E-learning for marine biotechnology: an example with a metagenomic approach
- Published
- Accepted
- Subject Areas
- Marine Biology, Science and Medical Education, Computational Science, Environmental Contamination and Remediation
- Keywords
- metagenomics, e-learning, marine biotechnology, bioinformatics
- Copyright
- © 2018 Liguori et al.
- Licence
- This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Preprints) and either DOI or URL of the article must be cited.
- Cite this article
- 2018. E-learning for marine biotechnology: an example with a metagenomic approach. PeerJ Preprints 6:e27336v1 https://doi.org/10.7287/peerj.preprints.27336v1
Abstract
Bioinformatics has pervaded all fields of biology and has become an indispensable tool for almost all research projects. Hence the demand for graduates well-trained in bioinformatics has grown. Teaching bioinformatics has been incorporated in all traditional life science curricula. Better than teaching stand-alone bioinformatics, it would be useful to stress multidisciplinary and problem-solving aspects. Since bioinformatics relies heavily on the use of computers, e-learning is particularly convenient, but few examples have been produced so far. We present a tutorial that starts from a practical problem: finding novel enzymes from marine environments. First, we introduce the idea of metagenomics, a recent approach that extends biotechnology with non-culturable microbes. We then lead the students through databases such as BRENDA, and programs such as BLAST and Clustal Omega. Lastly, we let the students querying these databases about molecules found in marine environments. At the end of the experience, students will have acquired practical knowledge of bioinformatics fundamentals.
Author Comment
This is an abstract which has been accepted for the BBCC2018 conference.