If you want to map experimental data to (digital) biological pathways, you need to know what measured datum matches which metabolite in the pathways (that also applies to transcriptomics and proteomics data, of course). However, if a pathways does not have a single database from which identifiers are used, or your analysis platform outputs data with CAS registry numbers, then you need something like identifier mapping. In Maastricht we use BridgeDb for that, and I develop the metabolite identifier mapping databases, which provide the mapping data to BridgeDb, which performs the mapping.

However, identifier mapping for metabolites is non-trivial, and I won't got into details in this post.

Elsevier (RELX Group) has seen a lot of publicity this week again. After the patent on peer review earlier this week, today I learned from Max Kemman about the datasearch.elsevier.com website. This is great! Finding data (think FAIR, doi:10.1038/sdata.2016.18) is hard. Elixir Europe aims at fixing this, and working on open standards to have data explain itself, e.g. adoption of schema.org. But an entry point that finds information is still very much welcome.
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This blog deals with chemblaics in the broader sense. Chemblaics (pronounced chem-bla-ics) is the science that uses computers to solve problems in chemistry, biochemistry and related fields. The big difference between chemblaics and areas such as chem(o)?informatics, chemometrics, computational chemistry, etc, is that chemblaics only uses open source software, open data, and open standards, making experimental results reproducible and validatable. And this is a big difference!
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