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{bio,medical} informatics

Friday, March 30, 2001

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find related articles. powered by google. EyeforPharma Physiome launches PACE program to promote biological simulations in research
"Physiome Sciences ( ) has implemented The Physiome Academic Centers of Excellence Program (The PACE Program) to enable biomedical researchers to use computer models in the design and interpretation of their research."

"The PACE Program will make its proprietary biological simulation technology available to academic collaborators. In addition, the technology will allow researchers to integrate gene, protein and functional data that are generated in their labs, to simulate and visualize how cells work and the mechanism of disease pathways."
redux [02.16.01]
find related articles. powered by google. MIT Technology Review Upstream: Biology in Silico
"Computers capable of mimicking life have long been the stuff of sci-fi nightmares—think The Terminator or 2001's HAL 9000. But for researchers struggling to make sense of vast amounts of new biological data, and for drug companies anxious to cut costs and speed development, having accurate computer simulations of living systems is still a dream. To make that dream come true, they are turning to "in silico biology," building computer models of the intricate processes that take place inside cells, organs, and even people. The ultimate goal: an entire organism modeled in silicon, allowing researchers to test new therapies much as engineers "fly" new airplane designs on supercomputers."

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 [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 [02.24.00]
find related articles. powered by google. Science Revealing Uncertainties in Computer Models
[summary - can be viewed for free once registered]
"Computer simulations give the impression of precision, but they are founded on a raft of assumptions, simplifications, and outright errors. New tools are needed, scientists say, to quantify the uncertainties inherent in calculations and to evaluate the validity of the models. But making uncertainties evident is a tough challenge, as evidenced by several recent workshops.”

[ 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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