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» Using Multiple Alignments to Improve Gene Prediction
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BIBM
2008
IEEE
107views Bioinformatics» more  BIBM 2008»
14 years 1 months ago
A Functional Network of Yeast Genes Using Gene Ontology Information
In the post-genomic era, the organization of genes into networks has played an important role in characterizing the functions of individual genes and the interplay between them. I...
Erliang Zeng, Giri Narasimhan, Lisa Schneper, Kala...
RECOMB
2004
Springer
14 years 7 months ago
Predicting Genetic Regulatory Response Using Classification: Yeast Stress Response
We present a novel classification-based algorithm called GeneClass for learning to predict gene regulatory response. Our approach is motivated by the hypothesis that in simple orga...
Manuel Middendorf, Anshul Kundaje, Chris Wiggins, ...
EMNLP
2007
13 years 8 months ago
Improving Word Alignment with Bridge Languages
We describe an approach to improve Statistical Machine Translation (SMT) performance using multi-lingual, parallel, sentence-aligned corpora in several bridge languages. Our appro...
Shankar Kumar, Franz Josef Och, Wolfgang Macherey
BMCBI
2008
138views more  BMCBI 2008»
13 years 7 months ago
Systematic identification of yeast cell cycle transcription factors using multiple data sources
Background: Eukaryotic cell cycle is a complex process and is precisely regulated at many levels. Many genes specific to the cell cycle are regulated transcriptionally and are exp...
Wei-Sheng Wu, Wen-Hsiung Li
BMCBI
2010
147views more  BMCBI 2010»
13 years 7 months ago
Automatic detection of anchor points for multiple sequence alignment
Background: Determining beforehand specific positions to align (anchor points) has proved valuable for the accuracy of automated multiple sequence alignment (MSA) software. This f...
Florian Pitschi, Claudine Devauchelle, Eduardo Cor...