ChIPSeq Analysis with Bayesian Machine Learning

Title

ChIPSeq Analysis with Bayesian Machine Learning

Creator

Aniketh A.S.; John I.; Mathew J.; Katoch H.; Siddarth A.S.; Biju V.G.

Description

ChIP-sequencing, otherwise called ChIP-seq, is a technique used to identify protein co-operations with DNA. A crucial advancement to the field of bio-informatics, ChIP sequencing is conducted in research labs around the world to get a better understanding of the way transcription factors and other associated proteins influence the gene in many biological processes and in tackling disease states. ChIP-seq is predominantly a field under the domain of biotechnology, however recent advancements and development of tools to process ChIP data have turned the study into one involving bio-informatics, allowing computer scientists and lab technicians to work on an otherwise scholarly field of biochemistry, molecular biology, microbiology and biomedicine. This report illustrates the predominant work-flow undertaken to sequence chromatin from a cell and to gain insights on the gene/protein of interest. Another aspect added is to use Machine Learning with Bayesian statistical techniques for Peak Calling. The different stages enumerated in this paper have been completed either with the R language or on a Web Server titled Galaxy.org. 2019 IEEE.

Source

2019 International Conference on Data Science and Communication, IconDSC 2019

Date

2019-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Bio-Informatics; Chip-Sequencing; DNA; Machine Learning

Coverage

Aniketh A.S., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India; John I., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India; Mathew J., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India; Katoch H., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India; Siddarth A.S., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India; Biju V.G., Computer Science Engineering, Christ Faculty of Engineering, Deemed to be university, Bangalore, India

Rights

Restricted Access

Relation

ISBN: 978-153869319-3

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/IconDSC.2019.8816879

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