Abstract
A statistical search technique is applied to certain critical computational problems in mapping the human genome, employing a Bayesian model to provide the best solution accuracy as a function of the number of parameters and heuristic search techniques derived from artificial intelligence. Critical contributions towards the solution of the assembly problem for optical mapping data are made, including the first detailed optical mapping data model, an efficient statistical algorithm that implements the update rules for the model parameters iteratively using dynamic programming, and experiments which produce highly accurate maps over wide range of experimental variations.
Original language | English (US) |
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Pages (from-to) | 434-437 |
Number of pages | 4 |
Journal | Proceedings - IEEE Computer Society's International Computer Software and Applications Conference |
State | Published - 1997 |
Event | Proceedings of the 1997 21st Annual International Computer Software & Applications Conference, COMPSAC'97 - Washington, DC, USA Duration: Aug 13 1997 → Aug 15 1997 |
ASJC Scopus subject areas
- Software
- Computer Science Applications