Evidence map›Paper›PMID 16792820›Full record

ArticleBMC bioinformatics2006

MACSIMS: multiple alignment of complete sequences information management system.

Julie D Thompson, Arnaud Muller, Andrew Waterhouse, Jim Procter, Geoffrey J Barton, Frédéric Plewniak, Olivier Poch

Open access · goldAbstract read
In one paragraph

Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
2.2field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

27 citing papers in PubMed, 47 citations in OpenAlex.

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  11. The chordate proteome history database.Evolutionary bioinformatics online · 2012
    Article
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  14. MSV3d: database of human MisSense Variants mapped to 3D protein structure.Database : the journal of biological databases and curation · 2012
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 2 countries.

Julie D ThompsonLaboratoire de Biologie et Genomique Structurales, Institut de Génétique et de Biologie Moléculaire et Cellulaire, Illkirch, France. julie@igbmc.u-strasbg.fr
Arnaud Muller
Andrew Waterhouse
Jim Procter
Geoffrey J Barton
Frédéric Plewniak
Olivier Poch
Institut de génétique et de biologie moléculaire et cellulaire · FRGenomics (United Kingdom) · GBUniversity of Dundee · GB

Funding

Biotechnology and Biological Sciences Research Council BBS/B/16542
6 · The paper itself

Abstract

backgroundIn the post-genomic era, systems-level studies are being performed that seek to explain complex biological systems by integrating diverse resources from fields such as genomics, proteomics or transcriptomics. New information management systems are now needed for the collection, validation and analysis of the vast amount of heterogeneous data available. Multiple alignments of complete sequences provide an ideal environment for the integration of this information in the context of the protein family.

resultsMACSIMS is a multiple alignment-based information management program that combines the advantages of both knowledge-based and ab initio sequence analysis methods. Structural and functional information is retrieved automatically from the public databases. In the multiple alignment, homologous regions are identified and the retrieved data is evaluated and propagated from known to unknown sequences with these reliable regions. In a large-scale evaluation, the specificity of the propagated sequence features is estimated to be >99%, i.e. very few false positive predictions are made. MACSIMS is then used to characterise mutations in a test set of 100 proteins that are known to be involved in human genetic diseases. The number of sequence features associated with these proteins was increased by 60%, compared to the features available in the public databases. An XML format output file allows automatic parsing of the MACSIM results, while a graphical display using the JalView program allows manual analysis.

conclusionMACSIMS is a new information management system that incorporates detailed analyses of protein families at the structural, functional and evolutionary levels. MACSIMS thus provides a unique environment that facilitates knowledge extraction and the presentation of the most pertinent information to the biologist. A web server and the source code are available at http://bips.u-strasbg.fr/MACSIMS/.

Indexed as

AlgorithmsAnimalsComputational BiologyDatabases, ProteinEvolution, MolecularGenomicsHumansManagement Information SystemsMutationProgramming LanguagesProteomicsReproducibility of ResultsSequence Analysis, ProteinSoftware

Identifiers

PMID16792820
PMCPMC1539025
OpenAlexW1574945381

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.