I am still catching up with a lot of work, and found out I actually had forgotten to blog about this cool article by Denise Slenter: “Discovering life’s directed metabolic (sub)paths to interpret human biochemical markers using the DSMN tool” (doi:10.1039/D3DD00069A). This paper explains how various open science resources (Wikidata, Reactome, WikiPathways) are used to visualize the biological story of the data from two metabolomics experiments

When coffee is sold as single origin or as the more expensive Arabica beans— do you really know whether you are getting what you’re paying for? Different coffee-producing regions need to enforce the standards and reputation of their coffee, and there is a growing industry looking at different technologies to more accurately classify and test coffee beans from different origins.

**A genome scale model of Pseudomonas aeruginosa published recently in GigaScience will help scientists to fight multi-drug-resistant superbugs. Pseudomonas aeruginosa is one of the world’s most dangerous pathogens, causing life-threatening infections. It is increasingly resistant to all antibiotics.

As mentioned in our Happy New Year blog post, one of the highlights in 2017 was a second GigaScience hackathon workshop which we held in November last year in our Hong Kong BGI office.

Sophisticated computational analyses must be performed on metabolomics data in order to measure the abundances of the metabolites. However, this typically requires expert knowledge in computer programming and biostatistics, restricting the usefulness of metabolomics to specialised laboratories.