Dominique Blache CITS3200 Project - Episodic events in endocrinology

Integrated software to analyse episodic events in hormones profiles

Hormonal profiles are often following rhythms than can be seasonal, or regular cycles over, say 24 h (daily rhythms), or the frequency and amplitude of short, rapid increases in concentration, usually known episodic ultradian events (see LH Profile Figure 1). Because if the frequency of EUEs is not constant, few statistical approaches can be used to identify true EUEs form background noise. See an example of LH profile here: https://drive.google.com/open id=1GcR0nt92xQTx_ZDiOAoYaWQCFuW4k-GJ

The normal methods for measuring hormone concentration in biological substrates are radioimmunoassay (RIA), enzyme-linked immunosorbent assay (ELISA) and enzyme immunoassay (EIA). They are based on the fitting of a curve describing the relationship between concentration of a standards and the level of a signal (radioactivity, colour, fluorescence) with a specific instrument. ELISA or EIA methods are costly but rapid and sensitive, and are used for small numbers of samples (hundreds). RIA method is very sensitive and low cost when used to assay large number of samples (over a thousand), so is most appropriate for analysis of pulse patterns. We need to develop an integrated software package for processing the raw data generated by the primary instrument (eg, gamma counter) and for the analysis of pulsatile patterns of secretion (stochastic analysis). Commercial software has been created to perform these analyses but most of it is either discontinued or is only available for a single platform (often a combination of instrument and computer system supplied by the instrument manufacturer). None of the available software integrates both processing of raw data into assay output with stochastic analysis (pulses), or statistical analysis of long-duration rhythms.

The software package will:

Run on multiple platforms (Windows, Macintosh, Unix)
Capture data from the various instruments that generate the raw data;
Analyse raw data using standard curves;
Analyse profiles to detect pulses, rhythms and trends, based on both the variability of the assay and the biological variability of the data;
Generate reports that illustrate the quality of the data processing and the characteristics of the pulses and long lasting change (amplitude, nadir, duration, frequency);
Include a database that can be used to refine the parameters used in the algorithms.

Client

Contact: Dominique Blache
Phone: 6488 6730
Email: [email protected]
Preferred contact: Email
Location: UWA Crawley

IP Exploitation Model

The IP exploitation model requested by the Client is: Creative Commons ( open source ) http://creativecommons.org.au/

Department of Computer Science & Software Engineering
The University of Western Australia
Last modified: 22 July 2019
Modified By: Michael Wise