Computational network biology aims to understand cell behavior through complex network analysis. The Chromatin ImmunoPrecipitation sequencing (ChIP-seq) technique allows interrogating the physical binding interactions between proteins and DNA using Next-Generation Sequencing. Taking advantage of this technique, in this study we propose a computational framework to analyze gene regulatory networks built from ChIP-seq data. We focus on two different cell lines: GM12878, a normal lymphoblastoid cell line, and K562, an immortalised myelogenous leukemia cell line. In the proposed framework, we preprocessed the data, derived network relationships in the data, analyzed their network properties, and identified differences between the two cell lines through network comparison analysis. Throughout our analysis, we identified known cancer genes and other genes that may play important roles in chronic myelogenous leukemia.

Analysis of Gene Regulatory Networks Inferred from ChIP-seq Data

Stamoulakatou E.;Piccardi C.;Masseroli M.
2019-01-01

Abstract

Computational network biology aims to understand cell behavior through complex network analysis. The Chromatin ImmunoPrecipitation sequencing (ChIP-seq) technique allows interrogating the physical binding interactions between proteins and DNA using Next-Generation Sequencing. Taking advantage of this technique, in this study we propose a computational framework to analyze gene regulatory networks built from ChIP-seq data. We focus on two different cell lines: GM12878, a normal lymphoblastoid cell line, and K562, an immortalised myelogenous leukemia cell line. In the proposed framework, we preprocessed the data, derived network relationships in the data, analyzed their network properties, and identified differences between the two cell lines through network comparison analysis. Throughout our analysis, we identified known cancer genes and other genes that may play important roles in chronic myelogenous leukemia.
2019
Bioinformatics and Biomedical Engineering
978-3-030-17937-3
978-3-030-17938-0
Bioinformatics; Biomolecular networks; Cancer; ChIP-seq; Next-Generation Sequencing; Transcription factors
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1102513
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