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Overview of Multiple Sequence Alignment Algorithms

Developed by Yu He (TA for Bio 4342), this PowerPoint presentation provides a basic overview of the common algorithms used to generate multiple sequence alignments. The presentation also illustrates how one could use Clustal Omega to generate a multiple sequence alignment for a set of orthologous proteins in order to identify conserved domains within the protein.

Eukaryotic Comparative Genomics

This lecture from Dr. Barak Cohen discusses the major factors to consider (e.g., species to analyze, model for conserved sequences) when using phylogenetic footprinting to identify conserved regions across multiple species. The lecture also illustrates how the weight matrix model can be used to describe sequence motifs, and it provides an introduction to Magma, which uses the multiple species with multiple genes approach to discover conserved motifs.

From Smith-Waterman to BLAST

This lecture from Dr. Jeremy Buhler discusses the limitations of the Smith-Waterman local alignment algorithm and the heuristics used by the BLAST program in order to reduce the search space and to quickly produce high-scoring local alignments.

Introduction to Dynamic Programming

Developed by Dr. Anton E. Weisstein (Truman State University) and Mingchao Xie (TA for Bio 4342), this lecture and exercise introduce students to the core algorithm (dynamic programming) used by many sequence alignment tools (e.g., BLAST). The exercise includes a spreadsheet with a dynamic programming matrix that allows students to explore the impact of different types of alignments (i.e. global, semiglobal, and local) and scoring systems on the resulting sequence alignment.

An Introduction to Hidden Markov Models

Developed by Dr. Anton E. Weisstein (Truman State University), Zongtai Qi and Zane Goodwin (TAs for Bio 4342), this curriculum introduces students to the idea of Hidden Markov Models (HMM) that forms the core component of most gene predictors. The lecture by Zongtai Qi uses weather prediction to illustrate the key concepts of the HMM, whereas the lecture by Zane Goodwin focuses on the HMM that models a splice donor site. The exercise developed by Dr. Weisstein includes a spreadsheet with a simple HMM exercise that models a splice donor site. The spreadsheet allows students to examine the impact of different transition and emission probabilities on splice site predictions. A video recording of Dr. Weisstein’s HMM presentation during the 2014 GEP Alumni Workshop is also available online. This HMM curriculum is also available on CourseSource.
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Introduction to ab initio and Evidence-based Gene Finding

This PowerPoint presentation examines the use of gene prediction programs (such as Genscan) in annotation, noting some of the limitations of gene prediction programs in creating putative gene models. It also introduces the UCSC and other browsers as sources of supporting evidence.

Basics of BLAST

This PowerPoint presentation provides a brief introduction to the different kind of BLAST searches available.