ISBN-13: 9783031204135 / Angielski / Twarda / 2023 / 411 str.
ISBN-13: 9783031204135 / Angielski / Twarda / 2023 / 411 str.
This self-contained textbook covers fundamental aspects of sequence analysis with special emphasis on evolutionary biology, including sequence alignment, exact matching, phylogeny reconstruction, and coalescent simulation. It addresses these topics through a series of over 800 computer problems, ranging from elementary to research level, to enable learning by doing. Students solve the problems in the same computational environment used for decades in science – the Unix command line. This is available on all four major operating systems for PCs: Windows, macOS, chromeOS, and Linux. To learn using this powerful system, students analyze sample sequence data by applying generic tools, bioinformatics software, and over 50 programs specifically written for this course and available via GitHub. The solutions for all problems are included, making the book ideal for self-study. Problems are grouped into sections headed by an introduction and a list of new terms. By using practical computing to explore sequence data in an evolutionary context, the book enables readers to tackle their own computational problems.
This self-contained textbook covers fundamental aspects of sequence analysis with special emphasis on evolutionary biology, including sequence alignment, exact matching, phylogeny reconstruction, and coalescent simulation. It addresses these topics through a series of over 800 computer problems, ranging from elementary to research level, to enable learning by doing. Students solve the problems in the same computational environment used for decades in science – the Unix command line. This is available on all four major operating systems for PCs: Windows, macOS, chromeOS, and Linux. To learn using this powerful system, students analyze sample sequence data by applying generic tools, bioinformatics software, and over 50 programs specifically written for this course and available via GitHub. The solutions for all problems are included, making the book ideal for self-study. Problems are grouped into sections headed by an introduction and a list of new terms. By using practical computing to explore sequence data in an evolutionary context, the book enables readers to tackle their own computational problems.