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{bio,medical} informatics

Friday, October 27, 2000

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find related articles. powered by google. BioMedNet Expression: gene by gene
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"C. elegans has yielded large amounts of data for developmental biologists. And the worm continues to be an extraordinary research model. Most recently, researchers have succeeded in tracking the expression of 98% of the nematode's genes as it develops, matures, and eventually ages. The study provides an estimate of the number of genes expressed and the relationships between them. It could also lead to the characterization of unfamiliar genes.

Reference: Hill, A.A., Hunter, C.P., Tsung, B.T. et al. 2000. Genomic analysis of gene expression in C. elegans. Science 290(5492):809-812."
find related articles. powered by google. MSNBC A genetic view of growth and death
"Scientists using a “gene chip” and a beakerful of ground-up roundworms say they have been able to watch genes turn on and off as the worms were born, grew and died. The experiment is the first in which researchers have been able to watch, almost live, the genetic activity in an entire animal, and document how it changes as the animal lives and grows."

find related articles. powered by google. Science Genomic Analysis of Gene Expression in C. elegans
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"Until now, genome-wide transcriptional profiling has been limited to single-cell organisms. The nematode Caenorhabditis elegans is a well-characterized metazoan in which the expression of all genes can be monitored by oligonucleotide arrays. We used such arrays to quantitate the expression of C. elegans genes throughout the development of this organism. The results provide an estimate of the number of expressed genes in the nematode, reveal relations between gene function and gene expression that can guide analysis of uncharacterized worm genes, and demonstrate a shift in expression from evolutionarily conserved genes to worm-specific genes over the course of development.”

redux [08.29.00]
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."

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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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