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» Using Multiple Alignments to Improve Gene Prediction
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CSB
2005
IEEE
118views Bioinformatics» more  CSB 2005»
14 years 1 months ago
Gene Teams with Relaxed Proximity Constraint
Functionally related genes co-evolve, probably due to the strong selection pressure in evolution. Thus we expect that they are present in multiple genomes. Physical proximity amon...
Sun Kim, Jeong-Hyeon Choi, Jiong Yang
NAR
2000
152views more  NAR 2000»
13 years 7 months ago
ASDB: database of alternatively spliced genes
Version 2.1 of ASDB (Alternative Splicing Data Base) contains 1922 protein and 2486 DNA sequences. The protein entries from SWISS-PROT are joined into clusters corresponding to al...
I. Dralyuk, Michael Brudno, Mikhail S. Gelfand, Ma...
BMCBI
2010
138views more  BMCBI 2010»
13 years 7 months ago
Sigma-2: Multiple sequence alignment of non-coding DNA via an evolutionary model
Background: While most multiple sequence alignment programs expect that all or most of their input is known to be homologous, and penalise insertions and deletions, this is not a ...
Gayathri Jayaraman, Rahul Siddharthan
BMCBI
2004
125views more  BMCBI 2004»
13 years 7 months ago
A fast algorithm for determining the best combination of local alignments to a query sequence
Background: Existing sequence alignment algorithms assume that similarities between DNA or amino acid sequences are linearly ordered. That is, stretches of similar nucleotides or ...
Gavin C. Conant, Andreas Wagner
BMCBI
2007
134views more  BMCBI 2007»
13 years 7 months ago
Efficient pairwise RNA structure prediction using probabilistic alignment constraints in Dynalign
Background: Joint alignment and secondary structure prediction of two RNA sequences can significantly improve the accuracy of the structural predictions. Methods addressing this p...
Arif Ozgun Harmanci, Gaurav Sharma, David H. Mathe...