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{bio,medical} informatics

Friday, July 07, 2000

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UniSci Book Cites Dangers Of Misunderstanding Human Genetics
"A new book by Dr. Jonathan Kaplan of the University of Tennessee provides a timely and provocative analysis of how genetic research can be misused to shape social policy. "

"Kaplan examines the roles genetic explanations for these types of differences play in our culture -- and how science has been used inappropriately to "medicalize" problems that should be more properly addressed as complex social issues."

"As Kaplan states in his chapter on mood-affective disorders: "... an emphasis on the biochemical and the genetic share the property that they make the condition out to be internal to the patient. Once a genetic explanation is offered, and any plausible sounding pathway proposed, the opportunities for claiming that there are other ways of approaching the problem are radically curtailed."

The problem becomes entirely that of personal biochemistry: the danger is in adopting easy solutions without looking at other reasons for the problem -- and without questioning the framework in which certain temperaments or sexual orientations become defined as problems."
ABCNews.Com Suicide Gene?
"If somebody has this predisposition and nothing bad ever happens to them, it may never be expressed,” says study co-author David Bakish, a professor of psychiatry at the University of Ottawa and head of the psychopharmacology clinic at the Royal Ottawa Hospital. “But if they lose their job or whatever, then it may come into play.”

People often come into emergency rooms with suicidal thoughts, he says. “With a test, you could say, ‘You have this mutation, you are at higher risk. Maybe you’d benefit from long-term treatment.’”

[ 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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