Power spectrum-based genomic feature extraction from high-throughput ChIP-seq sequences

Binhua Tang, Yufan Zhou, Victor X Jin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Due to its enhanced accuracy and high-throughput capability in capturing genetic activities, recently Next Generation Sequencing technology is being applied prevalently in biomedical study for tackling diverse topics. Within the work, we propose a computational method for answering such questions as deciding optimal argument pairs (peak number, p-value threshold, selected bin size and false discovery rate) from estrogen receptor α ChIP-seq data, and detecting corresponding transcription factor binding sites. We employ a signal processing-based approach to extract inherent genomic features from the identified transcription factor binding sites, which illuminates novel evidence for further analysis and experimental validation. Thus eventually we attempt to exploit the potentiality of ChIP-seq for deep comprehension of inherent biological meanings from the high-throughput genomic sequences.

Original languageEnglish (US)
Title of host publicationIntelligent Computing Theories and Application - 12th International Conference, ICIC 2016, Proceedings
EditorsPrashan Premaratne, De-Shuang Huang, Vitoantonio Bevilacqua
PublisherSpringer Verlag
Pages439-447
Number of pages9
ISBN (Print)9783319422909
DOIs
StatePublished - Jan 1 2016
Event12th International Conference on Intelligent Computing Theories and Application, ICIC 2016 - Lanzhou, China
Duration: Aug 2 2016Aug 5 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9771
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other12th International Conference on Intelligent Computing Theories and Application, ICIC 2016
CountryChina
CityLanzhou
Period8/2/168/5/16

Keywords

  • ChIP-seq
  • Comprehensive analysis
  • Genomic feature
  • Optimal argument pair
  • Transcription factor binding site

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Power spectrum-based genomic feature extraction from high-throughput ChIP-seq sequences'. Together they form a unique fingerprint.

  • Cite this

    Tang, B., Zhou, Y., & Jin, V. X. (2016). Power spectrum-based genomic feature extraction from high-throughput ChIP-seq sequences. In P. Premaratne, D-S. Huang, & V. Bevilacqua (Eds.), Intelligent Computing Theories and Application - 12th International Conference, ICIC 2016, Proceedings (pp. 439-447). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9771). Springer Verlag. https://doi.org/10.1007/978-3-319-42291-6_44