The theory of artificial neural networks is briefly reviewed focusing on supervised and
unsupervised techniques which have great impact on current chemical applications. An …

The human genome sequence is the book of our life. Buried in this large volume are our
genes, which are scattered as small DNA fragments throughout the genome and comprise a …

Background Exhaustive methods of sequence alignment are accurate but slow, whereas
heuristic approaches run quickly, but their complexity makes them more difficult to …

We present an improved splice site predictor for the genehnding program Genie. Genie is
based on a generalized Hidden Markov Model (GHMM) that describes the grammar of a …

Ab initio gene identification in the genomic sequence of Drosophila melanogaster was
obtained using Fgenes (human gene predictor) and Fgenesh programs that have organism …

In one of the first major texts in the emerging field of computational molecular biology, Pavel
Pevzner covers a broad range of algorithmic and combinatorial topics and shows how they …

We present a statistical model of genes in DNA. A Generalized Hidden Markov Model
(GtlMM) provides the framework for describing the grasnmar of a legal parse of a DNA …

A computer program, PROMOTER SCAN, has been developed to recognize a high
percentage of Pol II promoter sequences while allowing only a small rate of false positives. A …

Proteins with sequence-specific DNA binding function are important for a wide range of
biological activities. De novo prediction of their DNA-binding specificities from sequence …

A hidden Markov model (HMM) has been developed to find protein coding genes in E. coli
DNA using E. coli genome DNA sequence from the EcoSeq6 database maintained by Kenn …