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» Sequence kernels for predicting protein essentiality
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APBC
2004
116views Bioinformatics» more  APBC 2004»
13 years 8 months ago
Structure-Function Relationship in DNA Sequence Recognition by Transcription Factors
Transcription factors play essential role in the gene regulation in higher organisms, binding to multiple target sequences and regulating multiple genes in a complex manner. In or...
Akinori Sarai, Samuel Selvaraj, M. Michael Gromiha...
BIBM
2010
IEEE
156views Bioinformatics» more  BIBM 2010»
13 years 5 months ago
Truncation of protein sequences for fast profile alignment with application to subcellular localization
We have recently found that the computation time of homology-based subcellular localization can be substantially reduced by aligning profiles up to the cleavage site positions of s...
Man-Wai Mak, Wei Wang, Sun-Yuan Kung
BMCBI
2010
123views more  BMCBI 2010»
13 years 7 months ago
A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction
Background: Predicting which molecules can bind to a given binding site of a protein with known 3D structure is important to decipher the protein function, and useful in drug desi...
Brice Hoffmann, Mikhail Zaslavskiy, Jean-Philippe ...
NIPS
2008
13 years 8 months ago
Scalable Algorithms for String Kernels with Inexact Matching
We present a new family of linear time algorithms based on sufficient statistics for string comparison with mismatches under the string kernels framework. Our algorithms improve t...
Pavel P. Kuksa, Pai-Hsi Huang, Vladimir Pavlovic
BMCBI
2005
132views more  BMCBI 2005»
13 years 7 months ago
Kalign - an accurate and fast multiple sequence alignment algorithm
Background: The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families f...
Timo Lassmann, Erik L. L. Sonnhammer