Overview
- Highlights the potential held by new computational techniques, such as cloud computing and big data technologies, in connection with protein bioinformatics
- Chiefly focuses on protein structure, which remains poorly understood and is not effectively used in medicine
- Describes methods for applying structural bioinformatics in medical diagnostics
Part of the book series: Computational Biology (COBO, volume 28)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (11 chapters)
-
Front Matter
-
Cloud Services for Scalable Computations
-
Front Matter
-
-
Big Data Analytics in Protein Bioinformatics
-
Front Matter
-
-
Multi-threaded Solutions for Protein Bioinformatics
-
Front Matter
-
-
Back Matter
Keywords
About this book
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 Datacomputational 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.
Reviews
“This excellent and practically oriented text can benefit researchers seeking to establish a cloud-based bioinformatics HPC facility. Note that most of the solutions are implemented as embarrassingly parallel processes and not as distributed parallel processes. The book will be of interest to researchers and scientific software developers of bioinformatics and biomedical databases.” (Alexander Tzanov, Computing Reviews, June 06, 2019)
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Scalable Big Data Analytics for Protein Bioinformatics
Book Subtitle: Efficient Computational Solutions for Protein Structures
Authors: Dariusz Mrozek
Series Title: Computational Biology
DOI: https://doi.org/10.1007/978-3-319-98839-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer Nature Switzerland AG 2018
Hardcover ISBN: 978-3-319-98838-2Published: 09 October 2018
Softcover ISBN: 978-3-030-07538-5Published: 26 December 2018
eBook ISBN: 978-3-319-98839-9Published: 25 September 2018
Series ISSN: 1568-2684
Series E-ISSN: 2662-2432
Edition Number: 1
Number of Pages: XXVI, 315
Number of Illustrations: 41 b/w illustrations, 110 illustrations in colour
Topics: Computational Biology/Bioinformatics, Computer Communication Networks, Protein Structure, Bioinformatics, Mathematical and Computational Biology