Romania
This first edition first published 2021
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Library of Congress Cataloging-in-Publication Data
Names: Gagniuc, Paul A., author.
Title: Algorithms in bioinformatics : theory and implementation / Paul A. Gagniuc, Polytechnic University of Bucharest, Bucharest, Romania.
Description: First edition. | Hoboken, NJ : Wiley, 2021. | Includes bibliographical references and index.
Identifiers: LCCN 2021004386 (print) | LCCN 2021004387 (ebook) | ISBN 9781119697961 (cloth) | ISBN 9781119697954 (adobe pdf) | ISBN 9781119697992 (epub)
Subjects: LCSH: Bioinformatics. | Algorithms.
Classification: LCC QH324.2 .G34 2021 (print) | LCC QH324.2 (ebook) | DDC 570.285–dc23
LC record available at https://lccn.loc.gov/2021004386
LC ebook record available at https://lccn.loc.gov/2021004387
Cover Design: Wiley
Cover Image: © Science Photo Library/Alamy Stock Photo
I dedicate this book to my family,
my children Nichita and Ana,
my beautiful wife Elvira,
and to my mother-in-law Anastasia.
Preface
Algorithms in Bioinformatics: Theory and Implementation is a concise yet comprehensive textbook of bioinformatics, which describes some of the main algorithms that are used to elucidate biological functions and relationships. This unique guide to Algorithms in Bioinformatics approaches the subject along the four convergent lines of mathematics, implementation, simulation, experimentation, and can be ideal for upper-undergraduate bioinformatics courses, researchers, doctoral students, and sociologists or engineers charged with data analysis. This work first begins with a general introduction to biology, which is meant to bring a more concrete understanding of the molecular processes concerning the field of bioinformatics. Following this introduction, an in-detail look is made to subjects like sequence alignment, forced alignment, detection of motifs, sequence logos, Markov chains, or information entropy. Other novel approaches are also described, such as self-sequence alignment, objective digital stains (ODSs) or spectral forecast, and the discrete probability detector (DPD) algorithm. This work also contains thorough step-by-step explanations regarding the meaning of the background models in bioinformatics from several angles. More importantly, it introduces the readers to the art of algorithms, shows how to design computer implementations, and provides extensive worked examples with detailed case studies. The implementations presented here point out how native programming in Javascript can broaden the horizons of possibilities in bioinformatics by considering the might of modern Internet browsers. Graphical illustrations are used for technical details on computational algorithms to aid an in-depth understanding of their inner workings. Moreover, this work brings to the reader's attention more than 100 open-source implementations and 33 Powerpoint presentations.
About the Companion Website
This book is accompanied by a companion website:
www.wiley.com/go/gagniuc/algorithmsinbioinformatics
The website includes the following:
Algorithms in JavaScript
Charts for visualization
PowerPoint presentations
Sequence alignment (Jupiter bioinformatics application)
HTML/JavaScript
