Thomas Mailund

I am an associate professor in bioinformatics at Aarhus University, Denmark. My background in math and computer science but for the last decade my main focus has been on genetics and evolutionary studies, particularly comparative genomics, speciation, and gene flow between emerging species. I write as a hobby, but my books are all focused on topics I teach in my daily work, where I teach several classes on data science, statistics, programming, and computer science. I try to write the kinds of books I would like to use in my own teaching, or the kinds of books I would like to have had when I learned the topics myself. I do have some ambitions of writing popular science books as well, but I have not had the courage to try my writing skills on that yet. So far, I have stuck to more technical topics where I feel more at home. Still, that can't go on forever, so some day I will dare to write about genetics and human evolution without hiding behind maths.

Get an introduction to functional data structures using R and write more effective code and gain performance for your programs. This book teaches you workarounds because data in functional languages is not mutable: for example you’ll learn how to change variable-value bindings by modifying environments, which can be exploited to emulate pointers and implement traditional data structures. You’ll also see how, by abandoning traditional data structures, you can manipulate structures by building new versions rather than modifying them. You’ll discover how these so-called functional data structures are different from the traditional data structures you might know, but are worth understanding to do serious algorithmic programming in a functional language such as R. By the end of Functional Data Structures in R, you’ll understand the choices to make in order to most effectively work with data structures when you cannot modify the data itself. These techniques are especially applicable for algorithmic development important in big data, finance, and other data science applications. What You'll Learn Carry out algorithmic programming in RUse abstract data structuresWork with both immutable and persistent dataEmulate pointers and implement traditional data structures in RBuild new versions of traditional data structures that are known Who This Book Is For Experienced or advanced programmers with at least a comfort level with R. Some experience with data structures recommended.