Evidence map›Paper›PMID 19036790›Full record

ArticleNucleic acids research2009

SUPERFAMILY--sophisticated comparative genomics, data mining, visualization and phylogeny.

Derek Wilson, Ralph Pethica, Yiduo Zhou, Charles Talbot, Christine Vogel, Martin Madera, Cyrus Chothia, Julian Gough

Abstract read
In one paragraph

Article in Nucleic acids research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 287 papers.

0numbers the graph read from it
0cells of the map it votes in
287citing papers in PubMed
–field-weighted citation impact
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

287 citing papers in PubMed.

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227 more citing papers are in PubMed but not listed here.

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

8 authors.

Derek WilsonMRC Laboratory of Molecular Biology, Hills Road, Cambridge CB2 2QH, Department of Computer Science, University of Bristol, The Merchant Venturers Building, Bristol BS8 1UB, UK. dw@mrc-1mb.cam.ac.uk
Ralph Pethica
Yiduo Zhou
Charles Talbot
Christine Vogel
Martin Madera
Cyrus Chothia
Julian Gough

Funding

Medical Research Council MC_U105161047Medical Research Council MC_U105184318
6 · The paper itself

Abstract

SUPERFAMILY provides structural, functional and evolutionary information for proteins from all completely sequenced genomes, and large sequence collections such as UniProt. Protein domain assignments for over 900 genomes are included in the database, which can be accessed at http://supfam.org/. Hidden Markov models based on Structural Classification of Proteins (SCOP) domain definitions at the superfamily level are used to provide structural annotation. We recently produced a new model library based on SCOP 1.73. Family level assignments are also available. From the web site users can submit sequences for SCOP domain classification; search for keywords such as superfamilies, families, organism names, models and sequence identifiers; find over- and underrepresented families or superfamilies within a genome relative to other genomes or groups of genomes; compare domain architectures across selections of genomes and finally build multiple sequence alignments between Protein Data Bank (PDB), genomic and custom sequences. Recent extensions to the database include InterPro abstracts and Gene Ontology terms for superfamiles, taxonomic visualization of the distribution of families across the tree of life, searches for functionally similar domain architectures and phylogenetic trees. The database, models and associated scripts are available for download from the ftp site.

Indexed as

Databases, ProteinProtein Structure, TertiaryAnimalsComputer GraphicsGenomicsHumansPhylogenyProteinsSequence Analysis, DNASequence Analysis, ProteinProteins

Identifiers

PMID19036790
PMCPMC2686452

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.