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{bio,medical} informatics

Tuesday, August 29, 2000

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find related articles. powered by google. Genome Biology Genomics: what is realistically achievable?
"Since I am a computer scientist by training, I tend to think of the current situation in which the field of genomics is being driven forward by rapid technological advances as quite analogous to the sequence of events in computing that were triggered by advances in microcomputer and network technologies. I distinctly remember the early period in which it seemed clear to most computer scientists (including myself) that technical advances were very desirable and interesting, but could have little impact on either the fundamental research issues or the overall advance of the field. Most of us completely underestimated the impact of exponential price improvements in key-enabling technologies. Certainly no one that I know of foresaw in any detail the current world of computing (although a few had rare insights into the potential). As we face the world generated by the web, we should remember that as late as the early 1990s common wisdom indicated that 'movies on demand' would be the application that drove increased network bandwidth."

"As microarray data from genomic sequences become increasingly available, the expression data that will be produced will obviously be directly relevant. There will probably be other forms of data, as well, but these adequately illustrate the point: the generation of hypotheses will flow from integrating a number of such sources of data. The existence of a growing number of hypotheses will guide the rate-limiting 'wet' lab efforts."
redux [08.12.00]
find related articles. powered by google. GenomeBiology Whither genomics?
"The flood of data from genome-wide analysis is transforming biology. We need to develop new, interdisciplinary approaches to convert these data into information about the components and structures of individual biological pathways and to use the resulting information to yield knowledge about general principles that explain the functions and evolution of life."

"Genomics increases the chance that biology will experience a split like the one in physics, between those who collect and those who analyze data. This will challenge the majority of biologists who believe that modeling, simulation, and theory have little to contribute to biology. This prejudice rests on insecurity engendered by most biologists' weakness in mathematics (including my own) and previous efforts to model systems using more variables than there were data points. If we keep clinging to this prejudice, we will drown in a sea of data."

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?
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"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."

[ 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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