Evidence map›Paper›PMID 18314547›Full record

ArticleNucleic acids research2008

MAGIIC-PRO: detecting functional signatures by efficient discovery of long patterns in protein sequences.

Chen-Ming Hsu, Chien-Yu Chen, Baw-Jhiune Liu

Abstract readEvaluation StudyCorrected and Republished Article
In one paragraph

Article in Nucleic acids research, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Chen-Ming HsuDepartment of Computer Science and Engineering, Yuan Ze University, Chung-Li, 320, Taiwan, Republic of China.
Chien-Yu Chen
Baw-Jhiune Liu

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper presents a web service named MAGIICPRO,which aims to discover functional signatures of a query protein by sequential pattern mining. Automatic discovery of patterns from unaligned biological sequences is an important problem in molecular biology. MAGIIC-PRO is different from several previously established methods performing similar tasks in two major ways. The first remarkable feature of MAGIIC-PRO is its efficiency in delivering long patterns. With incorporating a new type of gap constraints and some of the state-of-theart data mining techniques, MAGIIC-PRO usually identifies satisfied patterns within an acceptable response time. The efficiency of MAGIIC-PRO enables the users to quickly discover functional signatures of which the residues are not from only one region of the protein sequences or are only conserved in few members of a protein family. The second remarkable feature of MAGIIC-PRO is its effort in refining the mining results. Considering large flexible gaps improves the completeness of the derived functional signatures. The users can be directly guided to the patterns with as many blocks as that are conserved simultaneously. In this paper,we show by experiments that MAGIIC-PRO is efficient and effective in identifying ligand-binding sites and hot regions in protein-protein interactions directly from sequences. The web service is availableat http://biominer.bime.ntu.edu.tw/magiicproand a mirror site at http://biominer.cse.yzu.edu.tw/magiicpro.

Indexed as

SoftwareBinding SitesComputer GraphicsInternetLigandsModels, MolecularMultiprotein ComplexesProtein ConformationSequence Analysis, ProteinUser-Computer InterfaceLigandsMultiprotein Complexes

Identifiers

PMID18314547
PMCPMC3143912

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.