Algorithms in Computational Biology takes a deep dive into the tools used and common problems in bioinformatics (e.g.: sequence alignment, ordination) and explores the underlying algorithms that make them run. The algorithms used in sequence alignment come from an older problem in Computer Science called Fuzzy String Matching, or sometimes Inexact String Matching, from which an understanding of the solutions to these older problems imparts a stronger understanding of the Sequence Alignment problem. By briefly looking at the history of the problem and solutions, and then taking a deeper look at the mechanics of the algorithm, readers will improve their understanding of their science and be more able to accurately and efficiently implement solutions in Computational Biology. Each chapter of the book provides its own look at a problem-algorithm pairing. Each chapter is comprised of a brief history, which describes the problem, then restates the problem more succinctly in algorithmic and mathematical terms, and then presents known solutions to those algorithms. The book begins with a "state of computational biology" Introduction, and ends with a concluding chapter wherein the next problems of computational biology are described and explored. This book is intended to be an independent resource for someone wanting to learn more about computational biology, formatted in an interesting and accessible way. Algorithms in Computational Biology provides a bridge for Computational Scientists, talking about something they know: the algorithm, and Biologists, talking about something they know: the biology. By making the other half just accessible enough, and walking that line, both can gain a deeper understanding and appreciation for the other.