Delta Scan: The Future of Science and Technology, 2005-2055: Growing Synergy Between Biology and Mathematics

Key Pages

Category:
Science and Technology

Domain:
Mathematics, Biology and Biotechnology

Keywords:
Information and Knowledge - mathematics, bioinformatics, neuroinformatics, health care

Outlook:
Biological research is stimulating work in new realms of mathematics, and new maths is contributing to advances in biology. Growing synergy between the two disciplines promises to accelerate progress in both fields in coming decades.

Summary Analysis:
Most of the deep and truly novel mathematical ideas originated in attempts to solve physical problems and only later were recast into more rigorous axiomatic language – geometry and calculus for example. Physics is said to be the “fundamental science", because each of the other natural sciences (biology, chemistry, geology, etc.) deals with particular types of material systems that obey the laws of physics. In principle therefore, it should be possible to develop biology in mathematical form from first physical principles. In reality it is not that straightforward, as biological systems are nonlinear and extremely complex, making it difficult to use standard mathematical techniques successfully.

The increase of computational resources in the last few decades are enabling the first steps in quantifying biology to be made though. New mathematical techniques and tools can be applied to challenging aspects of biological research - the complexity of interactions studied, the size of relevant databases, and the time scales of basic biological processes, whether short like photosynthesis or long like evolution, for example. Conversely, challenging aspects of biological research are stimulating innovation in mathematics and it is feasible that biological challenges will stimulate truly novel mathematical ideas as much as physical challenges have. Growing synergy between the two disciplines promises to accelerate progress in both fields in coming decades.

Areas of biological research that are stimulating maths innovation include the following:

Understanding and modeling of cells and their interactions with the environment (bioinformatics)
Understanding of the brain, behaviour, and emotion (neuroinformatics)
Complex ecological modeling, monitoring of epidemic and ecological pathologies
Life: What is it? Where is the line between organisms and inanimate objects? How does life originate? What are the conditions for onset of life?
DNA / genome - function, structure, and topology
Consciousness. What is it? Can we use mathematical models to better understand intelligence?
Sleep? Why do animals sleep? Why do they dream?
Bioelectromagnetism: What are the mechanisms of biorhythms and chronobiology? Why do cells generate electrical fields? How do animals possess long-range navigation and migration abilities?
Immune system

Mathematical innovations that are contributing to progress in biology include the following:

Numerical methods
Modeling of multilevel complex systems
Probability and statistics
Better understanding of data mining (knowledge discovery, pattern recognition) in large bodies of data
Image analysis to aid in molecular modeling and manipulation
Artificial intelligence to automate analysis and identification of patterns in biological data
Nonlinear dynamical systems - bifurcation theory, stability
Partial differential equations
Perturbation and asymtotic methods
Combinatorics
Fluid Dynamics
Quantum Chemistry

Implications:

Acceleration of advances in both mathematics and biology
Improvement of environmental and financial modeling as mathematical and computational techniques developed for biological exploration are applied

Early Indicators:

Current use of alternative analysis tools such as visual pattern recognition and retrieval with databases generated to organize and access the large data sets involved in biological problems
Current use of networking to facilitate cross-group collaboration as well as complex database storage and analysis
Work on developing parallel computing for complex problem analysis and simulation
Use of mathematical tools to complete the mapping of the human genome in April 2003

What to Watch:

Collaboration between mathematicians and biologists leads to semantic understanding of genome functionality by 2010.
Effective mathematical models of cells and possibly organisms are created by 2050.

