Near-unsupervised computational methods for exploring 'omic' data
Grant number: DP150103512 | Funding period: 2015 - 2019
The project aims to investigate the recently proposed promising machine learning paradigm "Near Unsupervised Learning" by critically analysing and comparing existing methods. The project also aims to develop new algorithms in the broader spectrum of Big Data Analytics and their adaptation to the following three applications: species separation in metagenomic data; development of a model to relate genomic information to cancer drug sensitivity; and, the identification of distinct metabolite distribution patterns in mass spectrometry metabolomic data. The potential outcomes include increased understanding of the usefulness of fertilisers on different plant varieties and newly emerging plant di..View full description
Related publications (15)
A Physarum-Inspired Algorithm for Minimum-Cost Relay Node Placement in Wireless Sensor Networks
Yahui Sun, Daniel Rehfeldt, Marcus Brazil, Doreen Thomas, Saman Halgamuge
Relay node placement, which aims to connect pre-deployed sensor nodes to base stations, is essential in minimizing the costs of wi..
Estimating neuronal conductance model parameters using dynamic action potential clamp
Y Deerasooriya, G Berecki, D Kaplan, IC Forster, S Halgamuge, S Petrou
Parameterization of neuronal membrane conductance models relies on data acquired from current clamp (CC) or voltage clamp (VC) rec..
ENVirT: inference of ecological characteristics of viruses from metagenomic data
Duleepa Jayasundara, Damayanthi Herath, Damith Senanayake, Isaam Saeed, Cheng-Yu Yang, Yuan Sun, Bill C Chang, Sen-Lin Tang, Saman K Halgamuge
Background: Estimating the parameters that describe the ecology of viruses,particularly those that are novel, can be made possible..
A new peak detection algorithm for MALDI mass spectrometry data based on a modified Asymmetric Pseudo-Voigt model
C Wijetunge, I Saeed, BA BOUGHTON, U Roessner, SK Halgamuge
Background Mass Spectrometry (MS) is a ubiquitous analytical tool in biological research and is used to measure the mass-to-charge..