Scalable Big Data Analytics for Protein Bioinformatics

Efficient Computational Solutions for Protein Structures

Autor: Dariusz Mrozek

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Legare: Copertă tare

Editura: Springer International Publishing AG

Disponibilitate: În depozitul extern

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This book presents a focus on proteins and their structures. The text describes various scalable sol...

Informații despre carte

Autor

Dariusz Mrozek

Limbă

engleză

Legare

Carte - Copertă tare

Publicat

2018

Pagini

315

EAN

9783319988382

ISBN

3319988387

Enbook ID

19777120

Editura

Springer International Publishing AG

Greutate

823

Dimensiuni

155 x 235 x 19

Descriere completă

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.

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Scalable Big Data Analytics for Protein Bioinformatics

Efficient Computational Solutions for Protein Structures

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