An Example of a Complex Trait

Alzheimer's disease is characterized by a gradual loss of brain function, usually starting with increasing loss of memory. Four different genes have been identified that can play a role in causing Alzheimer's disease. Rare mutations in each of three different genes (on different chromosomes) can each cause Alzheimer's disease. A common variation in a fourth gene, called ApoE, which occurs in approximately 35 percent of the population, increases the risk of developing Alzheimer's disease about threefold if a person has one copy of the allele (called e4), and about tenfold if they have two copies of the allele.

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Taken together, these four genes account for less than half of all the genetic effects in Alzheimer's disease, indicating that additional genes that have not yet been identified are also important. In addition, environmental risk factors can have an effect. For example, taking certain anti-inflammatory medications, such as ibuprofen, reduces the risk of developing Alzheimer's disease, whereas severe head injury increases it. see also Alzheimer's Disease; Breast Cancer; Cardiovascular Disease; Diabetes; Epistasis; Inheritance Patterns.

Jonathan L. Haines

Bibliography

Haines, Jonathan L., and Margaret A. Pericak-Vance, eds. Approaches to Gene Mapping in Complex Human Diseases. New York: John Wiley & Sons, 1998.

Strachan, Tom, and Andrew P. Read. Human Molecular Genetics, 2nd ed. New York John Wiley & Sons, 1999.

Computational Biologist

A computational biologist is a scientist who develops and utilizes computational tools to analyze biological data. The Human Genome Project and other large sequencing projects have generated an extraordinary amount of data. Biologists are now faced with the challenge of extracting meaning from linear sequences composed of billions of base pairs. The work of computational biologists is indispensable for this task and for many other biological problems that lend themselves to computational solutions.

A basic knowledge of molecular biology and genetics is important, enabling the computational biologist to understand the issues, to interpret the meaning of results, and to communicate with research biologists who work at the laboratory bench. The actual job duties, apart from proficiency in oral and written communication and reading the literature, are very much centered around working with computers. It is, therefore, paramount that a computational biologist be highly skilled in computer technology, with expertise in hardware, software, and the principles of programming. Daily tasks range from accessing public databases and using publicly available and commercial tools for analysis, to developing novel methods for solving problems.

Until recently, there were no formal educational opportunities in computational biology at the graduate level. Therefore, most of the current practitioners and authorities in the field have a combination of degrees at the graduate (master's or doctorate) and undergraduate (baccalaureate) levels in computer science and biology. Still others hold degrees in one of the two fields and are self-taught in the discipline for which they lack formal training. Most often such individuals will have an advanced degree in computer science and will be self-taught in biology, although the converse can also be true. Nonetheless, the ability to program in a high-level language such as C+ + or PERL is a major qualification.

With the release of the working draft of the human genome in 2001, computational biology has come of age. Highly qualified individuals are in demand at academic, private, and government research institutes alike. Academic institutions have taken notice and have begun implementing certificate and base pairs two nucleotides (either DNA or RNA) linked by weak bonds

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