Local Patterns in Biological Sequences
Predicting Protein Structural Similarity and
Cis-Regulatory Modules
978-3-639-10161-4
3639101618
76
2008-11-27
49.00 €
eng
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Many recent advances in the field of biology are due
to the widespread and ever-increasing availability of
sequence data, both DNA and protein. Local Patterns
in Biological Sequences presents three different
algorithms that make use of this wealth of
information: CYRCA, HexDiff, and PreCUSA. CYRCA was
designed to detect weak sequence similarity between
protein families using conserved protein sequence
patterns and graph theory. HexDiff used frequencies
of DNA patterns to detect a specific type of
regulatory sequence called cis-regulatory modules.
The third approach, drawing on the ideas explored in
CYRCA and HexDiff, used structural attributes
predicted from DNA sequence as an alternative source
of information for detecting regulatory sequences in
the genome. The common theme for these three
algorithms is extracting local features from long
biological sequences and utilizing them to predict
large-scale sequence properties.
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