• Undergraduate student participants supported with NSF funds must be citizens or permanent residents of the United States or its possessions. An undergraduate student is a student who is enrolled in a degree program (part-time or full-time) leading to a bachelor's degree.
• Students with basic biology background (general biology and organic chemistry; molecular cell biology preferred) and introductory programming experience (C/C++ or Java preferred).

Recent breakthroughs in DNA sequencing, screening, and related technologies have enabled researchers in the agricultural sciences, biology, and biochemistry to model the function of hundreds to thousands of genes simultaneously. This has led to an explosion in applied research in bioinformatics, ranging from drug design to plant breeding and crop management, as well as an unprecedented demand for data acquisition and information management capabilities in the area of computational genomics (CG).

While a first generation of laboratory techniques and analytical algorithms has already been developed and is gaining widespread commercial use, we expect future advances to dramatically increase the role of bioinformatics throughout society. Today's demand for bioinformatics expertise far exceeds the supply, and this imbalance will become more severe over the coming decade. Unfortunately, current degree programs in traditional disciplines fail to provide the kind of training needed for the practitioners of the future. The problem is that bioinformatics requires a rich, interdisciplinary education combining topics such as structural and functional genomics, laboratory methods, database engineering, fundamentals of mathematical and statistical models for gene expression, software development and engineering in CG, and specific skills such as polymerase chain reaction (PCR) experiment design and using and developing alignment and clustering software for genome data.

The Kansas State University Bioinformatics Working Group has developed a Research Experience for Undergraduates (REU) Summer Program to prepare undergraduate students to become tomorrow's practitioners in the rapidly growing area of applied computational genomics. This intensive summer-long program will build on K-State bioinformatics program (jointly sponsored by the Colleges of Engineering and Agriculture and by the Division of Biology), the plant genome research activities of the Department of Plant Pathology, and CG research in the Department of Computing and Information Sciences. The Bioinformatics Working Group has assembled a multi-disciplinary team of faculty, academic professionals, and students dedicated to producing the next generation of CG methods, environments, and applications.

This program will help prepare undergraduate students for careers in the biotechnology industry where CG skills and expertise are a growing need for the national workforce. By exposing students to this combination of hands-on applications and cutting-edge research, we expect the students to come away with the skill set to uniquely position themselves in the expanding field of applied genomics.

The students will have a unique opportunity to work with established teams headed by Dr. Jan Leach and Dr. William Hsu at K-State and Dr. Richard Bruskiewich, a K-State affiliate researcher at the International Rice Research Institute (IRRI) in the Phillippines, in the use of technologies and methodologies for functional genomics, especially in using the biological and computational tools for gene discovery and to understand gene function. They will become part of the working team and will contribute to research projects on identification of deletion mutants in a gene of interest from the rice mutant collection maintained by K-State, IRRI, and their collaborators.

Wet lab research: The formalization of CG experiments demands an understanding of the protocols for detection of specific deletion mutants. This will involve the design and implementation of PCR experiments, use of software for data collection and processing, data modeling and information retrieval (for comparative purposes), and finally statistical algorithms for learning from data and classification of new data. In our application domain of CG, we will show students how to use (1) software (e.g., UTRdb, UTRsite, EBI ClustalW, Whitehead Institute’s Primer Picker, and IRRI's IRIS) in support of molecular biology experiments such as development of PCR primers for screening the DNA pools, and (2) computational analyses such as gene clustering and expression network discovery. Basic programming background can be fulfilled by a first course in computer science.

Use and development of intelligent systems software for functional genomics: In May, 2002, the K-State KDD Lab released software packages called Machine Learning in Java (MLJ) and Bayesian Network Tools in Java (BNJ), containing a number of previously published algorithms, as well as several developed by the KDD Lab, that are useful in building computational models of gene regulatory dynamics. We intend to expose students in this program to basic bioinformatics software development. This includes use of the BNJ package as a standalone application as well as understanding and modifying the documented source code.

Students will have free time on weekends. We will plan for some team building activities, including recreational activities and cookouts.

Local students who have demonstrated successful projects may be asked to continue working with the Laboratory for Knowledge Discovery in Databases (KDD Lab) during the academic year.

Contact:
Kansas State University Bioinformatics Working Group
c/o Dr. William H. Hsu
234 Nichols Hall
Manhattan, KS 66506-2302
bhsu(AT)cis.ksu.edu
Phone: (785) 532-6350 x29
Fax: (785) 532-7353

To apply now, download our PDF application form.