NEAR UNSUPERVISED LEARNING FOR EARLY DISCOVERY OF NOVEL PATTERNS: METHODS, SCALABILITY AND LABEL DEPENDABILITY
Grant number: DP1096296 | Funding period: 2010 - 2014
This project aims to predict the unknown class labels using the existing small number of class labels. The outcomes of the project have direct relevance to the economy, environment, energy and health sectors due to the abundance of data coming out of these areas. For example, if an oncogene, a gene that can cause cancer when mutated can be found using data with only few labels and a large amount of unlabelled data, the costs and time needed for lab experimentation can be greatly reduced enabling pharmaceutical companies to develop corresponding medicines quicker. It will not only save more lives but also generates millions of dollars of income.
Related publications (13)
A physarum-inspired prize-collecting steiner tree approach to identify subnetworks for drug repositioning
Yahui Sun, Pathima Nusrath Hameed, Karin Verspoor, Saman Halgamuge
BACKGROUND: Drug repositioning can reduce the time, costs and risks of drug development by identifying new therapeutic effects for..
Accurate reconstruction of viral quasispecies spectra through improved estimation of strain richness
Duleepa Jayasundara, I Saeed, BC Chang, Sen-Lin Tang, Saman K Halgamuge
BACKGROUND: Estimating the number of different species (richness) in a mixed microbial population has been a main focus in metagen..
Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges
Mario A Munoz, Yuan Sun, Michael Kirley, Saman K Halgamuge
Selecting the most appropriate algorithm to use when attempting to solve a black-box continuous optimization problem is a challeng..
EXIMS: an improved data analysis pipeline based on a new peak picking method for EXploring Imaging Mass Spectrometry data
Chalini D Wijetunge, Isaam Saeed, Berin A Boughton, Jeffrey M Spraggins, Richard M Caprioli, Antony Bacic, Ute Roessner, Saman K Halgamuge
MOTIVATION: Matrix Assisted Laser Desorption Ionization-Imaging Mass Spectrometry (MALDI-IMS) in 'omics' data acquisition generate..
Extended Differential Grouping for Large Scale Global Optimization with Direct and Indirect Variable Interactions
Yuan Sun, Michael Kirley, Saman K Halgamuge
Cooperative co-evolution is a framework that can be used to effectively solve large scale optimization problems. This approach emp..
Inferring copy number and genotype in tumour exome data
Kaushalya C Amarasinghe, Jason Li, Sally M Hunter, Georgina L Ryland, Prue A Cowin, Ian G Campbell, Saman K Halgamuge
BACKGROUND: Using whole exome sequencing to predict aberrations in tumours is a cost effective alternative to whole genome sequenc..
Bioinformatics Pipelines for Targeted Resequencing and Whole-Exome Sequencing of Human and Mouse Genomes: A Virtual Appliance Approach for Instant Deployment
Jason Li, Maria A Doyle, Isaam Saeed, Stephen Q Wong, Victoria Mar, David L Goode, Franco Caramia, Ken Doig, Georgina L Ryland, Ella R Thompson, Sally M Hunter, Saman K Halgamuge, Jason Ellul, Alexander Dobrovic, Ian G Campbell, Anthony T Papenfuss, Grant A McArthur, Richard W Tothill
Targeted resequencing by massively parallel sequencing has become an effective and affordable way to survey small to large portion..
Exploratory analysis of high-throughput metabolomic data
Chalini D Wijetunge, Zhaoping Li, Isaam Saeed, Jairus Bowne, Arthur L Hsu, Ute Roessner, Antony Bacic, Saman K Halgamuge
In order to make sense of the sheer volume of metabolomic data that can be generated using current technology, robust data analysi..
Microbial and viral metagenomes of a subtropical freshwater reservoir subject to climatic disturbances
Ching-Hung Tseng, Pei-Wen Chiang, Fuh-Kwo Shiah, Yi-Lung Chen, Jia-Rong Liou, Ting-Chang Hsu, Suhinthan Maheswararajah, Isaam Saeed, Saman Halgamuge, Sen-Lin Tang
Extreme climatic activities, such as typhoons, are widely known to disrupt our natural environment. In particular, studies have re..