Evidence map›Paper›PMID 28275550›Full record

ArticleGenomics data2017

SVMRFE based approach for prediction of most discriminatory gene target for type II diabetes.

Atul Kumar, D Jeya Sundara Sharmila, Sachidanand Singh

Abstract read
In one paragraph

Article in Genomics data, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. 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

3 authors.

Atul KumarDepartment of Biotechnology and Health Sciences, Karunya University, Coimbatore, Tamil Nadu, India.
D Jeya Sundara SharmilaDepartment of Nanosciences and Technology, Tamil Nadu Agriculture University, Coimbatore, Tamil Nadu, India.
Sachidanand SinghDepartment of Biotechnology and Health Sciences, Karunya University, Coimbatore, Tamil Nadu, India.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Type II diabetes is a chronic condition that affects the way our body metabolizes sugar. The body's important source of fuel is now becoming a chronic disease all over the world. It is now very necessary to identify the new potential targets for the drugs which not only control the disease but also can treat it. Support vector machines are the classifier which has a potential to make a classification of the discriminatory genes and non-discriminatory genes. SVMRFE a modification of SVM ranks the genes based on their discriminatory power and eliminate the genes which are not involved in causing the disease. A gene regulatory network has been formed with the top ranked coding genes to identify their role in causing diabetes. To further validate the results pathway study was performed to identify the involvement of the coding genes in type II diabetes. The genes obtained from this study showed a significant involvement in causing the disease, which may be used as a potential drug target.

Indexed as

MicroarrayProtein-protein interactionSVMRFEt-testType II diabetes

Identifiers

PMID28275550
PMCPMC5331150

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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.