Learn More
MOTIVATION Current software tools are moderately effective in predicting genetic structure (exons, introns, intergenic regions, and complete genes) from raw DNA sequence data. Improvements in accuracy and speed are needed to deal with the increasing volume of data from large scale sequencing projects. RESULTS We present a two-stage computer program to(More)
Logistic regression is frequently used in pattern recognition problems to model conditional probabilities of class membership given features observed. While performing well in many applications, logistic regression is limited to a relatively simple parametric model and is often not suitable for complex applications. This article describes a generalization(More)
An interactive computer program has been developed to align a three-dimensional region of interest (ROI) model to technetium-99m-hexamethylpropylenamine oxime (99mTc-HMPAO) single-photon emission computed tomography (SPECT) studies of the brain. The ROI model subdivides the human brain into fourteen discrete regions. A study was performed to determine(More)
Bayesian belief networks provide estimates of conditional probabilities, called query responses. The precision of these estimates is assessed using posterior distributions. This paper discusses two claims and a conjecture by Kleiter (1996) concerning the exact posterior distribution of queries. The two claims provide conditions where a query has an exact(More)
Border molding is an important step in the fabrication of complete dentures. Conventional border molding using impression modeling plastic has been time-consuming and has resulted in a great variation in the shape of the recorded borders. This study compared the shape and variability of the vestibular impressions made with impression modeling plastic and a(More)
A number of methods have been proposed to estimate the period of a variable star; e.g., a recent approach uses smoothing spline regression to fit tentative periodic functions (light curves) and selects the period minimizing a robust goodness-of-fit criterion. These methods assume that measurement errors vary independently over time. Empirical evidence,(More)
  • 1