Enzyme genetic programming. - Michael A. Lones; Andy M. Tyrrell (CEC, 2001)

Crossover and bloat in the functionality model of enzyme genetic programming. - Michael A. Lones; Andy M. Tyrrell (IEEE Congress on Evolutionary Computation, 2002)

Biomimetic Representation with Genetic Programming Enzyme. - Michael A. Lones; Andrew M. Tyrrell (Genet. Program. Evolvable Mach., 2002)

Enzyme genetic programming : modelling biological evolvability in genetic programming. - Michael Adam Lones (2003)

Enzyme Genetic Programming. - Michael A. Lones; Andy M. Tyrrell (Cellular Computing, 2004)

The evolutionary computation approach to motif discovery in biological sequences. - Michael A. Lones; Andrew M. Tyrrell (GECCO Workshops, 2005)

A co-evolutionary framework for regulatory motif discovery. - Michael A. Lones; Andy M. Tyrrell (IEEE Congress on Evolutionary Computation, 2007)

Regulatory Motif Discovery Using a Population Clustering Evolutionary Algorithm. - Michael A. Lones; Andy M. Tyrrell (IEEE ACM Trans. Comput. Biol. Bioinform., 2007)

Implicit Context Representation Cartesian Genetic Programming for the assessment of visuo-spatial ability. - Stephen L. Smith 002; Michael A. Lones (IEEE Congress on Evolutionary Computation, 2009)

Discriminating normal and cancerous thyroid cell lines using implicit context representation Cartesian genetic programming. - Michael A. Lones; Stephen L. Smith 002; Andrew T. Harris; Alec S. High; Sheila E. Fisher; D. Alastair Smith; Jennifer Kirkham (IEEE Congress on Evolutionary Computation, 2010)

Controlling Complex Dynamics with Artificial Biochemical Networks. - Michael A. Lones; Andy M. Tyrrell; Susan Stepney; Leo S. D. Caves (EuroGP, 2010)

Objective Assessment of Visuo-spatial Ability using Implicit Context Representation Cartesian Genetic Programming. - Michael A. Lones; Stephen L. Smith 002 (Genetic and Evolutionary Computation: Medical Applications, 2011)

Controlling legged robots with coupled artificial biochemical networks. - Michael A. Lones; Andy M. Tyrrell; Susan Stepney; Leo S. D. Caves (ECAL, 2011)

Sean Luke: essentials of metaheuristics. - Michael A. Lones (Genet. Program. Evolvable Mach., 2011)

Evolved Artificial Signalling Networks for the Control of a Conservative Complex Dynamical System. - Luis A. Fuente; Michael A. Lones; Alexander P. Turner; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (IPCAT, 2012)

Evolving Computational Dynamical Systems to Recognise Abnormal Human Motor Function. - Michael A. Lones; Stephen L. Smith 002; Andy M. Tyrrell; Jane E. Alty; D. R. Stuart Jamieson (IPCAT, 2012)

Using Artificial Epigenetic Regulatory Networks to Control Complex Tasks within Chaotic Systems. - Alexander P. Turner; Michael A. Lones; Luis A. Fuente; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (IPCAT, 2012)

Adaptive robotic gait control using coupled artificial signalling networks, hopf oscillators and inverse kinematics. - Luis A. Fuente; Michael A. Lones; Alexander P. Turner; Leo S. D. Caves; Susan Stepney; Andy M. Tyrrell (IEEE Congress on Evolutionary Computation, 2013)

Evolving classifiers to inform clinical assessment of Parkinson's disease. - Michael A. Lones; Jane E. Alty; Stuart E. Lacy; D. R. Stuart Jamieson; Katherine L. Possin; Norbert Schuff; Stephen L. Smith 002 (CICARE, 2013)

Characterisation of movement disorder in parkinson's disease using evolutionary algorithms. - Stuart E. Lacy; Michael A. Lones; Stephen L. Smith 002; Jane E. Alty; D. R. Stuart Jamieson; Katherine L. Possin; Norbert Schuff (GECCO (Companion), 2013)

