Git is a source code management system designed around the idea that branching and merging should actually work. The result is that you’re likely to have many more open branches than you otherwise would using a system such as Subversion. But how can you or the rest of your team quickly get up to speed on all of your branching activity? That’s where GitHub’s network graph feature comes in handy.

Yesterday’s post on cheminformatics benchmarking generated a number of interesting comments, both here and on a similar article posted to Egon Willighagen’s blog. One thing the discussion highlights is the need for a suite of benchmarks specifically aimed at comparing the performance of diverse cheminformatics toolkits under controlled conditions.

O’Boyle and Hutchison offer some interesting comparisons between Open Source cheminformatics toolkits in a recent Chemistry Central article. One of them is contained in the table above, in which the Java cheminformatics library CDK outperforms both the natively-compiled libraries Open Babel and RDKit.

The latest release of MX, the Java toolkit for cheminformatics, now supports reading a subset of SMILES strings. Although incomplete, full support for this feature is planned within a few releases. To get an idea of how to use the new SMILES reader, we can use interactive JRuby.

Yesterday the Royal Society of Chemistry (RSC) and ChemZoo (of ChemSpider fame) announced a plan to collaborate on the creation of an InChI Resolver service. From the announcement: It’s encouraging to see a major scientific publisher lend its support to InChI in further evidence of the broad adoption of the identifier. And an InChI key resolver is something I’ve previously said might be a good idea.

MX is an open source cheminformatics toolkit written in Java. One of the reasons Java was selected as MX’s development platform is the excellent support now available to interface the Java Virtual Machine to a variety of scripting languages. Of the scripting languages used in cheminformatics, Python stands out for its widespread adoption. This article will outline the steps needed to use MX from Python.

Graph theory is an essential component of cheminformatics, if you dig deeply enough. MX is a lightweight cheminformatics toolkit written in Java with a major goal of exposing the most important cheminformatics graph manipulations in a flexible, Java-centric way. Previous releases have focused on implementing subgraph monomorphism functionality for use in substructure search.

Ein Fehler ist aufgetreten. Sieh dir dieses Video auf www.youtube.com an oder aktiviere JavaScript, falls es in deinem Browser deaktiviert sein sollte. A source code version control system is an essential ingredient of software development. But it’s just low-level technology that doesn’t change the way you think about creating software and so can safely be ignored.

Recently, MX was introduced as a lightweight and free cheminformatics toolkit written in Java. There’s nothing like real code examples for getting up to speed with a new library. Creating those examples in an environment that makes experimentation easy is even better. This article introduces the basics of MX using the popular Java scripting environment JRuby.

If you want to build cheminformatics software of any kind, you’ll need a basic toolkit. Ideally, this toolkit contains all of the low-level functionality used over and over in your projects. Tools for building an in-memory molecular representation, exact- and substructure comparison, and reading/writing molfiles all fall into this category. Also ideally, this toolkit should be free.