Evidence map›Paper›PMID 25184141›Full record

ArticleBioMed research international2014

FSim: a novel functional similarity search algorithm and tool for discovering functionally related gene products.

Qiang Hu, ZhiGang Wang, ZhengGuo Zhang

Abstract read
In one paragraph

Article in BioMed research international, 2014. 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.

Qiang HuDepartment of Biomedical Engineering, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China.
ZhiGang WangDepartment of Biomedical Engineering, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China.
ZhengGuo ZhangDepartment of Biomedical Engineering, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, Beijing 100005, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDuring the analysis of genomics data, it is often required to quantify the functional similarity of genes and their products based on the annotation information from gene ontology (GO) with hierarchical structure. A flexible and user-friendly way to estimate the functional similarity of genes utilizing GO annotation is therefore highly desired.

resultsWe proposed a novel algorithm using a level coefficient-weighted model to measure the functional similarity of gene products based on multiple ontologies of hierarchical GO annotations. The performance of our algorithm was evaluated and found to be superior to the other tested methods. We implemented the proposed algorithm in a software package, FSim, based on R statistical and computing environment. It can be used to discover functionally related genes for a given gene, group of genes, or set of function terms.

conclusionsFSim is a flexible tool to analyze functional gene groups based on the GO annotation databases.

Indexed as

AlgorithmsDatabases, GeneticDatabases, ProteinGenesGenomicsProteinsSoftwareProteins

Identifiers

PMID25184141
PMCPMC4145548

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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.