The artificial epigenetic network. - Alexander P. Turner; Michael A. Lones; Luis A. Fuente; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (ICES, 2013)

Computational models of signalling networks for non-linear control. - Luis A. Fuente; Michael A. Lones; Alexander P. Turner; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (Biosyst., 2013)

Characterising neurological time series data using biologically motivated networks of coupled discrete maps. - Michael A. Lones; Stephen L. Smith 002; Andy M. Tyrrell; Jane E. Alty; D. R. Stuart Jamieson (Biosyst., 2013)

The incorporation of epigenetics in artificial gene regulatory networks. - Alexander P. Turner; Michael A. Lones; Luis A. Fuente; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (Biosyst., 2013)

Biochemical connectionism. - Michael A. Lones; Alexander P. Turner; Luis A. Fuente; Susan Stepney; Leo S. D. Caves; Andy M. Tyrrell (Nat. Comput., 2013)

Special issue on the frontiers of natural computing. - Michael A. Lones; Andy M. Tyrrell; Susan Stepney; Leo S. D. Caves (Nat. Comput., 2013)

Metaheuristics in nature-inspired algorithms. - Michael A. Lones (GECCO (Companion), 2014)

Classification and characterisation of movement patterns during levodopa therapy for parkinson's disease. - Michael A. Lones; Jane E. Alty; Philippa Duggan-Carter; Andrew James Turner; D. R. Stuart Jamieson; Stephen L. Smith 002 (GECCO (Companion), 2014)

Artificial Biochemical Networks: Evolving Dynamical Systems to Control Dynamical Systems. - Michael A. Lones; Luis A. Fuente; Alexander P. Turner; Leo S. D. Caves; Susan Stepney; Stephen L. Smith 002; Andy M. Tyrrell (IEEE Trans. Evol. Comput., 2014)

Evolving Classifiers to Recognize the Movement Characteristics of Parkinson's Disease Patients. - Michael A. Lones; Stephen L. Smith 002; Jane E. Alty; Stuart E. Lacy; Katherine L. Possin; D. R. Stuart Jamieson; Andy M. Tyrrell (IEEE Trans. Evol. Comput., 2014)

A comparison of evolved linear and non-linear ensemble vote aggregators. - Stuart E. Lacy; Michael A. Lones; Stephen L. Smith 002 (CEC, 2015)

Forming classifier ensembles with multimodal Evolutionary Algorithms. - Stuart E. Lacy; Michael A. Lones; Stephen L. Smith 002 (CEC, 2015)

Harmonic Versus Chaos Controlled Oscillators in Hexapedal Locomotion. - Luis A. Fuente; Michael A. Lones; Nigel T. Crook; Tjeerd Olde Scheper (IPCAT, 2015)

Evolving Ensembles: What Can We Learn from Biological Mutualisms? - Michael A. Lones; Stuart E. Lacy; Stephen L. Smith 002 (IPCAT, 2015)

Evolving Efficient Solutions to Complex Problems Using the Artificial Epigenetic Network. - Alexander P. Turner; Martin A. Trefzer; Michael A. Lones; Andy M. Tyrrell (IPCAT, 2015)

Medical Applications of Evolvable Hardware. - Michael A. Lones; Stephen L. Smith 002 (Evolvable Hardware, 2015)

Evolving Boolean networks for biological control: State space targeting in scale free Boolean networks. - Nadia S. Taou; David W. Corne; Michael A. Lones (CIBCB, 2016)

Towards Intelligent Biological Control: Controlling Boolean Networks with Boolean Networks. - Nadia S. Taou; David W. Corne; Michael A. Lones (EvoApplications (1), 2016)

A Multi-Objective Approach to Predicting Motor and Cognitive Deficit in Parkinson's Disease Patients. - Marta Vallejo; Jeremy Cosgrove; Jane E. Alty; Stuart Jamieson; Stephen L. Smith 002; David W. Corne; Michael A. Lones (GECCO (Companion), 2016)

Using Multiobjective Evolutionary Algorithms to Understand Parkinson's Disease. - Marta Vallejo; Jeremy Cosgrove; Jane E. Alty; Stephen L. Smith 002; David W. Corne; Michael A. Lones (GECCO (Companion), 2016)

