Introduction to Bioinformatics Course: Lectures and Other Materials                     

20 BME 643; Instructor: Jarek Meller

The Introduction to Bioinformatics is a multidisciplinary, entry level graduate course, which is offered each Spring as part of the curriculum for the graduate program in bioinformatics in the Dept. of Biomedical Engineering (BME) of the University of Cincinnati. For more information click here or contact me directly (you may send me an email using the following submission page, please add the phrase "intro2bioinfo" to "your name" line). 

Lectures '04


Lecture #1: Overview of the Course, Bioinfomatics as a Field of Study (ppt file)

Lecture #2: From Molecular Processes to String Matching (ppt file)

Lecture #3: Genome Assembly and String Matching (ppt file)

Lecture #4: From Suffix Trees to Approximate String Matching (ppt file)

Lecture #5: Alignment Counting and Dynamic Programming (ppt file)

Lecture #6: Multiple alignment, family profiles, entropy (Perl)

Lecture #7: Clustering and unsupervised learning (ppt file)

Lecture #8: Classification and supervised learning (ppt file)

Lecture #9: K-means vs. k-NN (Perl)

Lecture #10: Applying machine learning techniques to gene prediction (Perl)

Lecture #10: Additional materials: computational gene finding

Lecture #11: Protein structure prediction (ppt file)

Lecture #13: Hidden Markov Models (ppt file)

Lecture #14: From sequence alignment and PsiBLAST to fold recogniotion (hands-on)

Lecture #15: Molecular Dynamics (ppt file)

Lecture #16: Global optimization and Monte Carlo (ppt file)


Note that the titles of the lectures may not fully represent the actual content, which may be adjusted to address problems from previous lectures as well as additional topics. The title should still represent the main theme for each lecture.


See also a fragment of my recent write up, covering alignment problem, dynamic programming, protein folding and structure prediction and a couple of other topics: book fragment


Seminar (tmp)


Author: Jarek Meller