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{bio,medical} informatics

Saturday, May 26, 2001

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find related articles. powered by google. Science Can Genes Explain Biological Complexity?
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" When it comes to the complexity of organisms we immediately think of behavioral or morphological complexity or perhaps wish to count the number of cells in an organism or the number of genes in the organism's genome. As Szathmáry et al. explain in their Perspective, biological complexity is not that simple. With the completed sequences of yeast, worm, fly, and human at hand, it is now clear that the number of genes cannot account for the complexity of organisms (the fly genome has about 25,000 genes and we only have about 35,000). The Perspective authors discuss whether we should think about complexity in terms of interactions among gene-regulation networks, using equations similar to those used by ecologists to determine the multitudinous interactions within food webs.”
redux [02.20.01]
find related articles. powered by google. The New York Times Humbled by the Genome's Mysteries
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"Human complexity cannot be generated by 30,000 genes under the old view of life embodied in what geneticists literally called (admittedly with a sense of whimsy) their "central dogma": DNA makes RNA makes protein — in other words, one direction of causal flow from code to message to assembly of substance, with one item of code (a gene) ultimately making one item of substance (a protein), and the congeries of proteins making a body. Those 142,000 messages no doubt exist, as they must to build our bodies' complexity, with our previous error now exposed as the assumption that each message came from a distinct gene."

"The collapse of the doctrine of one gene for one protein, and one direction of causal flow from basic codes to elaborate totality, marks the failure of reductionism for the complex system that we call biology..."
find related articles. powered by google. 1999 Pacific Symposium on Biocomputing Gene Expression and Genetic Networks
"Biology is currently undergoing a shift from a mostly qualitative to an information rich, quantitative science. Using large-scale biological technologies, we are gaining global views of structural and dynamic information in the form of whole genome sequences and the corresponding gene activity patterns at the RNA and protein level. These data reflect the molecular workings of a complex information processing system. In many ways these systems can be effectively viewed from the perspective of genetic feedback networks, given that the fundamental step of biological information flow resides in gene activation and its control through the activity of regulatory genes."

"The following sets of nine papers deals with the modeling of molecular networks, inference of functional relationships from gene activity profiles, and networks approach to structural evolution. We begin with a review by Szallasi in which he explains shy integrative approaches have been ignored in the traditional search for "dominant" molecular genetic mechanisms, and why this is no longer tenable in light of the evidence for combinatorial molecular causes for e.g. complex human diseases."

find related articles. powered by google. On Semiotic Modeling Code-Duality and the Semiotics of Nature
"Through centuries biological theories have been molded to conform to the view of nature established in classical physics. An apparently infinite succession of deep-rooted controversies bear witness to the fact, that this was not at all an easy fit. Vitalism, teleology or finalism have perpetually been called upon to account for living systems. But the authority of physics was such, that in the end those deviations from the ideal was always defeated - to reappear, nevertheless, in new disguise in the next generation.

With the birth of molecular biology and especially molecular genetics in the fifties and sixties a strange thing happened. Suddenly a new and very foreign vocabulary was introduced into biology, that of cybernetics or information theory. Terms like 'program', 'genetic code', 'information', 'messenger-RNA', 'feedback' and the like became respectable or even indispensable notions. Such terms, however, clearly played no role in the world view of classical physics.

This contradiction disappears when it is recognized that these new terms did not mean the same thing in biology as they did in general language. Facilitated by a widespread indifference to epistemological problems among biologists the concept of genetic information became for all practical purposes identified as the sum of the genes which carried it."

"We highly suspect the fruitfulness of this paradigm."
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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