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Protein interaction network topology analysis for drug target discovery
Presentation / Conference Contribution
Lynden, S., Idowu, O., Periorellis, P., Young, M., & Andras, P. (2004, May). Protein interaction network topology analysis for drug target discovery. Presented at Japan Human Proteomics 2004, Tokyo, Japan

The aim of our work is to accumulate protein interaction data and to develop computational techniques for analysing the topologies of protein interaction networks to reveal network vulnerabilities. We have developed a variety of network analysis algo... Read More about Protein interaction network topology analysis for drug target discovery.

Using supervised machine learning algorithms to detect suspicious URLs in online social networks
Presentation / Conference Contribution
Al-Janabi, M., Quincey, E. D., & Andras, P. (2017, July). Using supervised machine learning algorithms to detect suspicious URLs in online social networks. Presented at 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017, Sydney, Australia

The increasing volume of malicious content in social networks requires automated methods to detect and eliminate such content. This paper describes a supervised machine learning classification model that has been built to detect the distribution of m... Read More about Using supervised machine learning algorithms to detect suspicious URLs in online social networks.

A critical analysis of studies that address the use of text mining for citation screening in systematic reviews
Presentation / Conference Contribution
Olorisade, B. K., de Quincey, E., Brereton, P., & Andras, P. (2016, June). A critical analysis of studies that address the use of text mining for citation screening in systematic reviews. Presented at EASE '16: 20th International Conference on Evaluation and Assessment in Software Engineering, Limerick, Ireland

Background: Since the introduction of the systematic review process to Software Engineering in 2004, researchers have investigated a number of ways to mitigate the amount of effort and time taken to filter through large volumes of literature.

Aim:... Read More about A critical analysis of studies that address the use of text mining for citation screening in systematic reviews.

Towards reliable hybrid bio-silicon integration using novel adaptive control system
Presentation / Conference Contribution
Luo, J. W., Degenaar, P., Coapes, G., Yakovlev, A., Mak, T., & Andras, P. (2013, May). Towards reliable hybrid bio-silicon integration using novel adaptive control system. Presented at 2013 IEEE International Symposium on Circuits and Systems (ISCAS), Beijing, China

Hybrid bio-silicon networks are difficult to implement in practice due to variations of biological neuron bursting frequency. This causes the hybrid network to have inaccuracies and unreliability. The network may produce irregular bursts or incorrect... Read More about Towards reliable hybrid bio-silicon integration using novel adaptive control system.

Random projection neural network approximation
Presentation / Conference Contribution
Andras, P. (2018, July). Random projection neural network approximation. Presented at 2018 International Joint Conference on Neural Networks (IJCNN), Rio de Janeiro, Brazil

Neural networks are often used to approximate functions defined over high-dimensional data spaces (e.g. text data, genomic data, multi-sensor data). Such approximation tasks are usually difficult due to the curse of dimensionality and improved method... Read More about Random projection neural network approximation.

Modelling the restoration of activity in a biological neural network
Presentation / Conference Contribution
Dos Santos, F., Steyn, J. S., & Andras, P. (2016, July). Modelling the restoration of activity in a biological neural network. Presented at 2016 International Joint Conference on Neural Networks (IJCNN), Vancouver, BC, Canada

Understanding the mechanisms of restoration of activity in biological neural systems following exposure to damage is key for design of future neuro-prosthetic devices and restorative treatments. The pyloric rhythm network within the crustacean stomat... Read More about Modelling the restoration of activity in a biological neural network.

Uncertainty and communication complexity in iterated cooperation games
Presentation / Conference Contribution
Andras, P. (2008, August). Uncertainty and communication complexity in iterated cooperation games. Presented at Artificial Life XI 2008, Winchester

Iterated cooperation games (e.g. Prisoner’s Dilemma) are used to analyze the emergence and evolution of cooperation among selfish individuals. Uncertainty of outcomes of games is an important factor that influences the level of cooperation. Communica... Read More about Uncertainty and communication complexity in iterated cooperation games.

A genetic solution for the cutting stock problem
Presentation / Conference Contribution
András, P., András, A., & Szabό, Z. (1996, August). A genetic solution for the cutting stock problem. Presented at First Online Workshop on Soft Computing (WSC1), Nagoya, Japan

The cutting stock problem it is of great interest in relation with several real world problems. Basically it means that there are some smaller pieces that have to be cut from a greater stock piece, in such a way, that the remaining part of the stock... Read More about A genetic solution for the cutting stock problem.

Unsupervised segmentation of cell nuclei using geometric models
Presentation / Conference Contribution
Fitch, S., Jackson, T., Andras, P., & Robson, C. (2008, May). Unsupervised segmentation of cell nuclei using geometric models. Presented at 2008 5th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Paris, France

Fluorescent microscopy of biological samples allows non-invasive screening of specific molecular events in-situ. This approach is useful for investigating intricate signalling pathways and in the drug discovery process. The large volumes of data invo... Read More about Unsupervised segmentation of cell nuclei using geometric models.

