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Jean-Christophe Nebel
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Bioinformatics 3rd Year Module
Year: 2007-2008
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| Module information |
CI3480 Bioinformatics
Dr Jean-Christophe Nebel. Ext 62740. E-mail: J.Nebel@kingston.ac.uk
Availability: Available to CS/SE/IS and Forensic Science students.
Pre-requisites: None.
This new module provides an introduction to bioinformatics; the exciting new field that comes from a marriage between biotechnology and computer technology. No biological background is required, since it is covered in the course. This module prepares you to join the biotechnology revolution either as an analyst or a programmer. After a brief introduction to the digital nature of genetics information, the following techniques are presented within the context of practical applications (e.g. DNA fingerprinting and gene therapy): sequence alignment, evolutionary tree building, data mining and structure prediction. Along the technical subjects, this module also covers some of the social, economical and ethical issues that arise in bioinformatics.
Delivery: One 2 hour lecture and one 2 hour workshop each week.
Assessment: 50% coursework, 50% end-of-module examination.
| Bioinformatics in Action 1: Elephant family |
>gi|924720|gb|U23739.1|MPU23739 Mammuthus primigenius cytochrome b (cytb) gene, Fairbanks allele, mitochondrial gene encoding mitochondrial protein, partial cds
GAAATTTCGGCTCACTACTAGGAGCGTGCCTAATTACCCAAATCCTAACAGGATTATTCCTAGCCATACA TTACACACCTGACACAATAACTGCATTTTCATCTATATCCCATATTTGCCGAGACGTGAACTACGGCTGA ATTATTCGACAACTACACTCAAACGGAGCATCCATCTTCTTCCTCTGCCTATACACACACATTGGACGAA ACATCTACTATGGGTCCT
>gi|924716|gb|U23737.1|MAU23737 Mammut americanum cytochrome b (cytb) gene, mitochondrial gene encoding mitochondrial protein, partial cds
GAAATTTCGGCTCACTACTAGGAGCATGCCTAATTACCCAAATCCTAACAGGATTATTCCTAGCCATACA TTATACACCCGACACAATAACCGCATTCTCATCTATATCCCATATCTGCCGAGATGTCAACAATGGCTGA ATTATTCGACAACTACACTCAAACGGAGCATCCATCTTCTTCCTCTGCCTATATACACACATTGGACGAA ACATCTACTACGGATCCT
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For the whole story, read the followng paper by Yang et al. 1996: Phylogenetic Resolution within the Elephantidae ...
| Bioinformatics in Action 2: Prediction of the clinical outcome of breast cancer patients |
Microarray technology reveals gene expression, or which genes are turned on or off under different conditions. Gene expression depends on the tissue, the developmental stage of the organism and the metabolic or physiologic state of the cell.
Researchers showed the clinical outcome of breast cancer patients can be predicted using the gene expression profile of the primary tumor.
Microarray: A red point indicates over-expression of a gene, while a green point indicates its under-expression.
Using clustering algorithms, it was possible to group the patients' tumors based on the dominant expression features. They discovered that 70 genes correlated tightly with the patients' clinical outcome (presence of metastases in the future), indicating that it could be predicted based on the gene expression profile of the primary tumor. Therefore, treatments can be customised so that every patient is provided with the best course of treatment.
For the whole story, read the followng paper: Rosetta Uses MathWorks Tools to Predict the Clinical Outcome of Breast Cancer Patients
| A success story: Drug design for HIV (from the computer to the clinic) |
In 1981, doctors recognized a strange new disease in the United States. The first handful of patients suffered from unusual cancers and pneumonias. As the disease spread, scientists discovered its cause - a virus that attacks human immune cells (HIV). Now a major killer worldwide, the disease is known by its acronym: AIDS.
Our story begins in 1989, when scientists determined the 3D structure of HIV protease, a viral enzyme critical in HIV's life cycle. Pharmaceutical scientists hoped that by blocking this enzyme, they could prevent the virus from spreading in the body.
3D structure of HIV protease protein
With the structure of HIV protease at their fingertips, researchers were no longer working blindly. They could finally see their target enzyme- in exhilarating, colour-coded detail. By feeding the structural information into a computer modelling program, they could spin a model of the enzyme around, zoom in on specific atoms, analyze its chemical properties, and even strip away or alter parts of it.
Most importantly, they could use the computerized structure as a reference to determine the types of molecules that might block the enzyme. These molecules can be retrieved from chemical libraries or can be designed on a computer screen and then synthesized in a laboratory. Such structure-based drug design strategies have the potential to shave off years and millions of dollars from the traditional trial-and-error drug development process.
These strategies worked in the case of HIV protease inhibitors. "From the identification of HIV protease as a drug target in 1988 to early 1996, it took less than 8 years to have three drugs on the market." Typically, it takes 10 to 15 years and hundreds of millions of dollars to develop a drug from scratch.
Initially, these drugs were hailed as the first real hope in 15 years for people with AIDS. Newspaper headlines predicted that AIDS might even be cured. Although HIV protease inhibitors did not become the miracle cure many had hoped for, the death rate from AIDS went down dramatically after these drugs became available. Now protease inhibitors are often prescribed with other anti-HIV drugs to create a "combination cocktail" that is more effective at squelching the virus than are any of the drugs individually.
For the whole story, read chapter 4 in the following paper: Structure-Based Drug Design: From the Computer to the Clinic
| More information about bioinformatics |
Check these links or send me an email (j.nebel@kingston.ac.uk):
