Evidence map›Paper›PMID 27716040›Full record

ArticleBMC bioinformatics2016

A decision analysis model for KEGG pathway analysis.

Junli Du, Manlin Li, Zhifa Yuan, Mancai Guo, Jiuzhou Song, Xiaozhen Xie, Yulin Chen

Abstract read
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Article in BMC bioinformatics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

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48citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

48 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Junli DuCollege of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
Manlin LiCollege of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
Zhifa YuanCollege of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
Mancai GuoCollege of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
Jiuzhou SongDepartment of Animal and Avian Sciences, University of Maryland, College Park, MD, 20742, USA.
Xiaozhen XieCollege of sciences, Northwest A&F University, Yangling, 712100, People's Republic of China.
Yulin ChenCollege of Animal Science and Technology, Northwest A&F University, Yangling, 712100, People's Republic of China. liml75@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe knowledge base-driven pathway analysis is becoming the first choice for many investigators, in that it not only can reduce the complexity of functional analysis by grouping thousands of genes into just several hundred pathways, but also can increase the explanatory power for the experiment by identifying active pathways in different conditions. However, current approaches are designed to analyze a biological system assuming that each pathway is independent of the other pathways.

resultsA decision analysis model is developed in this article that accounts for dependence among pathways in time-course experiments and multiple treatments experiments. This model introduces a decision coefficient-a designed index, to identify the most relevant pathways in a given experiment by taking into account not only the direct determination factor of each Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway itself, but also the indirect determination factors from its related pathways. Meanwhile, the direct and indirect determination factors of each pathway are employed to demonstrate the regulation mechanisms among KEGG pathways, and the sign of decision coefficient can be used to preliminarily estimate the impact direction of each KEGG pathway. The simulation study of decision analysis demonstrated the application of decision analysis model for KEGG pathway analysis.

conclusionsA microarray dataset from bovine mammary tissue over entire lactation cycle was used to further illustrate our strategy. The results showed that the decision analysis model can provide the promising and more biologically meaningful results. Therefore, the decision analysis model is an initial attempt of optimizing pathway analysis methodology.

Indexed as

Decision Support TechniquesSignal TransductionAnimalsCattleComputational BiologyDatabases, FactualFemaleGene Expression ProfilingGenomeLactationMammary Glands, AnimalTranscriptomeBovine mammaryCoefficient of determination (CD)Decision coefficient (DC)Pathway analysis

Identifiers

PMID27716040
PMCPMC5053338

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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.