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{bio,medical} informatics

Friday, September 05, 2003

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find related articles. powered by google. Genomeweb Look Who's Blazing the Systems Biology Trail

"With sights set on provoking the next wave of bio developments, schools including Cornell, Duke, MIT, Princeton, Stanford, the University of California, and the University of Michigan have undertaken bold initiatives to foster cross-fertilization among faculty and students of diverse disciplines. With state-of-the-art labs and mod monikers such as Bio-X and QB3, the programs will push scientists to seek interdepartmental solutions to biological questions raised by, among other things, genome data. And their directors - scientists who've had illustrious careers in biology, computational genomics, engineering, genetics, and medicine - are systems biology's new vanguard."

"As David Botstein, director of Princeton's fledgling Lewis-Sigler Institute for Integrative Genomics, notes, "We're in very early days. What we have here is high concept." But if concepts become reality, the training, research, and technologies that flow from these centers will instruct the future of the field that's becoming commonly known as systems biology."

redux [08.21.03]
find related articles. powered by google. Computerworld Singapore Beyond bioinformatics

"Some time last year, the "gene bubble" burst when the investment community became disenchanted with the deliverables of genomics, which were not quite as spectacular as promised. Now, a local researcher has predicted that the current hot topic of bioinformatics will not exist within the next ten years. Instead, its position will eventually be usurped by disciplines such as system biology and transcriptome research, which will be the focus for pharmaceutical research in the near future."

"System biology is an emergent field that aims at system-level understanding of biological systems. While system-level understanding has been a long-standing goal of biological sciences, it was only recently that system-level analysis, grounded on discoveries at molecular-level, could be made."

redux [06.24.03]
find related articles. powered by google. Bio-IT World BIO2003: Systems biology leading to advances in IT, medicine

"The study of systems biology, the field of research that creates predictive models of complex biological processes, will lead to advances in pharmaceuticals and medical treatment, but also to advances in computer science, a leading systems biologist predicted Monday.

""I think biology is going to give fundamental new insights to IT," Hood said. "Really understanding the evolution of gene regulatory networks is going to provide completely new strategies for how one deals with this horrendous computational problem of taking big programs ... and restructuring them really efficiently so that you don't restructure them simply by adding more onto them.""

redux [04.21.03]
find related articles. powered by google. Bio-IT World In Silico Models with Many More Variables

"One of the critical priorities now is to take all the components we can detect, and reconstruct the interaction networks inside cells that underlie biological processes. This type of reconstruction is very tricky: People call it 'integration of heterogeneous databases.' Collating these data files is like stacking playing cards -- each piece of data stands upon, and influences, the reliability of other pieces.

The next priority is then to generate computer models that can be used for simulations -- in silico biology. There are three categories of models we need to build: models for metabolism, DNA regulation, and cell signaling."

redux [02.2.03]
find related articles. powered by google. The Scientist Systems Biology: A Pale Beacon For Biotechs
[requires 'free' registration]

"Systems biology, a siren in a sea of dark prospects, has lured investors frustrated with low returns in biotechnology and anxious to set a new course of drug discovery. Institutions have also geared up training programs, but the excitement in the new field has failed to arrest downsizing in the biotech industry."

"Despite the interest of the pharmaceutical industry, prospective systems biologists should think carefully before investing in training in hopes of landing a job in the new field."

redux [03.08.02]
find related articles. powered by google. Science Systems Biology: A Brief Overview
[ summary can be viewed for free once registered ]

"To understand biology at the system level, we must examine the structure and dynamics of cellular and organismal function, rather than the characteristics of isolated parts of a cell or organism. Properties of systems, such as robustness, emerge as central issues, and understanding these properties may have an impact on the future of medicine. However, many breakthroughs in experimental devices, advanced software, and analytical methods are required before the achievements of systems biology can live up to their much-touted potential."

redux [02.26.02]
find related articles. powered by google. MIT Technology Review Systems Biology

"Over the last few years, there's been an explosion of information in biology. The mapping of the human genome gave biologists unprecedented detail about some 30,000 to 40,000 genes. Efforts are also under way to identify the thousands--and potentially millions--of proteins encoded by those genes. Researchers are now pursuing the next logical step in integrating all this data: systems biology.

The goal is to understand not just the functions of individual genes, proteins and smaller molecules like hormones, but to learn how all of these molecules interact within, say, a cell. Biologists hope to then use this information to generate more accurate computer models that will help unravel the complexities of human physiology and the underlying mechanisms of disease. The biggest payoff: faster development of more-effective drugs."

redux [04.05.00]
find related articles. powered by google. HMS Beagle Are Computers Evolving in Biology?
[requires 'free' registration]

"I suspect that although the new enthusiasm for computers in biology is genuine, it overlooks some basic problems in implementation. The basic difficulty, as I see it, is that although biologists use computers, they do not trust everything that comes out of them. It is one thing to use them to print up nice-looking graphs, but it is an entirely different matter to use them to think better."

