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ISMB
1994
13 years 9 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
NIPS
1996
13 years 9 months ago
A Model of Recurrent Interactions in Primary Visual Cortex
A general feature of the cerebral cortex is its massive interconnectivity-ithas been estimatedanatomically 15 that cortical neurons receive on the order of 10,000 synapses, the ma...
Emanuel Todorov, Athanassios Siapas, David Somers
3DPH
2009
207views Healthcare» more  3DPH 2009»
13 years 8 months ago
A 3D Human Brain Atlas
3D representations of human physiology provide interesting options in the field of education. Understanding the human brain seems to be much easier when the anatomical structure is...
Sebastian Thelen, Jörg Meyer, Achim Ebert, Ha...
GECCO
2008
Springer
184views Optimization» more  GECCO 2008»
13 years 8 months ago
Analysis of mammography reports using maximum variation sampling
A genetic algorithm (GA) was developed to implement a maximum variation sampling technique to derive a subset of data from a large dataset of unstructured mammography reports. It ...
Robert M. Patton, Barbara G. Beckerman, Thomas E. ...
BMCBI
2010
111views more  BMCBI 2010»
13 years 7 months ago
Protein sequences classification by means of feature extraction with substitution matrices
Background: This paper deals with the preprocessing of protein sequences for supervised classification. Motif extraction is one way to address that task. It has been largely used ...
Rabie Saidi, Mondher Maddouri, Engelbert Mephu Ngu...