There is a general interest to quantify biology to help growth of economy and affordable healthcare without causing much damage to the environment. This interest is both at the political level and at the scientific levels. From nutritional security to biofuel and beyond, all have roots in quantification of biology, we need to understand the theory behind all biological events that happen around us, whether within a cell due to a pathogen or in the environment due to the toxic industrial waste.

To manage this range of biological event, we need to understand the cause and effect equation of biological events. This is the reason, biology as a whole is embracing technology at an unprecedented rate. The main challenge in quantifying biology is that most of the biology problems are NP-hard; they need supercomputers to solve almost any problem. Therefore, biosciences research was always been the domain of computational elites who has access to large supercomputers.

Though many algorithms have been perfected in the recent past, the voluminous data from a NGS (Next Generation Sequencer) and increase in metadata have offset the benefits of these smarter algorithms. Newer and efficient algorithms combined with high performance cloud computing opens up the opportunity for smaller labs and under-privileged researchers and clinicians to engage in biology research and join the mainstream. The cloud also opens up the possibility for small clinics to offer personalized medicine who otherwise could not afford a supercomputer.

The new age genomics and the NGS technology in particular pushes the realm of compu-ting like never before. The challenges are immense as there is a need for parallel and efficient algorithms and tools to solve the data tsunami that the NGS machines offload. For example, the latest HiSeq 2000 from Illumina Inc, is expected to generate close to about 600 gigabase to 1 terabase per run. This data deluge coupled with the NP-hard nature of biological problems makes computer scientists to innovate newer and better techniques for transferring, managing, processing, decoding and analyzing the NGS data haze to unearth meaningful insights that can be applied to improve the quality of life.  

In the last few decades Web and network-delivered services have changed people’s lives. This technology has effectively “shrunk the world” and brought it into the pockets of individuals; it also helped the technology in a different way – it moved the center-stage of technology from giant technology companies to the technologists and technology consumers. Today an underprivileged entrepreneur somewhere in the world can innovate and open a shop in the Web and be successful. Likewise, HPC (High Performance Computing) accelerated by the cloud will transform the biotechnology, and life-sciences research, disease prognosis, and disease therapeutics. Unlike other domains.

In the life sciences almost everything is available in the open domain – most of the journals are open-access and free – even nicely catalogued in PubMed; almost all software are open-domain if not open source; even better is that, all experimental data are available for verification, download, and use. There are databases like NCBI (National Center for Biotechnology Information), Hapmap, SMD (Stanford Microarray Database), that archives data from genome to protein, microarray to microRNA. Anything anybody needs is available for free. The only component that was missing in this whole equation is the supercomputer. The cloud bridges this gap – a researcher can now do almost anything on the cloud. The cloud not only addresses the CPU power needs of a NP-hard problem, but also will addresses the storage requirements of hundreds of terabytes of storage a biology experiment might need. Though the communication technology is not ready yet to transfer such large volume of data online, the cloud vendors have perfected transfer of data offline.

High Performance Cloud Computing (HPCC) is poised to become the disruptive technology of the 21st century for lifesciences; cloud computing in particular will become an essential tool in the world for the biotechnology research for farmers, and clinicians alike. From high yield crops to industrial enzymes to high productive livestock and finally in Personalized medicine. HPCC solutions comprising of Infrastructure as a Service (IaaS), Platform as a Service (PaaS), and Software as a Service (SaaS) will play a pivotal role in translating lifescience to affordable applications. Cloud computing will be the highway to reduce the divide between computational elite and computational underprivileged, With cloud computing one can realize flexible, on-demand, and low-cost compute infrastructure whenever you want, wherever you want.

Another trend that will emerge along these lines very soon is the outsourcing model in biotechnology. Today the computational elites have monopolized the biotech research – they have large supercomputers with a large team of bioinformaticians. This will soon change – bioinformatics will graduate to computational quantitative biology with many smart researches offering their solutions in the clous mainly as an SaaS. Cloud computing is of particular benefit to small and medium-sized research centers, farmers, and clinicians who wish to outsource their data-center infrastructure, or large centers who wish to get peak load capacity without incurring the higher cost of ownership hrough larger data centers internally. In both instances, service consumers will use what they need on the Internet and pay only for what they use.

