Category:	Science and Technology
Domain:	Mathematics, Biology and Biotechnology
Keywords:	Biotechnology and genetics - mathematical modeling, disease, genomics research, computational biology, genome mapping, data generation
Outlook:	Mathematical modeling and analysis of large data sets has the potential to enable application of knowledge obtained from explorations of the human genome to the prevention, diagnosis, and treatment of disease.
Summary Analysis:	Computational methods have become intrinsic to modern biological research. Their importance is likely to increase as large-scale methods for data generation become more prominent, as the amount and complexity of the data increase, and as the questions being addressed become more sophisticated. In the future, it is likely that biomedical research will integrate computational and experimental components to an even greater extent, using computational capabilities to generate new hypotheses and develop experimental approaches to test them. The resulting experimental data could, in turn, help to generate more refined models that will improve overall understanding and increase opportunities for applications to disease prevention, diagnosis, and treatment. In particular, tools for mathematical analysis and modeling are likely to be valuable in developing practical applications of knowledge obtained from explorations of the human genome. These tools will help researchers move from the mapping of the genome to basic biological understanding. The mathematics currently used in analysing the human genome include the following: • Numerical analysis - to manipulate and make sense of the huge amounts of data generated by DNA • Statistics - to generate 'draft sequence data' of fragments whose chromosomal locations are known and to optimise the information extracted from these experiments • Computational models and numerically solvable equations that model the data - to predict molecular behavior • Topology - to study the exact structure of the DNA in order to determine information about its biological function and to analyse the more complicated structures of proteins • Computer graphics - to provide visual aids, both static and mobile, with which to study the DNA structures • Microarrays - to measure how much messenger RNA of a given type is produced in a sample of tissue, giving accurate estimates of the amount of corresponding protein being produced Applying genomic understanding to better health care will involve the following tasks: • Identifying genes and pathways with a role in health and disease, and determining how they interact with environmental factors • Developing, evaluating, and applying genome-based diagnostic methods for assessing susceptibility to diseases, predicting drug response, detecting illness early, and making an accurate molecular classification of diseases • Developing and deploying methods that catalyse the translation of genomic information into therapeutic advances As one example of the application of mathematical modeling in the realm of health care, researchers have recently come to a new understanding of density functional theory (DFT), a relatively new form of applied mathematics that can be used to simulate molecules. Researchers successfully demonstrated the applicability of DFT to the study of biochemical systems, the backbone of drug research, finding that in this instance DFT was as accurate as other approaches and considerably less expensive.

	Implications:	More rapid development and decreased cost of therapeutic drugs More effective prevention and treatment of disease Increased demand for personalized treatments as doctors are better able to assess which treatments are genetically more likely to be effective for a patient Potential for those who are deemed 'healthy' or 'not healthy' based on probabilities in their genes to experience psychological and social impacts Increased demand for research on and cures for genetic diseases
	Early Indicators:	Completion in 1999 of a National Institute of Standards and Technology (NIST) project carried out with Molecular Simulations, Inc., that combined applied mathematics and computer programming to develop new methods for simulating molecular structures and reactions in order to facilitate designing new molecules and therapeutic drugs Awarding of $98 million in the last ten years by the Advanced Technology Program of NIST to 34 R&D projects of the type 'Tools for DNA Diagnostics'
	What to Watch:	A comprehensive catalogue of all of the components encoded in the human genome is developed. Determination is made of how the genome-encoded components function in an integrated manner to perform cellular and organismal functions. An understanding of how genomes change and take on new functional roles is arrived at.
	Parallels/Precedents:	Application of mathematical modeling in the creation of new materials and in engineering and architecture
	Enablers/Drivers:	Development of new approaches to solving problems such as how to identify different features in a DNA sequence and how to analyse gene expression and regulation Development of reusable software modules to facilitate interoperability Development of methods to elucidate the effects of environmental (nongenetic) factors and of gene-environment interactions on health and disease Development of new ontologies to describe different data types Improvement of database technologies to facilitate the integration and visualization of different data types Improvement of knowledge management systems and standardization of data sets to allow the coalescence of knowledge across disciplines
	Leaders:	Institutions: National Institute of Standards and Technology (funding of mathematical research through its Advanced Technology Program) [link] BioForge (online community providing support for biological innovation) [link] European Bioinformatics Institute (ensuring that the growing body of information from molecular biology and genome research is placed in the public domain) [link] Medical Research Council Human Genetics Unit [link] UK Meteorological Office [link] UK Biobank [link] Cambridge Computational Biology Institute [link]
	Figures:
	Sources:	"A Vision for the Future of Genomics Research." National Human Genome Institute [link] Nizamie, S.H. & Sarkar, P.D. 2005. "Mathematics and biology: the interface," Mental Health Reviews. [link] Hanfei Bao, The Research on the Informatics Attributes of Medical Data, Information and Knowledge, Chinese Journal of Medical Treatment 2, 4-8, 2003 [link] Werner Dubitzky and Francisco Azuaje, eds, Artificial Intelligence Methods and Tools for Systems Biology, Springer 2004, ISBN 1402029594 [link] Braden Greer and Javed Khan, Diagnostic Classification of Cancer using DNA MIcroarrays and Artificial Intelligence, Ann. N.Y. Acad. Sci. 1020: 49–66 (2004) L A Liotta et al, Chemical Proteomics: Written in Blood, Nature 425, 905, 2003 Emanuel Petricoin et al, Proteomic Pattern Diagnostics: Consumers and Producers in the Era of Correlative Science, BMC Informatics 4, Ann. N.Y. Acad. Sci. 1020: 49–66 (2004). doi: 10.1196/annals.1310.007 University of the West of England, Informatics improve health of European children [link] Foresight Brain Science Addiction and Drugs project, especially genomics paper by David Ball et al [link]

	At A Glance:	When:	11–20 years
		Where:	Global
		How Fast:	Years
		Likelihood:	Medium-Low
		Impact:	Medium-Low
		Controversy:	Low

Related Outlooks:

Posted at Dec 20/2006 10:30AM:
Giorgio Gaviraghi I believe that the best strategy for future health care is to develop computerized body models and disease models all at atomic level. Such models can be utilize to study any alteration that a subject may suffer and in real time , by developing treatment simulations models define a diagnosis as well as a treatment for the single patient. Such system, associated with a nanochip injected in a human body to monitor all vital data ( blood, pressure, sugar levels etc) and transmitting any variation in real time can help not only to prevent but to eliminate diseases which should be the real goal of this century in medicine.