Coursework Materials

The largest difficulty for schools establishing any new effort, including Bioinformatics, is the development of the curriculum. As a part of a project funded by the NIH's Institute of General Medical Science's Minority Access to Research Careers (MARC) program , a series of model courses for a graduate certificate in bioinformatics were developed for the three major domains of Bioinformatics: Biology, Computational Science and Mathematics. These materials include lectures, overheads with annotation, laboratory examples, test materials, student projects, and evaluation materials.

Bioinformatics University disseminates these original coursework materials for instructors to modify and use to help establish bioinformatics coursework on their own campuses without charge. The distribution of these coursework materials is through the Instructor Materials section of bioinformatics University. Materials have been developed for the following courses:

Biological Science Coursework

  • Bioinformatics I: Sequence Analysis
Target Audience: Biological Scientists

This course is designed to provide an understanding of important topics in applied bioinformatics and computational biology. Students will be able to learn about problems involved in the analysis of DNA and protein sequences. The course is intended to provide a good understanding of the commonly used algorithms in the analysis of genomic data, hands-on experiences with accessing and using relevant databases, the use of advanced computer programs for sequence analysis, protein structure modeling and a basic overview of genome assembly and analysis.
  • Bioinformatics II: Structural Analysis
Target Audience: Biological Scientists

This course is designed to provide an understanding of important topics in applied bioinformatics and computational biology. Students will be able to learn about problems involved in the analysis of biological data for modeling biological structures, emphasizing protein structures. The course is intended to provide a good understanding of the commonly used algorithms in the analysis of structural data, hands-on experiences with accessing and using relevant databases, the use of advanced computer programs for protein structure modeling and a basic overview of proteome analysis.
  • Molecular Biology for Bioinformatics
Target Audience: Students without a strong Biology background including Computer Scientists and Mathematicians

This course provides a broad introduction of Molecular Biology relevant to bioinformatics including the central dogma of molecular biology, the amino acids and their properties, secondary and tertiary structure, as well as an introduction of the various types of mutations that can occur as sequences evolve.

Computer Science Coursework

  • Algorithms for Biological Sequence Analysis
Target Audience: Computer Scientists

This course aims at providing a unifying overview of sequence analysis methods of use in modern computational molecular biology. The main topics covered include pairwise alignment, hidden Markov models, multiple alignment, profile searches, RNA secondary structure analysis, and phylogenic inference. The course is intended for computer scientists wishing to pursue a research career in computational molecular biology.
  • Bioinformatics Data Management
Target Audience: Computer Scientists

This course is an introduction to the concepts of Data Base Management and Information Retrieval most commonly applicable to Bioinformatics data and database systems. The course is intended for Computer Science students wishing to understand database issues in Bioinformatics. The first half of the course discusses relational databases and the second half covers information retrieval systems.

  • Essential Computing for Bioinformatics
Target Audience: Biology and other science students

This course provides a broad introductory discussion of essential computer science concepts that have wide applicability in the natural sciences. Particular emphasis will be placed on applications to bioinformatics. The concepts will be motivated by practical problems arising from the use of bioinformatics research tools such as genetic sequence databases. Concepts will be discussed in a weekly lecture and will be practiced via simple programming exercises using Python, an easy to learn and widely available scripting language.


Mathematical/Statistical Coursework

  • Mathematical Elements for Bioinformatics
Target Audience: Students From Mathematics, Statistics, and Computer Science.

The goal of this course is to provide review in mathematical foundation of probability and the general structure for statistical analysis of a wide variety of sequence analysis problems for students interested in basic training, learning and pursuing research in computational biology, genomics, and bioinformatics. Materials and examples will be present in biological context and their relevance to biological findings.

In addition to containing coursework information the INSTRUCTOR MATERIALS section also contains instructor forums where instructors can post questions, comments and suggestions about the materials as well as sources of additional supplemental materials that may be useful for the teaching of Bioinformatics.

Access to the Instructor Materials section is intended only for faculty and staff who have a need to teach bioinformatics as a part of their teaching responsibilities. Access to the Instructor Materials section of the website requires a key. To obtain a key, please contact Dr. Nicholas.

Coursework Development Team, Assisting Bioinformatics Efforts at Minority Schools NIH Grant #2T36GM008789

  • Satish Bhalla
    Johnson C. Smith
  • Ricardo Gonzalez-Mendez
    University of Puerto Rico Medical Sciences
  • Hugh B. Nicholas
    NRBSC - PSC
  • Alexander Ropelewski
    NRBSC - PSC
  • Jamie Seguel
    University of Puerto Rico at Mayaguez
  • Alade Tokuta
    North Carolina Central
  • Bienvenido Velez begin_of_the_skype_highlighting end_of_the_skype_highlighting
    University of Puerto Rico at Mayaguez
  • Troy Wymore
    NRBSC - PSC


Last modified: Tuesday, 29 March 2011, 05:31 PM