Exploring diagnostic models of Parkinson's disease with multi-objective regression. - Marta Vallejo; Stuart Jamieson; Jeremy Cosgrove; Stephen L. Smith 002; Michael A. Lones; Jane E. Alty; David W. Corne (SSCI, 2016)

Using epigenetic networks for the analysis of movement associated with levodopa therapy for Parkinson's disease. - Alexander P. Turner; Michael A. Lones; Martin A. Trefzer; Stephen L. Smith 002; Stuart Jamieson; Jane E. Alty; Jeremy Cosgrove; Andy M. Tyrrell (Biosyst., 2016)

2015 Information Processing in Cells and Tissues (IPCAT 2015). - Andy M. Tyrrell; Michael A. Lones; Stephen L. Smith 002; Gary B. Fogel (Biosyst., 2016)

Going through directional changes: evolving human movement classifiers using an event based encoding. - Michael A. Lones; Jane E. Alty; Jeremy Cosgrove; Stuart Jamieson; Stephen L. Smith 002 (GECCO (Companion), 2017)

A New Evolutionary Algorithm-Based Home Monitoring Device for Parkinson's Dyskinesia. - Michael A. Lones; Jane E. Alty; Jeremy Cosgrove; Philippa Duggan-Carter; Stuart Jamieson; Rebecca F. Naylor; Andrew James Turner; Stephen L. Smith 002 (J. Medical Syst., 2017)

Artificial Epigenetic Networks: Automatic Decomposition of Dynamical Control Tasks Using Topological Self-Modification. - Alexander P. Turner; Leo S. D. Caves; Susan Stepney; Andy M. Tyrrell; Michael A. Lones (IEEE Trans. Neural Networks Learn. Syst., 2017)

Towards in Vivo Genetic Programming: Evolving Boolean Networks to Determine Cell States. - Nadia S. Taou; Michael A. Lones (EuroGP, 2018)

Using echo state networks for classification: A case study in Parkinson's disease diagnosis. - Stuart E. Lacy; Stephen L. Smith 002; Michael A. Lones (Artif. Intell. Medicine, 2018)

Evolutionary Algorithms. - David W. Corne; Michael A. Lones (CoRR, 2018)

Investigating the use of Boolean networks for the control of gene regulatory networks. - Nadia S. Taou; David W. Corne; Michael A. Lones (J. Comput. Sci., 2018)

Evolutionary Algorithms. - David Corne; Michael A. Lones (Handbook of Heuristics, 2018)

Instruction-level design of local optimisers using push GP. - Michael A. Lones (GECCO (Companion), 2019)

Evolutionary acquisition of complex traits in artificial epigenetic networks. - Alexander P. Turner; Andrew M. Tyrrell; Martin Trefzer; Michael A. Lones (Biosyst., 2019)

Neural-Guided Particle Swarm optimization. - Amani M. Benhalem; Michael A. Lones (CEC, 2020)

Optimising Optimisers with Push GP. - Michael A. Lones (EuroGP, 2020)

Relative Robustness of Quantized Neural Networks Against Adversarial Attacks. - Kirsty Duncan; Ekaterina Komendantskaya; Robert J. Stewart 001; Michael A. Lones (IJCNN, 2020)

Mitigating Metaphors: A Comprehensible Guide to Recent Nature-Inspired Algorithms. - Michael A. Lones (SN Comput. Sci., 2020)

Evaluation of Recurrent Neural Network Models for Parkinson's Disease Classification Using Drawing Data. - Arjun Shenoy A. V; Michael A. Lones; Stephen L. Smith 002; Marta Vallejo (EMBC, 2021)

Anomaly Detection for Insider Threats: An Objective Comparison of Machine Learning Models and Ensembles. - Filip Wieslaw Bartoszewski; Mike Just; Michael A. Lones; Oleksii Mandrychenko (SEC, 2021)

