The Implementation of Molecular Evolution for the Masses

A couple of years ago, there was talk in the bioblogosphere about getting the general public interested in bioinformatics and molecular evolution:

• Amateur bioinformatics?
• Lowering the Ivory Tower with Molecular Evolution
• Molecular Evolution for the Masses

The idea was inspired by the findings of armchair astronomers -- people who have no professional training, but make contributions to astronomy via their stargazing hobbies. With so much data available in publicly accessible databases, there's no reason we can't motivate armchair biologists to start mining for interesting results.

But how do we train these new comp-bio code-monkeys? The field of bioinformatics requires both some computational skills, as well as an understanding of biology. Finding people with both skill sets (and interests) can be tricky. Well, a framework has been laid out in a recent paper in PLoS Biology for teaching the skills (doi:10.1371/journal.pbio.0060296). The authors present a web-based interface through which students implement standard online tools for DNA sequence analysis (Annotathon).

The course described in the paper takes advantage of the vast amount of data deposited in sequence repositories from metagenomic projects (specifically, the Global Ocean Sampling sequences). Starting with these data, the students perform simple molecular evolutionary analysis, including gene prediction, alignment, and phylogenetic construction. Here's how the authors summarize their course:

The goal of the course is to teach students how to computationally annotate biological sequences (DNA and protein sequences). The starting point is a short stretch of DNA sequence (such as a single metagenomic sequencing read) that students are asked to study according to two major lines of inquiry: (1) prediction of gene product putative function and (2) prediction of taxonomic group of origin.

The question remains: how can we translate these courses offered at universities to the general public? Can we inspire armchair computational biologists to analyze data outside of the classroom?

Hingamp P, Brochier C, Talla E, Gautheret D, Thieffry D, et al. (2008) Metagenome Annotation Using a Distributed Grid of Undergraduate Students. PLoS Biol 6(11): e296 doi:10.1371/journal.pbio.0060296