Evidence map›Paper›PMID 26568623›Full record

ArticleBioinformatics (Oxford, England)2016

MIEC-SVM: automated pipeline for protein peptide/ligand interaction prediction.

Nan Li, Richard I Ainsworth, Meixin Wu, Bo Ding, Wei Wang

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Bioinformatics (Oxford, England), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Sparse support vector machines with LArtificial intelligence in medicine · 2019
    Article
  3. Article
  4. Prediction of Protein-Protein Interactions by Evidence Combining Methods.International journal of molecular sciences · 2016
    Review
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

5 authors.

Nan LiDepartment of Chemistry and Biochemistry, UC, San Diego, La Jolla, CA 92093-0359 USA.
Richard I AinsworthDepartment of Chemistry and Biochemistry, UC, San Diego, La Jolla, CA 92093-0359 USA.
Meixin WuDepartment of Chemistry and Biochemistry, UC, San Diego, La Jolla, CA 92093-0359 USA.
Bo DingDepartment of Chemistry and Biochemistry, UC, San Diego, La Jolla, CA 92093-0359 USA.
Wei WangDepartment of Chemistry and Biochemistry, UC, San Diego, La Jolla, CA 92093-0359 USA.

Funding

Engineering the binding specificity of modular domainsR01GM111941 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI WANG, WEI · 2015 to 2018
$1.4M
NIGMS NIH HHS R01 GM111941
6 · The paper itself

Abstract

motivationMIEC-SVM is a structure-based method for predicting protein recognition specificity. Here, we present an automated MIEC-SVM pipeline providing an integrated and user-friendly workflow for construction and application of the MIEC-SVM models. This pipeline can handle standard amino acids and those with post-translational modifications (PTMs) or small molecules. Moreover, multi-threading and support to Sun Grid Engine (SGE) are implemented to significantly boost the computational efficiency. AVAILABILITY AND IMPLEMENTATION: The program is available at http://wanglab.ucsd.edu/MIEC-SVM CONTACT: : wei-wang@ucsd.edu SUPPLEMENTARY INFORMATION: Supplementary data available at Bioinformatics online.

Indexed as

SoftwareLigandsPeptidesProtein Processing, Post-TranslationalProteinsLigandsPeptidesProteins

Identifiers

PMID26568623
PMCPMC4907390

What Socratic holds

Textmetadata
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 Socratic graph.