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ISMB
1994
14 years 10 months ago
Stochastic Motif Extraction Using Hidden Markov Model
In this paper, westudy the application of an ttMM(hidden Markov model) to the problem of representing protein sequencesby a stochastic motif. Astochastic protein motif represents ...
Yukiko Fujiwara, Minoru Asogawa, Akihiko Konagaya
BMCBI
2006
147views more  BMCBI 2006»
14 years 9 months ago
A hidden Markov model approach for determining expression from genomic tiling micro arrays
Background: Genomic tiling micro arrays have great potential for identifying previously undiscovered coding as well as non-coding transcription. To-date, however, analyses of thes...
Kasper Munch, Paul P. Gardner, Peter Arctander, An...
BMCBI
2006
160views more  BMCBI 2006»
14 years 9 months ago
Gene prediction in eukaryotes with a generalized hidden Markov model that uses hints from external sources
Background: In order to improve gene prediction, extrinsic evidence on the gene structure can be collected from various sources of information such as genome-genome comparisons an...
Mario Stanke, Oliver Schöffmann, Burkhard Mor...
86
Voted
BMCBI
2005
114views more  BMCBI 2005»
14 years 9 months ago
A new decoding algorithm for hidden Markov models improves the prediction of the topology of all-beta membrane proteins
Background: Structure prediction of membrane proteins is still a challenging computational problem. Hidden Markov models (HMM) have been successfully applied to the problem of pre...
Piero Fariselli, Pier Luigi Martelli, Rita Casadio
SIGMOD
2008
ACM
86views Database» more  SIGMOD 2008»
14 years 9 months ago
The YAGO-NAGA approach to knowledge discovery
This paper gives an overview on the YAGO-NAGA approach to information extraction for building a conveniently searchable, large-scale, highly accurate knowledge base of common fact...
Gjergji Kasneci, Maya Ramanath, Fabian M. Suchanek...