Catalyzing Inquiry at the Interface of Computing and Biology (2005) / Chapter Skim
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1 Introduction
1 Introduction
Pages 9-22
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From page 9... ...
In the information technology context, the significance of these connections and components is much better understood than in the biological context, not least because human beings have been responsible for the design of information technology systems such as operating systems and computer systems. Still, the capabilities of existing computing methodologies to design or characterize large-scale information systems and networks are being stretched, and in the biological domain, a systems-level understanding of biological or computer networks is both highly important and difficult to achieve.
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From page 10... ...
1.2 PERSPECTIVES ON THE BIOCOMP INTERFACE This report addresses computationally inspired ways of understanding biology and biologically inspired ways of understanding computing. Although the committee started its work with the idea that it would discover a single community and intellectual synthesis of biology and computing, closer examination showed that the appropriate metaphor is one of an interface between the two fields rather than a common, shared area of inquiry.
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From page 11... ...
Some of this legacy is manifested in a several-decade development of private-sector databases (mostly those of pharmaceutical companies) and software for data analysis, in public-sector genetic databases, in the use of computer-generated visualization, and in the use of computation to determine the crystal structures of increasingly complex biomolecules.2 Several life sciences research fields have begun to take computational approaches.
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From page 12... ...
Nevertheless, genomics research is simply not possible without information technology. It is not an exaggeration to say that it was the sequencing of complete genomes, more than any other research activity, that brought computational and informatics approaches to the forefront of life sciences research, as well as identifying the need for basic underlying algorithms to tackle biological problems.
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From page 13... ...
Yet it is also possible that a better understanding of information-processing principles in biological systems will lead as well to greater biological insight; so the dividing line between "applying biological principles to information processing" and "understanding biological information processing" is not as clear as it might appear at first glance. Moreover, even if biology ultimately proves unhelpful in providing insight into potential computing solutions, it is still a problem domain par excellence -- one that offers interesting intellectual challenges in which progress will require that the state of computing research be stretched immeasurably.
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From page 14... ...
For example, detailed computational models of cellular dynamics could lead to mechanism-based target identification and drug discovery for certain diseases such as cancer,5 to predictions of drug effects in humans that will speed clinical trials,6 and to a greater understanding of the functional interactions between the key components of cells, organs, and systems, as well as how these interactions change in disease states.7 On another scale of knowledge, it may be possible to trace the genetic variability in the world's human populations to a common ancestral set of genes -- to discover the origins of the earliest humans, while learning, along the way, about the earliest diseases that arose in humans, and about the biological forces that shape the world's populations. Work toward all of these capabilities has already begun, as biologists and computer scientists compile and consider vast amounts of information about the genetic variability of humans and the role of that variability in relation to evolution, physiological functions, and the onset of disease.
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From page 15... ...
The excitement and challenge of all of these possibilities drive the increasing interest in and enthusiasm for research at the interface. Box 1.1 Illustrative Research Areas at the Interface of Computer Science and Biology · Structure determination of biological molecules and complexes · Simulation of protein folding · Whole genome sequence assembly · Whole genome modeling and annotation · Full genome-genome comparison · Rapid assessment of polymorphic genetic variations · Complete construction of orthologous and paralogous groups of genes · Relating gene sequence to protein structure · Relating protein structure to function · In silico drug design · Mechanistic enzymology · Cell network analysis-simulation of genetic networks and the sensitivity of these pathways to component stoichiometry and kinetics · Dynamic simulation of realistic oligomeric systems · Modeling of cellular processes · Modeling of physiological systems in health and disease · Modeling behavior of schools, swarms, and their emergent behavior · Simulation of membrane structure and dynamic function · Integration of observations across scales of vastly different dimension and organization for model creation purposes · Development of bio-inspired autonomous locomotive devices · Development of biomimetic devices · Bioengineering prosthetics
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From page 16... ...
.12 On April 14, 2003, not quite 50 years to the day after James Watson and Francis Crick first published the structure of the DNA double helix,13 officials announced that the Human Genome Project was finished.14 After 13 years and $2.7 billion, the international effort had yielded a virtually complete listing of the human genetic code: a sequence some 3 billion base pairs long.15 1.4.2 The Computing-to-Biology Interface For most of the electronic computing age, biological computing applications have been secondary compared to those associated with the physical sciences and the military. However, over the last two decades, use by the biological sciences -- in the form of applications related to protein modeling and folding -- went from virtually nonexistent to being the largest user of cycles at the National Science Foundation Centers for High Performance Computing by FY 1998.
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From page 17... ...
In June 1999, the Botstein-Smarr Working Group on Biomedical Computing presented a report to the NIH entitled The Biomedical Information Science and Technology Initiative.16 Specifically tasked with investigating the needs of NIH-supported investigators for computing resources, including hardware, software, networking, algorithms, and training, the working group made recommendations for NIH actions to support the needs of NIH-funded investigators for biomedical computing. That report embraces a vision of computing as the hallmark of tomorrow's biomedicine.
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From page 18... ...
Autonomic computing is inspired by biology in the sense that biological systems -- and in particular the autonomic nervous system -- are capable of doing many things that would be desirable in complex computing systems. Autonomic computing is conceived as a way to manage increasingly complex and distributed computing environments as traditional approaches to system management reach their limits.
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From page 19... ...
To researchers in computer science, the committee hopes to demonstrate that biology represents an enormously rich problem domain in which their skills and talents can be of enormous value in ways that go far beyond their value as technical consultants and also that they may in turn be able to derive inspiration for solving computing problems from biological phenomena and insights. To researchers in the biological sciences, the committee hopes to show that computing and information technology have enormous value in changing the traditional intellectual paradigms of biology and allowing interesting new questions to be posed and answered.
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From page 20... ...
Medical devices such as implanted defibrillators rely on real-time analysis of biological data to decide when to deliver a potentially lifesaving shock. Medical informatics can be regarded as computer science applied directly to problems of medicine and health care, focusing on the management of medical information, data, and knowledge for medical problem solving and decision making.
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From page 21... ...
The chapter, "The Secrets of Life: A Mathematician's Introduction to Molecular Biology," is essentially a short primer on the fundamentals of molecular biology for nonbiologists. Appendix B lists some of the research challenges in computational biology discussed in other reports.
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