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CIBCB
2005
IEEE
14 years 1 months ago
The Homology Kernel: A Biologically Motivated Sequence Embedding into Euclidean Space
— Part of the challenge of modeling protein sequences is their discrete nature. Many of the most powerful statistical and learning techniques are applicable to points in a Euclid...
Eleazar Eskin, Sagi Snir
APBC
2004
13 years 9 months ago
EMAGEN: An Efficient Approach to Multiple Whole Genome Alignment
Following advances in biotechnology, many new whole genome sequences are becoming available every year. A lot of useful information can be derived from the alignment and compariso...
Jitender S. Deogun, Jingyi Yang, Fangrui Ma
NAR
2008
119views more  NAR 2008»
13 years 7 months ago
MALISAM: a database of structurally analogous motifs in proteins
MALISAM (manual alignments for structurally analogous motifs) represents the first database containing pairs of structural analogs and their alignments. To find reliable analogs, ...
Hua Cheng, Bong-Hyun Kim, Nick V. Grishin
BMCBI
2008
146views more  BMCBI 2008»
13 years 7 months ago
Can molecular dynamics simulations help in discriminating correct from erroneous protein 3D models?
Background: Recent approaches for predicting the three-dimensional (3D) structure of proteins such as de novo or fold recognition methods mostly rely on simplified energy potentia...
Jean-François Taly, Antoine Marin, Jean-Fra...
BMCBI
2004
208views more  BMCBI 2004»
13 years 7 months ago
Using 3D Hidden Markov Models that explicitly represent spatial coordinates to model and compare protein structures
Background: Hidden Markov Models (HMMs) have proven very useful in computational biology for such applications as sequence pattern matching, gene-finding, and structure prediction...
Vadim Alexandrov, Mark Gerstein