Evidence map›Paper›PMID 12441380›Full record

ArticleProtein science : a publication of the Protein Society2002

Rapid protein domain assignment from amino acid sequence using predicted secondary structure.

Russell L Marsden, Liam J McGuffin, David T Jones

Abstract read
In one paragraph

Article in Protein science : a publication of the Protein Society, 2002. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing 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

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3 · Its place in the literature

Who cites it

58 citing papers in PubMed.

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  8. Biochemical characterization of PE_PGRS61 family protein ofIranian journal of basic medical sciences · 2016
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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

3 authors.

Russell L MarsdenBioinformatics Unit, Department of Computer Science, University College London, UK.
Liam J McGuffin
David T Jones

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The elucidation of the domain content of a given protein sequence in the absence of determined structure or significant sequence homology to known domains is an important problem in structural biology. Here we address how successfully the delineation of continuous domains can be accomplished in the absence of sequence homology using simple baseline methods, an existing prediction algorithm (Domain Guess by Size), and a newly developed method (DomSSEA). The study was undertaken with a view to measuring the usefulness of these prediction methods in terms of their application to fully automatic domain assignment. Thus, the sensitivity of each domain assignment method was measured by calculating the number of correctly assigned top scoring predictions. We have implemented a new continuous domain identification method using the alignment of predicted secondary structures of target sequences against observed secondary structures of chains with known domain boundaries as assigned by Class Architecture Topology Homology (CATH). Taking top predictions only, the success rate of the method in correctly assigning domain number to the representative chain set is 73.3%. The top prediction for domain number and location of domain boundaries was correct for 24% of the multidomain set (+/-20 residues). These results have been put into context in relation to the results obtained from the other prediction methods assessed.

Indexed as

Amino Acid SequenceComputational BiologyProteinsProtein Structure, SecondaryProtein Structure, TertiarySensitivity and SpecificitySequence AlignmentProteins

Identifiers

PMID12441380
PMCPMC2373756

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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.