Chapter 1 presents fundamental concepts from molecular biology. We describe the basicstructure and function of proteins and nucleic acids, the mechanisms of molecular genetics,the most important laboratory techniques for studying the genome of organisms, andan overview of existing sequence databases.Chapter 2 describes strings and graphs, two of the most important mathematical objectsused in the book. A brief exposition of general concepts of algorithms and theiranalysis is also given, covering definitions from the theory of NP-completeness.The following chapters are based on specific problems in molecular biology. Chapter3 deals with sequence comparison. The basic two-sequence problem is studied andthe classic dynamic programming algorithm is given. We then study extensions of thisalgorithm, which are used to deal with more general cases of the problem. A section is devotedto the multiple-sequence comparison problem. Other sections deal with programsused in database searches, and with some other miscellaneous issues.Chapter 4 covers the fragment assembly problem. This problem arises when a DNAsequence is broken into small fragments, which must then be assembled to reconstitutethe original molecule. This is a technique widely used in large-scale sequencing projects,such as the Human Genome Project. We show how various complications make thisproblem quite hard to solve. We then present some models for simplified versions of theproblem. Later sections deal with algorithms and heuristics based on these models.Chapter 5 covers the physical mapping problem. This can be considered as fragmentassembly on a larger scale. Fragments are much longer, and for this reason assemblytechniques are completely different. The aim is to obtain the location of some markersalong the original DNA molecule. A brief survey of techniques and models is given.We then describe an algorithm for th

My primary intent in writing this book is to provide the reader with basic programming, financial, and mathematical tools that can be successfully leveraged both in industry and academia. I cover the use of the R programming language, as well as the R environment as a means for manipulating financial market data and for solving a subset of problems that quants and traders typically encounter in their day-to-day activities. The chapters that follow should be treated as a tutorial on a recommended set of tools that I have personally found useful and that have served me well during the last few years of my career as a quant trader/developer. I am writing this book from the vantage point of a quant practitioner and not that of an academic. A significant portion of the content is based on my lecture notes from a graduate level class in quantitative finance that I teach on a part-time basis at Loyola University in Chicago.

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Context-Based, Adaptive, Lossless Image Coding (CALIC)