Computing for biologists: lessons from some successful case studies

ABSTRACT

My presentation will be online at the address http://cs.nyu.edu/cs/faculty/shasha/papers/sigmodtut05.ppt in addition to at the SIGMOD site. The presentation discusses computational techniques that have helped biologists, including combinatorial design to support a disciplined experimental design, visualization techniques to display the interaction among multiple inputs, and the discovery of gene function through the search through related species, and others.In this writeup, I confine myself to informal remarks describing both social and technical lessons I have learned while working with biologists. I intersperse these comments with references to relevant papers when appropriate.The tutorial is meant to appeal to researchers and practitioners in databases, data mining, and combinatorial algorithms as well as to natural scientists, especially biologists.

REFERENCES

• 1: Kenneth Birnbaum, Philip N. Benfey, and Dennis Shasha cis element/transcription factor analysis (cis/tf): A method for discovering transcription factor/cis element relationships. Genome Research, 11:1567--1573, 2001.
• 2: Kenneth Birnbaum, Dennis E. Shasha, Jean Y. Wang, Jee W. Jung, Georgina M. Lambert, David W. Galbraith, and Philip N. Benfey. A gene expression map of the arabidopsis root. Science, pages 1956--1960, 2003.
• 3: D. J. Cook and L. B. Holder. Substructure discovery using minimum description length and background knowledge. Artificial Intelligence Research, 1:231--255, 1994.
• 4: Laurence V. Lejay, Dennis E. Shasha, Peter M. Palenchar, Andrei Y. Kouranov, Alexis A. Cruikshank, Michael F. Chou, and Gloria M. Coruzzi. Adaptive combinatorial design to explore large experimental spaces: approach and validation. Systems Biology, 1.2:206--212, 2004.
• 5: Mitchell Levesque, Dennis Shasha, Wook Kim, Michael G. Surette, and Philip N. Benfey. Trait-to-gene: A computational method for predicting the function of uncharacterized genes. Current Biology, 13:129--133, 2003.
• 6: D. Shasha and R. Giugno. Graphgrep: A fast and universal method for querying graphs. Proceeding of the International Conference in Pattern recognition (ICPR), pages 112--115, 2002.
• 7: Xifeng Yan , Philip S. Yu , Jiawei Han, Graph indexing: a frequent structure-based approach, Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 13-18, 2004, Paris, France [doi>10.1145/1007568.1007607]