This week’s highlighted discussion is a different take on pathway and network tools. This is about the design of novel metabolic pathways in silico, not just exploring existing pathways to look for where your favorite genes play roles.
Although we have talked about COPASI before, in conjuction with GenoCAD, and we’ve done training on STRING, some of the other tools were new to me and I was pleased to learn of them. If you know of others you can offer the suggestions. Go have a look at the discussion.
The HMDB, or Human Metabolome DataBase, is another nice data collection and tools from the Wishart lab. Although we have mentioned it in the past, because of it’s emphasis more on small molecules it isn’t something we covered in detail. But with this new video that’s available, I thought it was a good time to include it in our database resources for folks who might be seeking out this kind of metabolomics data.
Their overview video that will be our tip of the week notes that currently their resource contains over 40,000 metabolites. They introduce the types of information contained within, including not only chemical names and structures, but also descriptions, taxonomies, concentrations in biological fluids, reactions and pathways and the roles in human disease. The video goes on to describe the ways to interact with the data, via browsing or searching, and more.
There’s a tremendous amount of information on the pages, with appropriate links to many other useful sources as well. Of course you can also search with sequences using BLAST, and the gene pages will offer lots of detail and links to enzyme and metabolite products that may be useful to think about. And in the never-ending search for appropriate biomarkers for medical situations, this is a really useful repository of knowledge.
While preparing for this tip, I also happened to notice a tweet from their group that was useful for folks who are trying to learn about these topics.
It appears to be a popular and effective guide to exploring translational biomarker discovery topics, with another tool that was new to me: ROCCET, ROC Curve Explorer & Tester. The tutorial with links is listed below as well. So have a look if you are interested in evaluating this type of biomarker data.
Wishart, D., Jewison, T., Guo, A., Wilson, M., Knox, C., Liu, Y., Djoumbou, Y., Mandal, R., Aziat, F., Dong, E., Bouatra, S., Sinelnikov, I., Arndt, D., Xia, J., Liu, P., Yallou, F., Bjorndahl, T., Perez-Pineiro, R., Eisner, R., Allen, F., Neveu, V., Greiner, R., & Scalbert, A. (2012). HMDB 3.0–The Human Metabolome Database in 2013 Nucleic Acids Research, 41 (D1) DOI: 10.1093/nar/gks1065
Xia, J., Broadhurst, D., Wilson, M., & Wishart, D. (2012). Translational biomarker discovery in clinical metabolomics: an introductory tutorial Metabolomics, 9 (2), 280-299 DOI: 10.1007/s11306-012-0482-9
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