Education Working Group

To participate in the discussion send mail to majordomo@sdsc.edu with the body of the message containing subscribe iscb-edu. All educators interested in the charge below are invited to participate. Current members 49.

Charge

To define a generic bioinformatics curriculum  which the society endorses as a staring point in the provision of a complete education in bioinformatics. The first draft of this curriculum will be presented and discussed at ISMB 2001. The curriculum is intended to be an aid to those developing their own programs in bioinformatics by covering all aspects of the field and providing links to the work of others.

The curriculum covers what will likely be taught at both the undergraduate and graduate levels at universities and other teaching institutions worldwide. 

Updates

April 7, 2001 - Finalization of the table below

April 1, 2001 - The question of whether the curriculum should cover the use of bioinformatics tools by an audience not taking bioinformatics as a major was considered. The consensus was that this would defocus our efforts and that we would concentrate on what is required to educate those majoring in bioinformatics. In other words a curriculum suited to those who would become future teachers of bioinformatics. While teaching molecular biologists, computer scientists etc. is very important this can only be done by those well trained in bioinformatics and that will be the focus.

Current Question

Does the following cover all elements of a useful curriculum? 

Theory and Methods Application Areas Data Types
Algorithms
  • Recursion
  • Graph trees
  • Dynamic programming
  • Classification
  • Decision trees
  • Bounded search

Mathematical and statistical analysis

  • Optimization
  • Combinatorial methods
  • Cluster analysis
  • Classification
  • Bayesian inference
  • Decision trees
  • Schocastic context free grammars

Artificial intelligence/machine learning

  • Neural networks
  • Genetic networks
  • Natural language processing

Data representation

  • Ontologies
  • Data models/structures

Knowledge representation

Databases and knowledge bases

Programming languages

Graphics and image analysis

Modeling

Usability engineering

Technology support
  • crystallography
  • micro arrays
  • mass spectrometry
  • NMR

 

  • Pairwise sequence alignments

  • Multiple sequence alignment

  • Pairwise structure alignments

  • Multiple structure alignments

  • Phylogenetic tree construction

  • Fragment and whole genome assembly

  • Genome comparison

  • Biological databases

  • Expression analysis

  • Feature extraction from sequences and structures

  • Structure prediction (RNA, DNA and protein)

  • Docking

  • Knowledge extraction

  • Protein - protein interactions

  • Interaction networks

  • Integrated systems

  • protein and genomic sequences

  • gel electrophoresis

  • structures (coordinates, structure factors, NMR constraints)

  • expression data (micro arrays)

  • spectroscopic (mass spec., circ. dichroism)

  • kinetic 

  • thermodynamic

  • interaction data (binding constants) 

  • images 

 

Prerequisite Reading Altman Bioinformatics 1998 14(7) 549-550