This paper describes HTS-Corrector, a software application for the analysis of HTS data, detection and visualization of systematic error, and corresponding correction of HTS signals. Three new methods for the statistical analysis and correction of raw HTS data are included in HTS-Corrector: background evaluation, well correction and hit-sigma distribution procedures intended to minimize the impact of systematic errors. We discuss the main features of HTS-Corrector and demonstrate the benefits of the algorithms.
A typical modern high-throughput screening (HTS) operation consists of testing thousands of chemical compounds to select active ones for future detailed examination. The authors describe 3 clustering techniques that can be used to improve the selection of active compounds (i.e., hits). They are designed to identify quality hits in the observed HTS measurements. The considered clustering techniques were first tested on simulated data and then applied to analyze the assay inhibiting Escherichia coli dihydrofolate reductase produced at the HTS laboratory of McMaster University. (Journal of Biomolecular Screening 2006:903-914)
It is widely accepted that there is more to software construction than basic programming skills [13,11,15,16]. Professional software construction involves not only understanding some theoretical concepts, but also mastering appropriate tools and practices. In this paper, we present an undergraduate course in Software Construction and Maintenance, developed with the goal of introducing students to those key concepts, tools and practices.We first outline the content of that course, explaining how it fits within our undergraduate program. We then present a key element of that course-namely, its maintenance corpus along with its testing frameworks-used to concretely introduce students to various tools and practices, e.g., automatic test execution, build and configuration management, source code documentation, use of assertions, etc.
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