Evidence map›Paper›PMID 22102772›Full record

ArticleBioinformation2011

Identification of hub proteins from sequence.

Aswathi Balakrishnan Latha, Achuthsankar Sukumaran Nair, Athmaja Sivasankaran, Pawan Kumar Dhar

Abstract read
In one paragraph

Article in Bioinformation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Substitution scoring matrices for proteins - An overview.Protein science : a publication of the Protein Society · 2020
    Review
  3. Article
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

4 authors.

Aswathi Balakrishnan Latha
Achuthsankar Sukumaran Nair
Athmaja Sivasankaran
Pawan Kumar Dhar

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of hub proteins from sequence is a challenge in molecular biology. Therefore, it is of interest to predict protein hubs in networks. We describe the prediction of protein "hub" using physiochemical, thermodynamic and conformational properties of amino acid residues in sequence. We have used twenty sequence based features to identify hub behaviour. Linear discriminant analysis and normalised Bayesian approach were utilized for identifying hub proteins solely using these sequence features in E. coli/H. sapiens datasets with accuracies of 99.5/98.6, 87.8/89.6 and 90.1/92.6, respectively.

Identifiers

PMID22102772
PMCPMC3218517

What OpenQuestion holds

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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.