Fundamentals of Bioinformatics and Computational Biology by Gautam B. Singh

The integration of computers in life sciences has been growing for the last two decades. While the first release of GenBank contained a mere half a million DNA sequence bases in 1982, the current release of GenBank has exceeded 100 giga bases of data. With data comes computational challenges for analysis, interpretation, visualization and integration of information. That in a nutshell is the reason to familiarize undergraduate students in computer science and engineering with the nature and use of biological data and thus become prepared to meet the demands of high tech careers in the twenty-first century. The intended audience of this textbook are students in computer science, engineering and information technology at the undergraduate or lower graduate level. The material is primarily presented in a simplified manner and extensive details are left out. However, pointers to appropriate references should guide those who are interested in exploring specific topics in greater detail. Topics in this textbook are organized into three parts. Part I of this book provides some background to the field of bioinformatics and an introduction to molecular biology and genetics. A survey of biological databases is also included. The material in this part is considered to be fairly fundamental and should be covered in all courses, graduate and undergraduate. Part II of the book covers methodologies for retrieving information from biological databases and covers simple boolean searches, sequence alignment algorithms, protein alignment, scoring matrices, alignment tools and biolinguistic methods. Undergraduate students should cover basic retrieval techniques and advanced topics such as PAM and BLOSUM may be included based on the amount of time available and level of preparation of the students. Part III of the book covers the topics related to sequence analysis and covers algorithms for finding patterns and detecting genes. Part IV focuses ontopics in phylogenetics and systems biology and covers the algorithms for distance, character and probabilistic methods for inferring phylogeny. Also described are some key algorithms for analyzing micro-chip data. The book is an offshoot of our project aimed at creating bioinformatics educational resources for undergraduates in computer science and engineering. This project is sponsored by the National Science Foundation, USA. Additional details for the project and bioinformatics educational resources are available from The author would like to acknowledge the efforts by students who participated in creating resources for the NSF sponsored bioinformatics project: Kenneth DeMonn, Nirmala Venkatraman, David Poe, Guy Lima, Kellie McGowan and Ashwin Kottam. Their work influenced the content and the presentation in this text. For the BioFlow project we are also analyzing student learning styles in collaboration with Professor Christine Hansen, Department of Psychology, Oakland University. The results from obtained from the student assessment studies were very valuable in providing insight into methods that made this text more comprehensible for computer science and engineering undergraduates.

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