DocumentCode :
763851
Title :
Crossing the interdisciplinary barrier: a baccalaureate computer science option in bioinformatics
Author :
Doom, Travis ; Raymer, Michael ; Krane, Dan ; Garcia, Oscar
Author_Institution :
Dept. of Comput. Sci. & Eng., Wright State Univ., Dayton, OH, USA
Volume :
46
Issue :
3
fYear :
2003
Firstpage :
387
Lastpage :
393
Abstract :
Bioinformatics is a new and rapidly evolving discipline that has emerged from the fields of experimental molecular biology and biochemistry, and from the artificial intelligence, database, pattern recognition, and algorithms disciplines of computer science. Largely because of the inherently interdisciplinary nature of bioinformatics research, academia has been slow to respond to strong industry and government demands for trained scientists to develop and apply novel bioinformatic techniques to the rapidly growing freely available repositories of genetic and proteomic data. While some institutions are responding to this demand by establishing graduate programs in bioinformatics, the entrance barriers for these programs are high, largely because of the significant amount of prerequisite knowledge in the disparate fields of biochemistry and computer science required for sophisticated new approaches to the analysis and interpretation of bioinformatics data. The authors present an undergraduate-level bioinformatics curriculum in computer science designed for the baccalaureate student. This program is designed to be tailored easily to the needs and resources of a variety of institutions.
Keywords :
biochemistry; biomedical education; computer science education; educational courses; artificial intelligence; baccalaureate computer science option; baccalaureate student; biochemistry; bioinformatics; computer science; database; entrance barriers; experimental molecular biology; genetic data; inherently interdisciplinary nature; interdisciplinary barrier; pattern recognition; proteomic data; undergraduate engineering education; undergraduate-level bioinformatics curriculum; Artificial intelligence; Biochemistry; Bioinformatics; Biology; Computer science; Databases; Genetics; Government; Industrial training; Pattern recognition;
fLanguage :
English
Journal_Title :
Education, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9359
Type :
jour
DOI :
10.1109/TE.2003.814593
Filename :
1220740
Link To Document :
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