Bioinformatics

A One Semester Course
1. Auflage 2022
ISBN: 978-3-031-20019-9
Verlag: Springer International Publishing

Buch, Englisch, 128 Seiten, Format (B × H): 168 mm x 240 mm, Gewicht: 242 g

Reihe: Synthesis Lectures on Biomedical Engineering

This book focuses on bioinformatics, the study of the management and analysis of information used in biological systems.  Particular emphasis explains to the reader how to study and extract useful information, such as relatedness of species, function of specific sequences, and genome organization from genomic sequences. 

This book focuses on the algorithmic aspects of bioinformatics and not on databases and software packages.  There are two important discriminating characteristics that sets the book apart.  It connects the algorithmic aspects and approaches to bioinformatics with the biological context while maintaining a user friendly and accessible description of the algorithms. The authors have curated the content for use a stand alone reference or the book will fit a one semester course on the subject.

Zielgruppe

Upper undergraduate

Autoren/Hrsg.

Otu, Hasan H.

Sayood, Khalid

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Biophysik
• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Naturwissenschaften Biowissenschaften Biochemie (nichtmedizinisch)
• Naturwissenschaften Physik Angewandte Physik Biophysik
• Naturwissenschaften Biowissenschaften Biowissenschaften Evolutionsbiologie

Inhaltsverzeichnis

Introduction.- Molecular Biology Primer.- A bit of Biology.- Pairwise Sequence Alignment.- Multiple Sequence Alignment.- Molecular Phylogeny.

Über Autor(innen)

Khalid Sayood received the B.S. and M.S. degrees in electrical engineering from the University of Rochester, Rochester, NY, in 1977 and 1979, respectively, and the Ph.D. degree in electrical engineering from Texas A&M University, College Station, in 1982. From 1995 to 1996, he served as the Founding Head of the Computer Vision and Image Processing Group at the Turkish National Research Council Informatics Institute. From 1996 to 1997, he was a Visiting Professor with Bogazici University, Istanbul, Turkey. Since 1982, he has been with the University of Nebraska–Lincoln, where he is currently serving as a Professor in the Department of Electrical and Computer Engineering. He is the author of Introduction to Data Compression, 5th ed., Morgan Kaufmann, 2017, Understanding Circuits: Learning Problem Solving Using Circuit Analysis, Morgan & Claypool, 2005, Learning Programming Using MATLAB, Morgan & Claypool, 2006, Joint Source Channel Coding Using Arithmetic Codes, Morgan & Claypool, 2010,and Computational Genomic Signatures, Morgan & Claypool, 2011, and the Editor of Lossless Compression Handbook, Academic Press, 2002. His research interests include bioinformatics, data compression, and biological signal processing.
Hasan H. Otu obtained his B.S. degree in 1996 and his M.S. degree in 1997, both from Bogazici University, Department of Electrical and Electronics Engineering. In 2002, he graduated from the University of Nebraska-Lincoln with a Ph.D. in Electrical Engineering focusing on Bioinformatics. He has been a faculty member at Harvard Medical School (2003 - 2012), where he was a research fellow between 2002-2003. He is the founding director of the Bioinformatics Core at Beth Israel Deaconess Medical Center, Harvard Medical School and Associate Director of the Proteomics Core at Dana Farber Harvard Cancer Center. Between 2010-2013, he acted as the founding chair of the Department of Genetics and Bioengineering at Istanbul Bilgi University. Since 2013, he has been serving as Professor of Electrical and Computer Engineering at the University of Nebraska-Lincoln. His research interests are in Bioinformatics, focusing on macromolecular sequence analysis, microarrays, biomarker discovery, genetic variations, systems biology, and analysis of high throughput biological data within the context of networks.