Introduction to Bioinformatics-Video Lecture-Watch Online

This course will cover bioinformatics concepts and methodologies. It seeks to emphasize the concepts behind the rapid development of the field, both to give conceptual understanding of these very new areas, and to give students a foundation for how to do innovative work in these fields. The course aims to teach the conceptual foundations for the student to be able to invent new kinds of bioinformatics. It seeks to teach this material through real problems and examples of solutions. The course emphasizes statistical inference and algorithmic complexity as the two foundations of bioinformatics. Bioinformatics can be described broadly as the study of the inherent structure of biological information. In practice this means that bioinformatics problems can be considered to reduce to the problem of discovering whatever patterns are present in the data. This has two components: algorithms for finding a given kind of pattern (and the inherent computational difficulty of finding that pattern), and ways to measure the strength of the evidence that a given pattern is statistically significant (i.e. not just “random noise”). We will consider both components in detail, and their inter-relationships on various problems. The course will cover bioinformatics algorithms, their foundations in genomics data, and their use for analysis and interpretation of genomics data. We’ll examine sequence analysis and comparative genomics algorithms to get an understanding of the fundamental computational issues for biological data search and analysis