A medical researcher recently commented on a trend in medical research: papers nowadays almost always need to include support from the genetic level, and the amount of the data to be mined for useful information is overwhelming. These challenges in medical and biological sciences have provided fertile ground for bioinformatics research and new impetus to advance scalable computing.
Scalable computing is essential to bioinformatics because biological systems are intrinsically loaded with entities and information. Data mining, structure prediction, and simulations all require vast amount of computing resources. A job recently submitted to a public server has run for three weeks and the estimated time to completion is about another month. Much remains to be done in this area to boost the throughput of these systems so biologists can rely on bioinformatics in daily research.
In this special issue, several biologists are invited to report how they have used bioinformatics to make new biological discoveries. Their experiences and perspective offer valuable insights on the successes and problems with current bioinformatics and scalable computing techniques. In addition, several innovative models are introduced to model and simulate biological systems, and the authors share experience on how to develop bioinformatics solutions with scalability in mind.
Just like many biologists refer to PubMed for literature, if the scalability obstacle can be removed, we can foresee that more and more of them will seek answers to biological questions from various bioinformatics services, services implementing much more sophisticated algorithms than sequence alignment. With the high throughput of a scalable server, an accurate answer will be delivered promptly to the desktop of a biologist, instead of a long wait and an ETC of 42.