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{bio,medical} informatics


Tuesday, March 20, 2001

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find related articles. powered by google. BreastLink Both Genes and Environment Play Role in Causing Cancer
"The study’s analysis suggests that having a gene associated with a particular cancer does not mean that the individual carrying that gene will inevitably develop cancer. Even a person whose identical twin develops cancer has less than a 15 percent chance of having the same kind of cancer. This study thus introduces a much needed shot of reality into the media portrayal of fatalism and inevitability surrounding the issue of genetic heritage.

The study also points to a need for accelerated research into the extent to which genes interact with the environment to affect an individual’s susceptibility to disease. Most importantly, this and similar studies make it abundantly clear that the nature-versus-nurture argument is based on a false and arbitrary separation."
redux [07.13.00]
find related articles. powered by google. The New York Times Genes May Cause 25% of 3 Major Cancers
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"Genes may cause more than one-quarter of three major types of cancer, more than previously thought, a group of researchers says.

Scandinavian researchers concluded that genes account for 42 percent of the risk for prostate cancer, 35 percent for colorectal cancer and 27 percent for breast cancer.

The rest of the cases are caused by what people do, such as smoking and diet, or what happens to them, such as on-the-job hazards or viral infections, the researchers said."

"...the conclusion runs contrary to the widespread belief that scientists "will find solutions or cures to all diseases in the genes," Dr. Lichtenstein said. "That won't be the case."

redux [04.25.00]
find related articles. powered by google. UniSci Selfish Gene Theory Of Evolution Called Fatally Flawed
"In the current issue of Advances in Complex Systems (February-April), Dr. Yaneer Bar-Yam, president of the New England Complex Systems Institute and an expert on the application of mathematical analysis to complex systems, contends that the selfish-gene theory of evolution is fatally flawed.

If his mathematical proof gains general acceptance, it will shut the door on controversial "gene-centered" views of evolution.

Bar-Yam, in the upcoming article, proves that the "selfish gene" approach is not valid in the general case. He demonstrates that the gene-centered view, expressed in mathematical form, is only an approximation of the dynamics actually at work."

"The key to Bar-Yam's analysis lies in recognizing three levels of structure in nature: the gene, the organism and the group (or network) of organisms."

redux [05.26.00]
find related articles. powered by google. British Medical Journal Genetic epidemiology
"Research in disease aetiology has shifted towards investigating genetic causes, powered by the human genome project. Successful identification of genes for monogenic disease has led to interest in investigating the genetic component of diseases that are often termed complex, that is, they are known to aggregate in families but do not segregate in a mendelian fashion. Genetic epidemiology has permitted identification of genes affecting people's susceptibility to disease, although progress has been much slower than many people expected. While the role of genetic factors in diseases such as hypertension, asthma, and depression is being intensively studied, family studies and the large geographical and temporal variation in the occurrence of many diseases indicate a major role of the environment. Thus, it is necessary to consider findings about susceptibility genes in the context of a population and evaluate the role of genetic factors in relation to other aetiological factors. This article discusses some approaches used to resolve the genetic architecture of disease and to study the relation of genes to environmental factors in the population. "


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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.

BIOINFORMATICS IN THE 21st CENTURY

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