The complexity of biomolecular interactions and influences is a major obstacle to their comprehension and elucidation. Visualizing knowledge of biomolecular interactions increases comprehension and facilitates the development of new hypotheses.
Behind this innovative tool: relatively "old" technology, with a dash of crowdsourcing!
Here are the building blocks:
HTML: What can we say? The rock-solid key to the web.
Perl, a text-based scripting language which, apart from Java, drove interactivity on the web through most of the 90's until PHP took over (and Python seems to be up and coming next for the Big Data crowd);
MySQL; the open-source database of choice for millions of website, also purportedly showing its age (Hadoop is a strong contender for the future open-source of choice, again, driving by the big data movement);
GraphViz: proudly touted as "Drawing graphs since 1988" (http://www.graphviz.org/About.php), an open source graph (network) visualization project from AT&T Research. Probably lesser known than Tableau (which is not truly open source), it still creates GIFs viewable everywhere—even D3.js has the stumbling block of churning out SVG files, truly beautiful yet not directly visible on every browser.
The secret sauce: CROWDSOURCING! Without a doubt, the most powerful engine to drive this comes from the active community building this project.
Read the article (it's written for a very specific scientific community, so you might wind up glossing over the deeper details, but the visuals do tell much of the story and should be inspiring for anyone interested in serious visualization applications via the net.