Bioinformatics點解?

Merriam-Webster Online Dictionary
The collection, classification, storage, and analysis of biochemical and biological information using omputers especially as applied to molecular genetics and genomics

Introduction of a MS Programme in Bioinformatics from Georgia Institute of Technology
Bioinformatics is an integration of mathematical, statistical, and computer methods to analyze biological, biochemical and biophysical data

Wikipedia
Creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems posed by

Bioinformatics

Bioinformatics combines biochemistry and molecular biology with information technology, and is now at the forefront of modern Science. With the completion of the Human Genome Project and the advent of modern high-throughput biology, the need for people qualified in Bioinformatics exceeds supply. Mixing biology and computing may seem strange at first but there are two essential reasons for this. One is that, at its heart, biology is actually a digital science - our DNA is like a digital code. The other reason is that now we study cells or tissues by looking at the entire genome at once. To make biological sense of so much information requires computing. Bioinformatics makes the perfect match of digital biology with digital computing.

Digital Biology

Digital biology is in our genes. Our genes are chains of four different nucleotides, which we represent by the letters A, C, G or T. We can consider our genes to be a string of letters based on a four-state digital code instead of the two states (0 or 1) used by computers. The signals vital to our lives are hidden in this digital code of the genome. Proteins are translated from our genes as a chain of amino acids. This time the 20 amino acids create a 20-state digital code. All the complexity and joy of life is built from this digital foundation. The techniques of the digital world of computing are what is needed to find and fully understand the digital signals of life hidden among the nucleic and amino acids.

Understanding Life through Genomic Science

Working on entire genomes is a good way to understand how our bodies develop and function, or the processes of disease. All the genome sequencing projects have created a mountain of digital data that modern computers will let us mine and interpret. Since we know all (or most) of the genes in a genome, we can do experiments that study all of the genes at once. For example, we can now ask what genes are expressed in different types of cancer and find all of them. This opens new paths to drug design and diagnosis and many other possibilities. However, the amount of data generated is enormous. We must bring computer science and data mining, supported by biological knowledge, together to solve these problems. Modern biology requires a deep understanding of biology and a deep understanding of computing. You can start the journey along this path through the Bachelor of Science in Bioinformatics.

What You Will Learn

You will learn the areas of biochemistry and molecular biology that are important to give you a solid foundation in the subjects. An understanding of the molecular basis of life and the role of the genome will be emphasised. You will also learn how to program a computer, to understand data structures and algorithms, databases and the internet. In short, you will become a computing professional. Of course, bioinformatics itself will be taught through specialised modules. You will learn two fields and the link between them. That is, you will know how to bring out the best of modern biology and computing.

Who is this for?

If you really like both biology and computing, then this degree will give you the best of both worlds and open doors that would remain closed if you only studied one field.
If biology is your main interest but you also like computing, then this degree will let you take your biology to new heights.
If computing is what you want to do and you are intrigued by biology, then this degree opens a very important range of problems and developments to which you can apply your computing knowledge.

係咪機因呀

2007-03-15 13:59:51 補充：
sor,,,係Bioinformatics=生物數學

Bioinformatics and computational biology involve the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry and biochemistry to solve biological problems usually on the molecular level. Research in computational biology often overlaps with systems biology. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.

The terms bioinformatics and computational biology are often used interchangeably. However bioinformatics more properly refers to the creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems posed by or inspired from the management and analysis of biological data. Computational biology, on the other hand, refers to hypothesis-driven investigation of a specific biological problem using computers, carried out with experimental and simulated data, with the primary goal of discovery and the advancement of biological knowledge. A similar distinction is made by National Institutes of Health in their working definitions of Bioinformatics and Computational Biology, where it is further emphasized that there is a tight coupling of developments and knowledge between the more hypothesis-driven research in computational biology and technique-driven research in bioinformatics. Computational biology also includes lesser known but equally important sub disciplines such as computational biochemistry and computational biophysics.

A common thread in projects in bioinformatics and computational biology is the use of mathematical tools to extract useful information from data produced by high-throughput biological techniques such as genome sequencing. A representative problem in bioinformatics is the assembly of high-quality genome sequences from fragmentary "shotgun" DNA sequencing. Other common problems include the study of gene regulation using data from microarrays or mass spectrometry.