The next generation lifesciences, biotechnology, and healthcare applications will be a con-glomeration of a gamut of tools including but not limited to Systems biology, High Performance cloud computing systems, computer algorithms, mathematics, statistics, biological networks, molecular interaction pathways, Protein-enzyme-simulations, etc. Each of these techniques have a pivotal role to play in deciphering the complex human – environment system and thereby providing enough insights to translate research into appllication or science into discovery, be it personalized medicine, industrial bio-products, agri products or livestock systems. However, the question that we need to answer is how to make this future wellbeing system accessible, omnibus, and affordable for everybody? The answer is in integration of engineering, technology and science. Here there is an unanimous choice for high performance cloud computing – as, it enables and ignites affordable next generation genomics applications to reach the masses in the form of new therepies, drugs, better crops, sustainable enviroment, and proactive and preventive medicine.

About the Author

Asoke Talukder is an author, professor, and a practicing computational geneticist. He worked in tech-nology domains for companies like ICL, Fujitsu-ICIM, Microsoft, Oracle, Informix, Digital, Hewlett Packard, Sequoia, Northern Telecom, NEC, KredietBank, iGate, Cellnext, etc. He Internet enabled Microsoft PowerPoint, engineered the first 64-bit database (Informix), engineered Oracle Parallel Server for Fault Tolerant computer, and developed many killer technologies and products. He setup the first X.25 network in India for Department of Telecommunications (currently BSNL & MTNL), and the first Java Competency Centre in India. He engineered the Network Management System for Queen’s Award winning PDMX. He is recipient of many international awards for innovation and professional excellence including ICIM Professional Excellence Award, ICL Excellence Award, IBM Solutions Excellence Award, Simagine GSMWorld Award, All India Radio/Doordarshan Award etcetera. Asoke has been listed in “Who’s Who in the World”, “Who’s Who in Science and Engineering”, and “Outstanding Scientists of 21st Century”. He authored many research articles, book chapters, and textbooks. Asoke did M.Sc (Physics) with Bio-physics major and Ph.D (Computer Engineering). He was the DaimlerChrysler Chair Professor at IIIT-Bangalore, and currently Adjunct Faculty at Indian Institute of Information Technology & Management, Gwalior, Department of Computer Engineering, NITK Surathkal, and Department of Computer Science & Engineering, NIT Warangal. His current domain of expertise is in Computational Genomics and Statistical Bioinformatics. Along with teaching, he is founder of Geschickten Biosciences, a company in the domain of Computational Quantitative Biology focusing on Omic sciences analytics, GenomicsCloud, and Personalized/Holistic Medicine & Wellbeing.
 
About Geschickten Biosciences

To solve the challenges posed by the current Genomics technology such as Next Generation Sequencing, Geschickten has designed GenomicsCloud a novel cloud based software-as-a-services application for managing, analyzing and visualizing NGS data. A simple yet powerful software engine for NGS data analytics, Genomics Cloud will bring the power of a supercomputer accessible through a mobile device. One area that still remains as the concern in the cloud, is the data security and conformance to the regulatory requirements for transfer of genomics data across geographical boundaries. To mitigate this challenge, Geschickten has added an additional layer in the Cloud computing stack that will address the security requirements. This is termed as the cloud vendor layer. Cloud vendors will primarily be cloud resource aggregators, who will aggregate the services of many Original cloud providers’ and offer the services to the end biologist at an affordable price that will conform to the regulatory and taxation requirement of the end-user and the geography. The cloud vendor will ensure data transfer, data security, data management, and charging. This layer will also ensure some of the concerns of multi-tenancy in the Cloud.

Geschickten Biosciences (www.geschickten.com) is a niche scientific intelligence company from Bangalore, India. The first Computational Quantitative Biology company from India Geschickten offers a wide range of products and scientific services to independent researchers, sequencing centers and industry including but not limited to Biotechs, Pharmaceuticals, Chemical, FMCG, and Biofuel companies etc. As experts in in NGS data analytics and Microarray data analysis, Geschickten is combining engineering, technology and science to translate research into discovery. Geschickten offers innovative technological solutions for Agriculture research, Animal biology, Environmental science and in human genetics.