Engineering topics
Publications and source records attributed to Williams, Peter L..
Methods to identify a set of probe polynucleotides suitable for detecting a set of targets and in particular methods for identification of primers suitable for detection of target microorganisms related polynucleotides, set of polynucleotides and compositions, and related methods and systems for detection and/or identification of microorganisms in a sample.
PriMux is a new software package for selecting multiplex compatible, degenerate primers and probes to detect diverse targets such as viruses. It requires no multiple sequence alignment, instead applying k-mer algorithms, hence it scales well for large target sets and saves user effort from curating sequences into alignable groups. PriMux has the capability to predict degenerate primers as well as probes suitable for TaqMan or other primer/probe triplet assay formats, or simply probes for microarray or other single-oligo assay formats. PriMux employs suffix array methods for efficient calculations on oligos 10-,100 nt in length. TaqManH primers and probes for each segment of Rift Valley fever virus were designed using PriMux, and lab testing comparing signatures designed using PriMux versus those designed using traditional methods demonstrated equivalent or better sensitivity for the PriMux-designed signatures compared to traditional signatures. In addition, we used PriMux to design TaqManH primers and probes for unalignable or poorly alignable groups of targets: that is, all segments of Rift Valley fever virus analyzed as a single target set of 198 sequences, or all 2863 Dengue virus genomes for all four serotypes available at the time of our analysis. The PriMux software is available as open source from http:// sourceforge.net/projects/PriMux.
The goal of this paper is to provide a foundation for objectively comparing volume rendered images. The key elements of the foundation are: (1) a rigorous specification of all the parameters that need to be specified to define the conditions under which a volume rendered image is generated; (2) a methodology for difference classification, including a suite of functions or metrics to quantify and classify the difference between two volume rendered images that will support an analysis of the relative importance of particular differences. The results of this method can be used to study the changes caused by modifying particular parameter values, to compare and quantify changes between images of similar data sets rendered in the same way, and even to detect errors in the design, implementation or modification of a volume rendering system. If one has a benchmark image, for example one created by a high accuracy volume rendering system, the method can be used to evaluate the accuracy of a given image.