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Algorithms in Bioinformatics
Theory and Implementation
Paul A. Gagniuc
University Politehnica of Bucharest
Bucharest, Romania

This first edition first published 2021
© 2021 John Wiley & Sons, Inc.
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The contents of this work are intended to further general scientific research, understanding, and discussion only and are not intended and should not be relied upon as recommending or promoting scientific method, diagnosis, or treatment by physicians for any particular patient. In view of ongoing research, equipment modifications, changes in governmental regulations, and the constant flow of information relating to the use of medicines, equipment, and devices, the reader is urged to review and evaluate the information provided in the package insert or instructions for each medicine, equipment, or device for, among other things, any changes in the instructions or indication of usage and for added warnings and precautions. While the publisher and authors have used their best efforts in preparing this work, they make no representations or warranties with respect to the accuracy or completeness of the contents of this work and specifically disclaim all warranties, including without limitation any implied warranties of merchantability or fitness for a particular purpose. No warranty may be created or extended by sales representatives, written sales materials or promotional statements for this work. The fact that an organization, website, or product is referred to in this work as a citation and/or potential source of further information does not mean that the publisher and authors endorse the information or services the organization, website, or product may provide or recommendations it may make. This work is sold with the understanding that the publisher is not engaged in rendering professional services. The advice and strategies contained herein may not be suitable for your situation. You should consult with a specialist where appropriate. Further, readers should be aware that websites listed in this work may have changed or disappeared between when this work was written and when it is read. Neither the publisher nor authors shall be liable for any loss of profit or any other commercial damages, including but not limited to special, incidental, consequential, or other damages.
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.
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.
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