Gene prediction is one of the most challenging tasks in genome analysis, for which many tools have been developed and are still evolving. In this paper, we present a novel gene pr...
Rong She, Jeffrey Shih-Chieh Chu, Ke Wang, Nanshen...
The MAP (maximum a posteriori hypothesis) problem in Bayesian networks is to find the most likely states of a set of variables given partial evidence on the complement of that set...
We focus on a multidimensional field with uncorrelated spectrum, and study the quality of the reconstructed signal when the field samples are irregularly spaced and affected by in...
Background: Structure matching plays an important part in understanding the functional role of biological structures. Bioinformatics assists in this effort by reformulating this p...
Several methods to select variables that are subsequently used in discriminant analysis are proposed and analysed. The aim is to find from among a set of m variables a smaller sub...