"Francis Crick was once quoted as saying that no biologist had ever made a discovery using a mathematical model. I would reply that no biologist has ever made a discovery by running an electrophoretic gel. They make discoveries by using their brains. Computers, like all scientific tools, are only as good as the person who uses them. If biologists don't understand how computer models are constructed, they won't know their strengths and limitations. Without some foundation of trust, biologists will be unlikely to utilize or accept this powerful method of data analysis."

redux [01.19.02]
find related articles. powered by google. O'Reilly Network An Interview with Dr. Leroy Hood

"The integration of bioinformatics with these systems approaches is an integral, essential feature. One of the things that we stress is that in the future it's going to be increasingly important for people in bioinformatics to be intimately associated with data producers, because no matter how smart you are you can't model biological complexity--it's just too complex. The only way we're going to understand it is through the integration of these global experimental observations, together with powerful computational tools for analysis, and ultimately, for modeling.

A mistake that a lot of people in bioinformatics have tended to make is thinking that you can set up a bioinformatics center and it can work in isolation from the biology, and it can study all these great databases and learn lots and lots about biology. In vitro biology and in silico biology are all popular terms, but it isn't true, and it isn't going to be true in the future."

redux [04.18.01]
find related articles. powered by google. The New York Times Approaching Biology From a Different Angle
[requires 'free' registration]

"Systems biology is a loosely defined term, but the main idea is that biology is an information science, with genes a sort of digital code. Moreover, while much of molecular biology has involved studying a single gene or protein in depth, systems biology looks at the bigger picture, how all the genes and proteins interact. Ultimately the goal is to develop computer models that can predict the behavior of cells or organisms, much as Boeing can simulate how a plane will fly before it is built.

But such a task requires biologists to team up with computer scientists, engineers, physicists and mathematicians. The structure of universities makes that difficult, Dr. Hood said."

redux [07.13.00]
find related articles. powered by google. Nature Segmentation in silico

"A new mathematical biology is emerging. Building on experimental data from developing organisms, it uses the power of computational methods to explore the properties of real gene networks."

"Our understanding of gene networks is at an early stage. We perceive their complexity only after it has been filtered by the limitations of the techniques used to study them. Genome databases and DNA-chip technology, which enables huge numbers of genes to be screened for activity, will undoubtedly provide more, and much more complicated, data than anything produced by Drosophila genetics. If a relatively simple gene network such as the segment-polarity system is hard to understand intuitively, we can be certain that modelling will be essential to make sense of the flood of new data.

But this will not be elegant theoretical modelling: rather, it will be rooted in the arbitrary complexity of evolved organisms. The task will require a breed of biologist-mathematician as familiar with handling differential equations as with the limitations of messy experimental data. There will be plenty of vacancies, and, on present showing, not many qualified applicants."

redux [05.15.01]
find related articles. powered by google. Systems Biology Workbench Development Group Mission

"Our Mission is to develop an integrated, easy-to-use environment, the workbench , which will enable biologists to create, manipulate, display and analyze biological models at molecular, cellular and multicellular levels. We are focusing on biochemical networks including mass action kinetics, metabolic pathways, stochastic simulation, gene expression and regulation."

"One of the key aspects of out project is to facilitate collaboration among existing developers and users of system biology software. We aim to do this by providing an open-source software infrastructure which will enable collaborators to freely use and share each other's computational resources."

redux [07.11.00]
find related articles. powered by google. Biospace.Com Big Picture Biology

"For most of us, formal biology education begins with complex systems--the traditional dissection of a frog in high school biology class is virtually a rite of passage in the U.S.

But the way many people learn about and invest in biotechnology is at the smallest end of the spectrum--the genome, now often described as the "periodic table" of biology. Genomics and all its related buzzwords have been responsible for much of the media attention, government grants, and investment capital heaped on the biotech industry over the past decade.

But just as there is a whole lot of chemistry that happens in between the periodic table and a birthday cake, there is a lot of biology in between the genome and a living organism. With the completion of biology's periodic table within sight, academics and industry players alike are pondering the best way to apply our hard won knowledge.

The only problem is, the path from genome to system seems to get harder the more we learn."

[ rhetoric ]

Bioinformatics will be at the core of biology in the 21st century. In fields ranging from structural biology to genomics to biomedical imaging, ready access to data and analytical tools are fundamentally changing the way investigators in the life sciences conduct research and approach problems. Complex, computationally intensive biological problems are now being addressed and promise to significantly advance our understanding of biology and medicine. No biological discipline will be unaffected by these technological breakthroughs.


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