Comput Biol Chem - Deciphering histone code of transcriptional regulation in malaria parasites by large-scale data mining.

Tópicos

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Resumo

Histone modifications play a major role in the regulation of gene expression. Accumulated evidence has shown that histone modifications mediate biological processes such as transcription cooperatively. This has led to the hypothesis of 'histone code' which suggests that combinations of different histone modifications correspond to unique chromatin states and have distinct functions. In this paper, we propose a framework based on association rule mining to discover the potential regulatory relations between histone modifications and gene expression in Plasmodium falciparum. Our approach can output rules with statistical significance. Some of the discovered rules are supported by literature of experimental results. Moreover, we have also discovered de novo rules which can guide further research in epigenetic regulation of transcription. Based on our association rules we build a model to predict gene expression, which outperforms a published Bayesian network model for gene expression prediction by histone modifications. The results of our study reveal mechanisms for histone modifications to regulate transcription in large-scale. Among our findings, the cooperation among histone modifications provides new evidence for the hypothesis of histone code. Furthermore, the rules output by our method can be used to predict the change of gene expression.

Resumo Limpo

histon modif play major role regul gene express accumul evid shown histon modif mediat biolog process transcript cooper led hypothesi histon code suggest combin differ histon modif correspond uniqu chromatin state distinct function paper propos framework base associ rule mine discov potenti regulatori relat histon modif gene express plasmodium falciparum approach can output rule statist signific discov rule support literatur experiment result moreov also discov de novo rule can guid research epigenet regul transcript base associ rule build model predict gene express outperform publish bayesian network model gene express predict histon modif result studi reveal mechan histon modif regul transcript largescal among find cooper among histon modif provid new evid hypothesi histon code furthermor rule output method can use predict chang gene express

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