@inproceedings{3c029a35dc344f809a28a5df0ef7ac38,
title = "Prediction of biological functions by histone modification patterns profiling",
abstract = "Histone modifications provide an important layer of gene regulation in eukaryotes. In this paper, we propose an approach that identifies the histone modification patterns most relevant for specific biological functions, such as flowering in plants. We first propose a new pattern scoring method, which evaluates the importance of each combinatorial pattern of histone modifications; this is used along with logistic regression, Support Vector Machines, and naive Bayesian classifier algorithms to predict gene functions. This approach is shown to be successful in inferring significant patterns verified by independent gene function data, outperforming other pattern scores used in current histone modification analysis research.",
keywords = "Gene expression, Histone modification, Predicting biological function",
author = "Yiou Xiao and Mehrotra, {Kishan G.} and Mohan, {Chilukuri K.} and Pratibha Choudhary and Ramesh Raina",
year = "2017",
language = "English (US)",
series = "Proceedings of the 9th International Conference on Bioinformatics and Computational Biology, BICOB 2017",
publisher = "The International Society for Computers and Their Applications (ISCA)",
pages = "217--222",
editor = "Hisham Al-Mubaid and Oliver Eulenstein and Qin Ding",
booktitle = "Proceedings of the 9th International Conference on Bioinformatics and Computational Biology, BICOB 2017",
note = "9th International Conference on Bioinformatics and Computational Biology, BICOB 2017 ; Conference date: 20-03-2017 Through 22-03-2017",
}