Comput Methods Programs Biomed - Ensemble transcript interaction networks: a case study on Alzheimer's disease.

Tópicos

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Resumo

Systems biology techniques are a topic of recent interest within the neurological field. Computational intelligence (CI) addresses this holistic perspective by means of consensus or ensemble techniques ultimately capable of uncovering new and relevant findings. In this paper, we propose the application of a CI approach based on ensemble Bayesian network classifiers and multivariate feature subset selection to induce probabilistic dependences that could match or unveil biological relationships. The research focuses on the analysis of high-throughput Alzheimer's disease (AD) transcript profiling. The analysis is conducted from two perspectives. First, we compare the expression profiles of hippocampus subregion entorhinal cortex (EC) samples of AD patients and controls. Second, we use the ensemble approach to study four types of samples: EC and dentate gyrus (DG) samples from both patients and controls. Results disclose transcript interaction networks with remarkable structures and genes not directly related to AD by previous studies. The ensemble is able to identify a variety of transcripts that play key roles in other neurological pathologies. Classical statistical assessment by means of non-parametric tests confirms the relevance of the majority of the transcripts. The ensemble approach pinpoints key metabolic mechanisms that could lead to new findings in the pathogenesis and development of AD.

Resumo Limpo

system biolog techniqu topic recent interest within neurolog field comput intellig ci address holist perspect mean consensus ensembl techniqu ultim capabl uncov new relev find paper propos applic ci approach base ensembl bayesian network classifi multivari featur subset select induc probabilist depend match unveil biolog relationship research focus analysi highthroughput alzheim diseas ad transcript profil analysi conduct two perspect first compar express profil hippocampus subregion entorhin cortex ec sampl ad patient control second use ensembl approach studi four type sampl ec dentat gyrus dg sampl patient control result disclos transcript interact network remark structur gene direct relat ad previous studi ensembl abl identifi varieti transcript play key role neurolog patholog classic statist assess mean nonparametr test confirm relev major transcript ensembl approach pinpoint key metabol mechan lead new find pathogenesi develop ad

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