A statistical aimbot detection method for online FPS games
Presentation / Conference Contribution
Yu, S.-Y., Hammerla, N., Yan, J., & Andras, P. (2012, June). A statistical aimbot detection method for online FPS games. Presented at The 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, QLD, Australia

First Person Shooter (FPS) is a popular genre in online gaming, unfortunately not everyone plays the game fairly, and this hinders the growth of the industry. The aiming robot (aimbot) is a common cheating mechanism employed in this genre, it differs... Read More about A statistical aimbot detection method for online FPS games.

Towards an Accurate Identification of Pyloric Neuron Activity with VSDi
Presentation / Conference Contribution
dos Santos, F., Andras, P., & Lam, K. (2017, September). Towards an Accurate Identification of Pyloric Neuron Activity with VSDi. Presented at ICANN 2017: 26th International Conference on Artificial Neural Networks, Alghero, Italy

Voltage-sensitive dye imaging (VSDi) which enables simultaneous optical recording of many neurons in the pyloric circuit of the stomatogastric ganglion is an important technique to supplement electrophysiological recordings. However, utilising the te... Read More about Towards an Accurate Identification of Pyloric Neuron Activity with VSDi.

Open-ended evolution in cellular automata worlds
Presentation / Conference Contribution
Andras, P. (2017, September). Open-ended evolution in cellular automata worlds. Presented at ECAL 2017, the Fourteenth European Conference on Artificial Life, Lyon, France

Open-ended evolution is a fundamental issue in artificial life research. We consider biological and social systems as a flux of interacting components that transiently participate in interactions with other system components as part of these systems.... Read More about Open-ended evolution in cellular automata worlds.

A systematic analysis of random forest based social media spam classification
Presentation / Conference Contribution
Al-Janabi, M., & Andras, P. (2017, August). A systematic analysis of random forest based social media spam classification. Presented at NSS: International Conference on Network and System Security, Helsinki, Finland

Recently random forest classification became a popular choice machine learning applications aimed to detect spam content in online social networks. In this paper, we report a systematic analysis of random forest classification for this purpose. We as... Read More about A systematic analysis of random forest based social media spam classification.

e-Science Tools for the Analysis of Complex Systems
Presentation / Conference Contribution
Idowu, O., Lynden, S., & Andras, P. (2004, August). e-Science Tools for the Analysis of Complex Systems. Presented at UK e-Science All Hands Meeting 2004, Nottingham


Many real world complex systems (e.g., protein-protein interaction networks in living cells, the Internet) can be conceptualised as graphs of interacting components, where the components are the nodes and the interactions are the edges of the grap... Read More about e-Science Tools for the Analysis of Complex Systems.

PD disease state assessment in naturalistic environments using deep learning
Presentation / Conference Contribution
Hammerla, N. Y., Fisher, J., Andras, P., Rochester, L., Walker, R., & Plötz, T. (2015, January). PD disease state assessment in naturalistic environments using deep learning. Presented at Twenty-Ninth AAAI conference on artificial intelligence, Austin, Texas

Management of Parkinson's Disease (PD) could be improved significantly if reliable, objective information about fluctuations in disease severity can be obtained in ecologically valid surroundings such as the private home. Although automatic assessmen... Read More about PD disease state assessment in naturalistic environments using deep learning.

Fault tolerance and network integrity measures: the case of computer-based systems
Presentation / Conference Contribution
Andras, P., Idowu, O., & Periorellis, P. (2006, April). Fault tolerance and network integrity measures: the case of computer-based systems. Presented at AISB'06: Network Analysis in Natural Sciences and Engineering, Bristol

Fault tolerance is a key aspect of the dependability of complex computer-based systems. Fault tolerance may be difficult to measure directly in complex real world systems, and we propose here to measure it in terms of integrity preservation of the sy... Read More about Fault tolerance and network integrity measures: the case of computer-based systems.

Computer Anxiety and the Big Five
Presentation / Conference Contribution
Crabbe, S. J., & Andras, P. (2012, November). Computer Anxiety and the Big Five. Presented at PPIG 2012 - 24th Annual Workshop, London

This paper explores the relationship between personality traits, as described by the Big Five Factors model, and the likelihood of someone suffering from computer anxiety. The research sample was a cohort of Business School Undergraduates. It was fou... Read More about Computer Anxiety and the Big Five.

Composition of Games as a Model for the Evolution of Social Institutions
Presentation / Conference Contribution
Andras, P. (2020, July). Composition of Games as a Model for the Evolution of Social Institutions. Presented at ALIFE 2020: The 2020 Conference on Artificial Life, Online

The evolution of social institutions (e.g. institutions of political decision making or joint resource administration) is an important question in the context of understanding of how societies develop and evolve. In principle, social institutions can... Read More about Composition of Games as a Model for the Evolution of Social Institutions.

On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution
Presentation / Conference Contribution
Hammerla, N. Y., Kirkham, R., Andras, P., & Ploetz, T. (2013, September). On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution. Presented at UbiComp '13: The 2013 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Zurich, Switzerland

The majority of activity recognition systems in wearable computing rely on a set of statistical measures, such as means and moments, extracted from short frames of continuous sensor measurements to perform recognition. These features implicitly quant... Read More about On preserving statistical characteristics of accelerometry data using their empirical cumulative distribution.