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Scalable big data analytics for prot...

Mrozek, Dariusz.

Scalable big data analytics for protein bioinformaticsefficient computational solutions for protein structures /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Scalable big data analytics for protein bioinformaticsby Dariusz Mrozek.
Reminder of title:	efficient computational solutions for protein structures /
Author:	Mrozek, Dariusz.
Published:	Cham :Springer International Publishing :2018.
Description:	xxvi, 315 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	ProteinsStructure.
Online resource:	https://doi.org/10.1007/978-3-319-98839-9
ISBN:	9783319988399$q(electronic bk.)

Scalable big data analytics for protein bioinformaticsefficient computational solutions for protein structures /
Mrozek, Dariusz.

Scalable big data analytics for protein bioinformaticsefficient computational solutions for protein structures /[electronic resource] :by Dariusz Mrozek. - Cham :Springer International Publishing :2018. - xxvi, 315 p. :ill., digital ;24 cm. - Computational biology,v.281568-2684 ;. - Computational biology ;v.20..

Formal Model of 3D Protein Structures for Functional Genomics, Comparative Bioinformatics, and Molecular Modeling -- Multithreaded PSS-SQL for Searching Databases of Secondary Structures -- GPU and CUDA for 3D Protein Structure Similarity Searching -- Cloud Computing for 3D Protein Structure Alignment -- General Discussion and Concluding Remarks.

This book presents a focus on proteins and their structures. The text describes various scalable solutions for protein structure similarity searching, carried out at main representation levels and for prediction of 3D structures of proteins. Emphasis is placed on techniques that can be used to accelerate similarity searches and protein structure modeling processes. The content of the book is divided into four parts. The first part provides background information on proteins and their representation levels, including a formal model of a 3D protein structure used in computational processes, and a brief overview of the technologies used in the solutions presented in the book. The second part of the book discusses Cloud services that are utilized in the development of scalable and reliable cloud applications for 3D protein structure similarity searching and protein structure prediction. The third part of the book shows the utilization of scalable Big Data computational frameworks, like Hadoop and Spark, in massive 3D protein structure alignments and identification of intrinsically disordered regions in protein structures. The fourth part of the book focuses on finding 3D protein structure similarities, accelerated with the use of GPUs and the use of multithreading and relational databases for efficient approximate searching on protein secondary structures. The book introduces advanced techniques and computational architectures that benefit from recent achievements in the field of computing and parallelism. Recent developments in computer science have allowed algorithms previously considered too time-consuming to now be efficiently used for applications in bioinformatics and the life sciences. Given its depth of coverage, the book will be of interest to researchers and software developers working in the fields of structural bioinformatics and biomedical databases.

ISBN: 9783319988399$q(electronic bk.)

Standard No.: 10.1007/978-3-319-98839-9doiSubjects--Topical Terms:

194956
Proteins
--Structure.

LC Class. No.: QP551

Dewey Class. No.: 612.01575

Scalable big data analytics for protein bioinformaticsefficient computational solutions for protein structures /
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