Learning Bayesian Network Classifiers: Searching in a Space of Partially Directed Acyclic Graphs

Acid, Silvia; Campos, Luis M. de; Castellano, Javier G.

doi:10.1007/s10994-005-0473-4

Cited by 51 publications

(30 citation statements)

References 22 publications

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“…Despite their interest and the corroboration that functionally related, genomically distant genes show similar gene-by-environment (G×E) interactions, these nominally significant effects did not survive Bonferroni correction for multiple testing. To reach an optimal correction for multiple-hypotheses testing concerning the numerous potential dependencies between multiple predictors and phenotypes, we applied a systems-based approach in the second phase using the Bayesian model averaging framework (58)(59)(60). This approach allowed the principled and detailed investigation of G×E interactions as model properties.…”

Section: Resultsmentioning

confidence: 99%

Brain galanin system genes interact with life stresses in depression-related phenotypes

Juhász

Hullám

Eszlári

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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Galanin is a stress-inducible neuropeptide and cotransmitter in serotonin and norepinephrine neurons with a possible role in stress-related disorders. Here we report that variants in genes for galanin (GAL) and its receptors (GALR1, GALR2, GALR3), despite their disparate genomic loci, conferred increased risk of depression and anxiety in people who experienced childhood adversity or recent negative life events in a European white population cohort totaling 2,361 from Manchester, United Kingdom and Budapest, Hungary. Bayesian multivariate analysis revealed a greater relevance of galanin system genes in highly stressed subjects compared with subjects with moderate or low life stress. Using the same method, the effect of the galanin system genes was stronger than the effect of the well-studied 5-HTTLPR polymorphism in the serotonin transporter gene (SLC6A4). Conventional multivariate analysis using general linear models demonstrated that interaction of galanin system genes with life stressors explained more variance (1.7%, P = 0.005) than the life stress-only model. This effect replicated in independent analysis of the Manchester and Budapest subpopulations, and in males and females. The results suggest that the galanin pathway plays an important role in the pathogenesis of depression in humans by increasing the vulnerability to early and recent psychosocial stress. Correcting abnormal galanin function in depression could prove to be a novel target for drug development. The findings further emphasize the importance of modeling environmental interaction in finding new genes for depression.galanin receptors | mood disorders | network-based analysis | neurogenesis | transmitter coexistence M ajor depressive disorder (MDD) is a common and serious disease afflicting more women than men, and a leading cause of disability worldwide, associated with much suffering and major costs for society (1, 2). Environmental psychosocial stressors are important in pathogenesis, because episodes are usually preceded by adverse life events, and early childhood experiences of physical and emotional abuse and parental neglect are important vulnerability factors (3, 4). Genetic vulnerability is significant with a heritability of about 35% (5). We remain ignorant about the brain processes that translate these genetic and environmental influences into depressive symptoms or risk. A major clue is that effective antidepressant drugs act directly or indirectly to enhance neurotransmission in serotonin (5-HT) and norepinephrine monoamine pathways, proving the monoamine hypothesis of depression (6-8). Many other candidate mechanisms have been identified in anatomical, pharmacological, and behavioral studies of stress in rodents. However, the demonstration of stateor trait-related abnormalities in human monoamine or other neural systems remains frustratingly elusive, despite modern brain-imaging methods. To determine whether the neuropeptide galanin has a role in depression, we used a unique Bayesian systems-based analysis to dissect out the influ...

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Section: Resultsmentioning

confidence: 99%

Brain galanin system genes interact with life stresses in depression-related phenotypes

Juhász

Hullám

Eszlári

et al. 2014

Proc. Natl. Acad. Sci. U.S.A.

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“…The reason to include a Bayesian multinet classifier in the experiments is to find Cellular Context Mining [41] and represent it with asymmetrical independences. The use of the C-RPDAG algorithm is motivated for its good results [11].…”

Section: Methodsmentioning

confidence: 99%

“…The method carries out a simple local search in a space composed of a type of partially directed acyclic graphs (PDAGs), which combine two concepts of equivalence of DAGs: classification equivalence and independence equivalence. Using the BDeu score, this algorithm has proved more effective than other Bayesian network classifiers [11].…”

Section: Introductionmentioning

confidence: 99%

Bayesian networks classifiers for gene-expression data

Campos

Cano

Castellano

et al. 2011

2011 11th International Conference on Intelligent Systems Design and Applications

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Abstract-In this work, we study the application of Bayesian networks classifiers for gene expression data in three ways: first, we made an exhaustive state-of-art of Bayesian classifiers and Bayesian classifiers induced from microarray data. Second, we propose a preprocessing scheme for gene expression data, to induce Bayesian classifiers. Third, we evaluate different Bayesian classifiers for this kind of data, including the C-RPDAG classifier presented by the authors.

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“…As we had previous experience in automatic classification, particularly in learning Bayesian network classifiers [1,3], we have limited our participation only to the task of text categorization.…”

Section: Introductionmentioning

confidence: 99%

Probabilistic Methods for Structured Document Classification at INEX’07

Campos

Fernández‐Luna

Huete

et al. 2008

Focused Access to XML Documents

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Abstract. This paper exposes the results of our participation in the Document Mining track at INEX'07. We have focused on the task of classification of XML documents. Our approach to deal with structured document representations uses classification methods for plain text, applied to flattened versions of the documents, where some of their structural properties have been translated to plain text. We have explored several options to convert structured documents into flat documents, in combination with two probabilistic methods for text categorization. The main conclusion of our experiments is that taking advantage of document structure to improve classification results is a difficult task.

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Learning Bayesian Network Classifiers: Searching in a Space of Partially Directed Acyclic Graphs

Cited by 51 publications

References 22 publications

Brain galanin system genes interact with life stresses in depression-related phenotypes

Brain galanin system genes interact with life stresses in depression-related phenotypes

Bayesian networks classifiers for gene-expression data

Probabilistic Methods for Structured Document Classification at INEX’07

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