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COMPUTATIONAL BIOLOGY |
Course Description
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The ability to manipulate organisms genetically has been revolutionized in the last ten years. Biological information produced by this revolution is represented in many forms: sequence data, structural data, and functional data. These data can often be accessed and interpreted only with the help of computers. Data Mining is now an established tool for predicting structure and understanding function in genomics and proteomics. It is becoming impossible for molecular biologists and biochemists to do research without the aid of computer based tools. The advent of computational biology also offers new opportunities for those in chemistry, physics, mathematics and computer science.
This course is intended for students in molecular biology, cell biology, microbiology, physiology, biochemistry, chemistry, physics, mathematics or computer science. It is an introduction to the concepts, and the principal data bases and algorithms, of bioinformatics and structural biology/chemistry. Although emphasis is placed on practical applications, an understanding of the mathematical basis of the algorithms, and their strengths and weaknesses - and the important principles of molecular biology and structural chemistry which they model, is important. This course should enable students to access and analyze sequence and structure data, create and edit images of molecules, and present results in web pages, CHIME and Power Point formats.
Prerequisites: Biology 201 or 203; CIS 110 or 217; Math 260 and 221. Exceptions by permission of the instructor.
What is Bioinformatics? What is Computational Biology?
In its broadest sense, computational biology is simply the application
of computational techniques in computer science, mathematics and statistics
to biological problems. In fact some would argue that computational
biology is not a "field" but an "approach". If so, this
approach was pioneered in the 1960's by ecologists who were interested
in building mathematical models of extremely complex ecosystems.
Perhaps the most practical manifestation of the computational approach
in science are the computer algorithms used by the National Weather Service
to model short term fluctuations in the atmosphere (weather!).
Today, "Computational Biology" is frequently used to imply an extension
of strict bioinformatics. However it is probably true that this is
a "popular use of the term not a correct one". 
In
any case, there is great interest and excitement, and great career and
scientific opportunities, in the application of computational methods
to genomics and proteomics. A good source of information is at bioinformatics.org(http://bioinformatics.org/faq/)...........
Biocomputing
in a Nutshell is exactly what it says - a very concise view of
the interface between computing and molecular biology.
Glossaries of Biotechnology
and Genomics.
As with any technical field, biotechnology is replete with a terminology
all its own. These are some glossaries to terms you may not be familiar
with.
"Gold Book" of Chemistry Definitions from IUPAC |
| Reference Sources on Molecular
Biology, Genomics and Bioinformatics
Primer
on Molecular Genetics at Johns Hopkins.
An excellent introduction to the fundamental concepts and processes of
the Central Dogma, restriction enzymes, gene cloning and gene sequencing.
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Biocomputing For Everyone! dated, but has relevant and interesting information National Bioinformatics Institute a national organization for the advancement of bioinformatics education and certification. Concise information about bioinformatics, genomics; a list of educational sites.
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