
ALMOB
2006
155views more  ALMOB 2006»
13 years 9 months ago
A phylogenetic generalized hidden Markov model for predicting alternatively spliced exons
Background: An important challenge in eukaryotic gene prediction is accurate identification of alternatively spliced exons. Functional transcripts can go undetected in gene expres...
Jonathan E. Allen, Steven L. Salzberg