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Title Details:
Biology of Big Data
Authors: Nikolaou, Christoforos
Chouvardas, Panagiotis
Reviewer: Bagkos, Panteleimon
Description:
Abstract:
This chapter addresses some of the latest advances in modern molecular biology under the unifying perspective of data analysis. Increasingly, conventional experimental approaches are replaced by large-scale methodologies through next-generation sequencing techniques. Biology gradually enters the era of big data. After an initial introduction to sequencing techniques and large-scale genomics as well as the types of data they generate, we focus on describing the main problems of modern genomics, such as mapping large numbers of sequences, identifying protein binding sites on DNA, and partitioning the genome into discrete regions based on specific properties. By the end of this chapter, you should be able to: Describe the basic protocol for conducting a next-generation sequencing experiment. List the most important methodologies for large-scale genomic analysis. Visualize genomic analysis data using genome browsers. Represent a sequence as a suffix tree and use this data structure to search for subsequences. Describe the creation of transcriptional regulatory networks using data from genome-wide studies.
Type: Chapter
Creation Date: 2015
Item Details:
License: http://creativecommons.org/licenses/by-nc-nd/3.0/gr
Handle http://hdl.handle.net/11419/1589
Bibliographic Reference: Nikolaou, C., & Chouvardas, P. (2015). Biology of Big Data [Chapter]. In Nikolaou, C., & Chouvardas, P. 2015. Computational Biology [Undergraduate textbook]. Kallipos, Open Academic Editions. https://hdl.handle.net/11419/1589
Language: Greek
Is Part of: Computational Biology
Number of pages 36
Publication Origin: Kallipos, Open Academic Editions