Parallels/Precedents:

Coevolution of physics and mathematics

Enablers/drivers:

Increasingly cross-disciplinary education of mathematicians and biologists
Advances in grid computing
Further development of modeling languages and tools

Leaders:
Institutions:

US National Human Genome Research Institute (use of mathematical tools in genetics research)[link]
DARPA (Defense Advanced Research Projects Agency) [link]
The Isaac Newton Institute for Mathematical Sciences, Cambridge, UK [link]
American Association for Artificial Intelligence (use of artificial intelligence in research projects) [link]
European Bioinformatics Institute [link]
BioSapiens Network: European Virtual Institute for Genome Annotation [link]
European Society for Mathematical and Theoretical Biology [link]
The International Neuroinformatics Coordinating Facility [link]
Neural Computing Research Programmes In Europe [link]
Asia Pacific Neural Network Assembly [link]
NERC and EPSRC Environmental Mathematics and Statistics Programme, UK [link]
e-Science Data Mining Special Interest Group, UK [link]
Environmental Systems Science Centre, University of Reading [link]
Centre for Mathematical Biology, Mathematical Institute, University of Oxford
Molecular Network Dynamics Research Group, Budapest University of Technology and Economics [link]
Max-Planck Institute of Molecular Cell Biology and Genetics, Germany [link]
Max Planck Institute for Evolutionary Anthropology, Germany [link]
Dept. of Applied Mathematics, The Weizmann Institute of Science, Israel

Figures:

Sources:

Cohen, JE. 2004. "Mathematics Is Biology's Next Microscope, Only Better...," PLoS Biol 2(12): e439 [link]
Costa, Luciano da Fontoura. 2004. "Bioinformatics: perspectives for the future." Genetics and Molecular Research 3 (4) : 564-574. [link]
"Math &amp;amp;amp; Bio 2010: Linking Undergraduate Disciplines." . [link]
Simon Levin, ed., "Mathematics and Biology: The Interface." [link]
Tiezzi, E. "Ecodynamics; the quest for evolutionary physics". Lecture deliverd to ECOSUD 2005, Fifth International Conference on Ecosystems and Sustainable Development [link]
"A Merging of Minds." November 1. 2003. New Scientist [link]

At A Glance:
When:
3–10 years

Where:
Global

How Fast:
Years

Likelihood:
Medium-High

Impact:
Medium-Low

Controversy:
Low

Related Outlooks:

About this outlook: An outlook is an internally consistent, plausible view of the future based on the best expertise available. It is not a prediction of the future. The AT-A-GLANCE ratings suggest the scope, scale, and uncertainty associated with this outlook. Each outlook is also a working document, with contributors adding comments and edits to improve the forecast over time. Please see the revision history for earlier versions.

Category:	Science and Technology
Domain:	Mathematics, Biology and Biotechnology
Keywords:	Information and Knowledge - mathematics, bioinformatics, neuroinformatics, health care
Outlook:	Biological research is stimulating work in new realms of mathematics, and new maths is contributing to advances in biology. Growing synergy between the two disciplines promises to accelerate progress in both fields in coming decades.
Summary Analysis:	Most of the deep and truly novel mathematical ideas originated in attempts to solve physical problems and only later were recast into more rigorous axiomatic language – geometry and calculus for example. Physics is said to be the “fundamental science", because each of the other natural sciences (biology, chemistry, geology, etc.) deals with particular types of material systems that obey the laws of physics. In principle therefore, it should be possible to develop biology in mathematical form from first physical principles. In reality it is not that straightforward, as biological systems are nonlinear and extremely complex, making it difficult to use standard mathematical techniques successfully. The increase of computational resources in the last few decades are enabling the first steps in quantifying biology to be made though. New mathematical techniques and tools can be applied to challenging aspects of biological research - the complexity of interactions studied, the size of relevant databases, and the time scales of basic biological processes, whether short like photosynthesis or long like evolution, for example. Conversely, challenging aspects of biological research are stimulating innovation in mathematics and it is feasible that biological challenges will stimulate truly novel mathematical ideas as much as physical challenges have. Growing synergy between the two disciplines promises to accelerate progress in both fields in coming decades. Areas of biological research that are stimulating maths innovation include the following: Understanding and modeling of cells and their interactions with the environment (bioinformatics) Understanding of the brain, behaviour, and emotion (neuroinformatics) Complex ecological modeling, monitoring of epidemic and ecological pathologies Life: What is it? Where is the line between organisms and inanimate objects? How does life originate? What are the conditions for onset of life? DNA / genome - function, structure, and topology Consciousness. What is it? Can we use mathematical models to better understand intelligence? Sleep? Why do animals sleep? Why do they dream? Bioelectromagnetism: What are the mechanisms of biorhythms and chronobiology? Why do cells generate electrical fields? How do animals possess long-range navigation and migration abilities? Immune system Mathematical innovations that are contributing to progress in biology include the following: Numerical methods Modeling of multilevel complex systems Probability and statistics Better understanding of data mining (knowledge discovery, pattern recognition) in large bodies of data Image analysis to aid in molecular modeling and manipulation Artificial intelligence to automate analysis and identification of patterns in biological data Nonlinear dynamical systems - bifurcation theory, stability Partial differential equations Perturbation and asymtotic methods Combinatorics Fluid Dynamics Quantum Chemistry

