Evidence map›Paper›PMID 28143579›Full record

ArticleTheoretical biology & medical modelling2017

Method for generating multiple risky barcodes of complex diseases using ant colony algorithm.

Xiong Li, Wen Jiang

Abstract read
In one paragraph

Article in Theoretical biology & medical modelling, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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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

2 authors.

Xiong LiSchool of Software, East China Jiaotong University, Nanchang, 330013, China. lx_hncs@163.com.
Wen JiangSoftware School, Hunan Vocational College Of Science and Technology, Changsha, Hunan, 410118, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSusceptible barcode recognition plays an important role in the diagnosis and treatment of complex diseases. Numerous approaches have been proposed to identify risky barcodes involved in the progress of complex diseases. However, some methods only consider differences in barcode frequencies between the control and disease groups; as such, these methods may be partial or even wrong. For example, some barcodes with a high risk ratio yield a low frequency on cases or exhibit a high frequency on controls, which may unreasonable from a statistical point.

resultsIn our study, a stricter criteria, maximum discrepancy and maximum constituency, is designed to evaluate each barcode and ant colony algorithm is used to search combination space of epistasis. For complex diseases with multi-subtypes, our method can list several potential barcodes contributing to different subtypes of complex diseases. Another contribution of this work is to introduce a method for determining the length of barcodes and excluding noisy barcodes whose frequencies are abnormal. In addition, common pathogenic genes shared by different risky barcodes are also recognized, which may provide key clue for further study, such as gene function analysis.

conclusionsExperimental results reveal that our method can find multiple risky barcodes whose risk ratio and odds ratio are >1. These barcodes could be related to different subtypes of complex diseases.

Indexed as

AlgorithmsModels, GeneticAnimalsAntsBreast NeoplasmsDNA Barcoding, TaxonomicFemaleHumansPolymorphism, Single NucleotideRisk FactorsAnt colony algorithmComplex diseasesEpistasisSingle nucleotide polymorphisms

Identifiers

PMID28143579
PMCPMC5286784

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LicenceCC BY
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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.