The introduction of high-throughput methods has transformed biology into a data-rich science. Knowledge about biological entities and processes has traditionally been acquired by thousands of scientists through decades of experimentation and analysis. The current abundance of biomedical data is accompanied by the creation and quick dissemination of new information. Much of this information and knowledge, however, is represented only in text form--in the biomedical literature, lab notebooks, Web pages, and other sources.
Using the tools of information technology to understand the molecular machinery of the cell offers both challenges and opportunities to computational scientists. Over the past decade, novel algorithms have been developed both for analyzing biological data and for synthetic biology problems such as protein engineering.
The work performed by living systems ranges from photosynthesis to prodigious feats of computation and organization. This multidisciplinary volume explores work across many different levels of organization. By addressing how work gets done, and why, from the perspectives of research in a range of disciplines, including cellular and evolutionary biology, neuroscience, psychology, electrical and computer engineering, and design, the volume sets out to establish an integrative perspective on understanding work in living systems, including humans.
Recent research in molecular biology has produced a remarkably detailed understanding of how living things operate. Becoming conversant with the intricacies of molecular biology and its extensive technical vocabulary can be a challenge, though, as introductory materials often seem more like a barrier than an invitation to the study of life.
There are many excellent computational biology resources now available for learning about methods that have been developed to address specific biological systems, but comparatively little attention has been paid to training aspiring computational biologists to handle new and unanticipated problems. This text is intended to fill that gap by teaching students how to reason about developing formal mathematical models of biological systems that are amenable to computational analysis.
Molecular biologist Elizabeth Blackburn—one of Time magazine’s 100 “Most Influential People in the World” in 2007—made headlines in 2004 when she was dismissed from the President's Council on Bioethics after objecting to the council's call for a moratorium on stem cell research and protesting the suppression of relevant scientific evidence in its final report.
Ideas about heredity and evolution are undergoing a revolutionary change. New findings in molecular biology challenge the gene-centered version of Darwinian theory according to which adaptation occurs only through natural selection of chance DNA variations. In Evolution in Four Dimensions, Eva Jablonka and Marion Lamb argue that there is more to heredity than genes.
Recent advances in biotechnology, spurred by the Human Genome Project, have resulted in the accumulation of vast amounts of new data. Ontologies—computer-readable, precise formulations of concepts (and the relationship among them) in a given field—are a critical framework for coping with the exponential growth of valuable biological data generated by high-output technologies.
Despite the fact that advanced bioinformatics methodologies have not been used as extensively in immunology as in other subdisciplines within biology, research in immunological bioinformatics has already developed models of components of the immune system that can be combined and that may help develop therapies, vaccines, and diagnostic tools for such diseases as AIDS, malaria, and cancer.