	Implications:	Acceleration of advances in both mathematics and biology Improvement of environmental and financial modeling as mathematical and computational techniques developed for biological exploration are applied
	Early Indicators:	Current use of alternative analysis tools such as visual pattern recognition and retrieval with databases generated to organize and access the large data sets involved in biological problems Current use of networking to facilitate cross-group collaboration as well as complex database storage and analysis Work on developing parallel computing for complex problem analysis and simulation Use of mathematical tools to complete the mapping of the human genome in April 2003
	What to Watch:	Collaboration between mathematicians and biologists leads to semantic understanding of genome functionality by 2010. Effective mathematical models of cells and possibly organisms are created by 2050.
	Parallels/Precedents:	Coevolution of physics and mathematics
	Enablers/drivers:	Increasingly cross-disciplinary education of mathematicians and biologists Advances in grid computing Further development of modeling languages and tools
	Leaders:	Institutions: US National Human Genome Research Institute (use of mathematical tools in genetics research)[link] DARPA (Defense Advanced Research Projects Agency) [link] The Isaac Newton Institute for Mathematical Sciences, Cambridge, UK [link] American Association for Artificial Intelligence (use of artificial intelligence in research projects) [link] European Bioinformatics Institute [link] BioSapiens Network: European Virtual Institute for Genome Annotation [link] European Society for Mathematical and Theoretical Biology [link] The International Neuroinformatics Coordinating Facility [link] Neural Computing Research Programmes In Europe [link] Asia Pacific Neural Network Assembly [link] NERC and EPSRC Environmental Mathematics and Statistics Programme, UK [link] e-Science Data Mining Special Interest Group, UK [link] Environmental Systems Science Centre, University of Reading [link] Centre for Mathematical Biology, Mathematical Institute, University of Oxford Molecular Network Dynamics Research Group, Budapest University of Technology and Economics [link] Max-Planck Institute of Molecular Cell Biology and Genetics, Germany [link] Max Planck Institute for Evolutionary Anthropology, Germany [link] Dept. of Applied Mathematics, The Weizmann Institute of Science, Israel
	Figures:
	Sources:	Cohen, JE. 2004. "Mathematics Is Biology's Next Microscope, Only Better...," PLoS Biol 2(12): e439 [link] Costa, Luciano da Fontoura. 2004. "Bioinformatics: perspectives for the future." Genetics and Molecular Research 3 (4) : 564-574. [link] "Math &amp;amp;amp; Bio 2010: Linking Undergraduate Disciplines." . [link] Simon Levin, ed., "Mathematics and Biology: The Interface." [link] Tiezzi, E. "Ecodynamics; the quest for evolutionary physics". Lecture deliverd to ECOSUD 2005, Fifth International Conference on Ecosystems and Sustainable Development [link] "A Merging of Minds." November 1. 2003. New Scientist [link]

At A Glance:	When:	3–10 years
	Where:	Global
	How Fast:	Years
	Likelihood:	Medium-High
	Impact:	Medium-Low
	Controversy:	Low