MIQS statistics

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MIQS specifications

Information


Unique identifier OMICS_19366
Name MIQS
Alternative name Matrix to Improve Quality in Similarity search
Interface Web user interface
Restrictions to use None
Input data A single sequence.
Input format FASTA
Computer skills Basic
Stability Stable
Maintained Yes

Maintainer


  • person_outline Kentaro Tomii

Publications for Matrix to Improve Quality in Similarity search

MIQS citations

 (3)
library_books

Protein sequence similarity search acceleration using a heuristic algorithm with a sensitive matrix

2017
J Struct Funct Genomics
PMCID: 5274646
PMID: 28083762
DOI: 10.1007/s10969-016-9210-4

[…] rch method. The use of MIQS is shown to enhance LAST performance considerably across varying m. Moreover, LAST performance is dominant over BLASTP with respect to both sensitivity and time. LAST with MIQS is time-efficient compared to the most sensitive of existing methods: SSEARCH and CS-BLAST. […]

library_books

A simple method to control over alignment in the MAFFT multiple sequence alignment program

2016
Bioinformatics
PMCID: 4920119
PMID: 27153688
DOI: 10.1093/bioinformatics/btw108

[…] UM-VSM as a possible solution. For a better solution, we have a plan to build and use a new series of empirical matrices, each of which is for a strictly specific range of similarity levels, based on MIQS (). By excluding too remote pairs (unlike BLOSUM), MIQS-VSM, -MSM or -MVSM might result in a better tradeoff between sensitivity and over-alignment. (iv) There is a natural requirement that a str […]

library_books

Robust sequence alignment using evolutionary rates coupled with an amino acid substitution matrix

2015
BMC Bioinformatics
PMCID: 4535666
PMID: 26269100
DOI: 10.1186/s12859-015-0688-8

[…] substitution matrices, for example, the CS-BLAST tool, is a novel search approach in which context-specific (CS) substitution matrices were incorporated into the BLAST algorithm []. At the same time, MIQS (Matrix to Improve Quality in Similarity search), a more robust matrix, has been developed from numerous matrices using principal component analysis for detecting remote homologies, for example, […]

Citations

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MIQS institution(s)
Biotechnology Research Institute for Drug Discovery, National Institute of Advanced Industrial Science and Technology (AIST), Koto-Ku, Tokyo, Japan; Graduate School of Information Sciences, Tohoku University, Aoba-ku, Sendai, Japan
MIQS funding source(s)
Partially supported by Platform Project for Supporting in Drug Discovery and Life Science Research (Platform for Drug Discovery, Informatics, and Structural Life Science) from the Ministry of Education, Culture, Sports, Science, and Technology (MEXT) and Japan Agency for Medical Research and Development (AMED).

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