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Literature DB >> 17387111

Ngila: global pairwise alignments with logarithmic and affine gap costs.

Abstract

UNLABELLED: Ngila is an application that will find the best alignment of a pair of sequences using log-affine gap costs, which are the most biologically realistic gap costs. AVAILABILITY: Portable source code for Ngila can be downloaded from its development website, http://scit.us/projects/ngila/. It compiles on most operating systems.

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Substances：

Year: 2007 PMID： 17387111 PMCID： PMC4739816 DOI： 10.1093/bioinformatics/btm095

Source DB: PubMed Journal: Bioinformatics ISSN： 1367-4803 Impact factor: 6.937

15 in total

1. Local sequence alignments with monotonic gap penalties.

Authors: R Mott
Journal: Bioinformatics Date: 1999-06 Impact factor: 6.937

2. Patterns of nucleotide substitution, insertion and deletion in the human genome inferred from pseudogenes.

Authors: Zhaolei Zhang; Mark Gerstein
Journal: Nucleic Acids Res Date: 2003-09-15 Impact factor: 16.971

3. Empirical analysis of protein insertions and deletions determining parameters for the correct placement of gaps in protein sequence alignments.

Authors: Mike S S Chang; Steven A Benner
Journal: J Mol Biol Date: 2004-08-06 Impact factor: 5.469

4. Exhaustive matching of the entire protein sequence database.

Authors: G H Gonnet; M A Cohen; S A Benner
Journal: Science Date: 1992-06-05 Impact factor: 47.728

5. An evolutionary model for maximum likelihood alignment of DNA sequences.

Authors: J L Thorne; H Kishino; J Felsenstein
Journal: J Mol Evol Date: 1991-08 Impact factor: 2.395

6. The size distribution of insertions and deletions in human and rodent pseudogenes suggests the logarithmic gap penalty for sequence alignment.

Authors: X Gu; W H Li
Journal: J Mol Evol Date: 1995-04 Impact factor: 2.395

Ngila: global pairwise alignments with logarithmic and affine gap costs.

1. Local sequence alignments with monotonic gap penalties.

2. Patterns of nucleotide substitution, insertion and deletion in the human genome inferred from pseudogenes.

3. Empirical analysis of protein insertions and deletions determining parameters for the correct placement of gaps in protein sequence alignments.

4. Exhaustive matching of the entire protein sequence database.

5. An evolutionary model for maximum likelihood alignment of DNA sequences.

6. The size distribution of insertions and deletions in human and rodent pseudogenes suggests the logarithmic gap penalty for sequence alignment.

7. Comparative biosequence metrics.

8. An improved algorithm for matching biological sequences.

9. Efficient sequence alignment algorithms.

10. Logarithmic gap costs decrease alignment accuracy.

1. Problems and solutions for estimating indel rates and length distributions.

2. PICS-Ord: unlimited coding of ambiguous regions by pairwise identity and cost scores ordination.

3. Logarithmic gap costs decrease alignment accuracy.