Abstract
Entropy estimation, which plays a central role in the analysis of biological data is discussed. Small improvements in estimates of relative entropy can yield significant rewards in the quality of sequence alignments. Estimation must be carried out in a regime where the possibilities are not exhausted by the data. It is found that within a Bayesian approach, the best possible estimates based on the data can be made by using a uniform entropic prior- one that reflects minimal a priori assumptions about the entropy.
| Original language | English (US) |
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| Title of host publication | Proceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 |
| Editors | J.H. Caulfield, S.H. Chen, H.D. Cheng, R. Duro, J.H. Caufield, S.H. Chen, H.D. Cheng, R. Duro, V. Honavar |
| Number of pages | 1 |
| Volume | 6 |
| State | Published - Dec 1 2002 |
| Event | Proceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 - Research Triange Park, NC, United States Duration: Mar 8 2002 → Mar 13 2002 |
Other
| Other | Proceedings of the 6th Joint Conference on Information Sciences, JCIS 2002 |
|---|---|
| Country/Territory | United States |
| City | Research Triange Park, NC |
| Period | 3/8/02 → 3/13/02 |
All Science Journal Classification (ASJC) codes
- Computer Science(all)