Evidence map›Paper›PMID 16916457›Full record

ArticleBMC bioinformatics2006

Incorporating background frequency improves entropy-based residue conservation measures.

Kai Wang, Ram Samudrala

Abstract 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 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

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  16. ASAP: a machine learning framework for local protein properties.Database : the journal of biological databases and curation · 2016
    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

2 authors.

Kai WangComputational Genomics Group, Department of Microbiology, University of Washington, USA. dna@u.washington.edu
Ram Samudrala

Funding

Protein structure from theory and experimentR33GM068152 · NIGMS · UNIVERSITY OF WASHINGTON · PI SAMUDRALA, RAM · 2003 to 2005
$901k
NIGMS NIH HHS GM068152-01NIGMS NIH HHS R33 GM068152
6 · The paper itself

Abstract

backgroundSeveral entropy-based methods have been developed for scoring sequence conservation in protein multiple sequence alignments. High scoring amino acid positions may correlate with structurally or functionally important residues. However, amino acid background frequencies are usually not taken into account in these entropy-based scoring schemes.

resultsWe demonstrate that using a relative entropy measure that incorporates amino acid background frequency results in improved performance in identifying functional sites from protein multiple sequence alignments.

conclusionOur results suggest that the application of appropriate background frequency information may lead to more biologically relevant results in many areas of bioinformatics.

Indexed as

Conserved SequenceEntropyAmino Acid SequenceDatabases, ProteinProtein Structure, SecondarySequence AlignmentSequence Analysis, Protein

Identifiers

PMID16916457
PMCPMC1562451

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LicenceCC BY
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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.