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At the Confluence of Biology and Computer Science

    

Computer science is similar to, and fundamental like, Mathematics. Inception of every CS area is motivated by a specific need for information processing. Needs in Defense sector caused the birth and growth of CS fields such as image analysis, coding & information theory, testing, and electronic security. Industrial automation was the reason for CS fields such as computer aided design, scheduling, user interface design, robotics, speech processing, and natural language systems. 

Biology is the next motivator for Computer Science. Progress in CS will define the future of biology. 

Biology is the study of living things, through collection and interpretation of data. Data collection means, e.g., the sophistication of laboratory equipment, have greatly increased in the past 10-15 years. We now produce significantly more biology data than can be manually interpreted. The progress of biology as a science, and consequently the progress of the humankind, depends on efficient and effective data interpretation.

Molecular biology studies the organization and function of molecular level structures (DNA, amino acids, proteins) in living organisms. Every cell in a species is almost identical. Cells are made up of DNA. DNA can be written out as a linear sequence of chemicals A, T, G, C. Genes, which are specific combinations of these chemicals (e.g., ATGTGGC), contain instructions for making proteins. Proteins act alone or in groups to perform every important body function.

Bioinformatics, our topic for today, is the science of using information to understand biology. Unfortunately, bioinformatics has become a buzzword; it is being used in a number of ways, depending on who is using it. The questions that drive bioinformatics are same as the ones humans have been asking for hundreds of years. How can we cure disease? How can we prevent infection? How can we produce enough food to feed all of humanity? Companies in the business of developing drugs, agricultural chemicals, hybrid plants, plastics, petroleum derivatives, and biological approaches to environmental remediation, are looking to bioinformatics to provide new targets and to help replace scarce natural resources. Researchers come to bioinformatics from many fields, including mathematics, computer science, and linguistics. 

Let us understand how CS is changing biology. As little as 20 years ago, looking for similarities between two DNA sequences would have been like looking for a needle in a haystack. Today, with commonly used computer programs, a biologist can find dozens of sequence matches in seconds, matching her sequence with the entire publicly held collection of sequences, using the World Wide Web. The increasing automation of experimental biology, and the application of IT to it, have lead to a fundamental change in the way biology is done. In addition to anecdotal work--locating and studying in detail a single gene at a time--we are now cataloguing as a “factory”, all the data that is available, making complete maps to which we can later return and mark the points of interest. The trend is toward storage of raw biological data of all types in public databases. Instead of doing preliminary research in the lab, scientists are first going to these databases to save time and resources.

What areas of CS does bioinformatics involve? It includes the representation, storage, and distribution of data. It covers intelligent design of data formats and databases, creation of tools to query those databases, and development of user interfaces that allow biologists to seamlessly navigate without getting lost in a sea of information. It involves developing analytical tools to mine for new knowledge in data. 

In short, the following areas of computer science are likely to be fundamentally affected by biology: algorithm design & complexity, parallel computing & embedded systems, image analysis, artificial intelligence, 3D modeling, graphics & visualization.

In conclusion, CS graduates should be extremely excited at the opportunity for contributing to biology through bioinformatics. Bioinformatics helps in improved diagnosis of disease, rational drug design, gene therapy, and in custom drug manufacturing. It helps identify new energy sources, ways of protection from biological and chemical warfare, and methods for waste cleanup. It helps in studying species evolution and migration, and in forensics. Bioinformatics can help build disease-, insect-, and drought-resistant crops, healthier farm animals, and biopesticides.

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