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BMCBI
2005
198views more  BMCBI 2005»
13 years 7 months ago
Clustering protein sequences with a novel metric transformed from sequence similarity scores and sequence alignments with neural
Background: The sequencing of the human genome has enabled us to access a comprehensive list of genes (both experimental and predicted) for further analysis. While a majority of t...
Qicheng Ma, Gung-Wei Chirn, Richard Cai, Joseph D....
IWANN
1995
Springer
13 years 11 months ago
Test Pattern Generation for Analog Circuits Using Neural Networks and Evolutive Algorithms
This paper presents a comparative analysis of neural networks, simulated annealing, and genetic algorithms in the determination of input patterns for testing analog circuits. The ...
José Luis Bernier, Juan J. Merelo Guerv&oac...
RECOMB
2002
Springer
14 years 7 months ago
DNA sequence evolution with neighbor-dependent mutation
We introduce a model of DNA sequence evolution which can account for biases in mutation rates that depend on the identity of the neighboring bases. An analytic solution for this c...
Peter F. Arndt, Christopher B. Burge, Terence Hwa
NIPS
2000
13 years 8 months ago
A Neural Probabilistic Language Model
A goal of statistical language modeling is to learn the joint probability function of sequences of words in a language. This is intrinsically difficult because of the curse of dim...
Yoshua Bengio, Réjean Ducharme, Pascal Vinc...
BIBM
2010
IEEE
151views Bioinformatics» more  BIBM 2010»
13 years 5 months ago
Probabilistic topic modeling for genomic data interpretation
Recently, the concept of a species containing both core and distributed genes, known as the supra- or pangenome theory, has been introduced. In this paper, we aim to develop a new ...
Xin Chen, Xiaohua Hu, Xiajiong Shen, Gail Rosen