A Data-Driven Biophysical Computational Model of Parkinson's Disease Based on Marmoset Monkeys. - Caetano Mazzoni Ranieri; Jhielson M. Pimentel; Marcelo R. Romano; Leonardo Abdala Elias; Roseli A. F. Romero; Michael A. Lones; Mariana F. P. Araújo; Patrícia A. Vargas; Renan Cipriano Moioli (IEEE Access, 2021)

IoTDevID: A Behaviour-Based Fingerprinting Method for Device Identification in the IoT. - Kahraman Kostas; Mike Just; Michael A. Lones (CoRR, 2021)

How to avoid machine learning pitfalls: a guide for academic researchers. - Michael A. Lones (CoRR, 2021)

Evolving continuous optimisers from scratch. - Michael A. Lones (Genet. Program. Evolvable Mach., 2021)

Optimising Boolean Synthetic Regulatory Networks to Control Cell States. - Nadia S. Taou; Michael A. Lones (IEEE ACM Trans. Comput. Biol. Bioinform., 2021)

The Effect of Manifold Entanglement and Intrinsic Dimensionality on Learning. - Daniel Kienitz; Ekaterina Komendantskaya; Michael A. Lones (AAAI, 2022)

Comparing Complexities of Decision Boundaries for Robust Training: A Universal Approach. - Daniel Kienitz; Ekaterina Komendantskaya; Michael A. Lones (ACCV (6), 2022)

A Review of Capsule Networks in Medical Image Analysis. - Heba El-Shimy; Hind Zantout; Michael A. Lones; Neamat El Gayar (ANNPR, 2022)

Why functional program synthesis matters (in the realm of genetic programming). - Fraser Garrow; Michael A. Lones; Robert J. Stewart 001 (GECCO Companion, 2022)

An in-depth review of machine learning based Android malware detection. - Ali Muzaffar; Hani Ragab Hassen; Michael A. Lones; Hind Zantout (Comput. Secur., 2022)

IoTDevID: A Behavior-Based Device Identification Method for the IoT. - Kahraman Kostas; Mike Just; Michael A. Lones (IEEE Internet Things J., 2022)

Parkinson's disease diagnosis using convolutional neural networks and figure-copying tasks. - Mohamad Alissa; Michael A. Lones; Jeremy Cosgrove; Jane E. Alty; Stuart Jamieson; Stephen L. Smith 002; Marta Vallejo (Neural Comput. Appl., 2022)

A Comprehensive Investigation of Feature and Model Importance in Android Malware Detection. - Ali Muzaffar; Hani Ragab Hassen; Hind Zantout; Michael A. Lones (CoRR, 2023)

Externally validating the IoTDevID device identification methodology using the CIC IoT 2022 Dataset. - Kahraman Kostas; Mike Just; Michael A. Lones (CoRR, 2023)

DroidDissector: A Static and Dynamic Analysis Tool for Android Malware Detection. - Ali Muzaffar; Hani Ragab Hassen; Hind Zantout; Michael A. Lones (CoRR, 2023)

REFORMS: Reporting Standards for Machine Learning Based Science. - Sayash Kapoor; Emily Cantrell; Kenny Peng; Thanh Hien Pham; Christopher A. Bail; Odd Erik Gundersen; Jake M. Hofman; Jessica Hullman; Michael A. Lones; Momin M. Malik; Priyanka Nanayakkara; Russell A. Poldrack; et al. (CoRR, 2023)

Investigating the Proficiency of Large Language Models in Formative Feedback Generation for Student Programmers. - Smitha S. Kumar; Michael Adam Lones; Manuel Maarek; Hind Zantout (LLM4CODE@ICSE, 2024)

ActDroid: An active learning framework for Android malware detection. - Ali Muzaffar; Hani Ragab Hassen; Hind Zantout; Michael A. Lones (CoRR, 2024)

Individual Packet Features are a Risk to Model Generalisation in ML-Based Intrusion Detection. - Kahraman Kostas; Mike Just; Michael A. Lones (CoRR, 2024)

ScaleNet: Scale Invariance Learning in Directed Graphs. - Qin Jiang; Chengjia Wang; Michael Lones; Yingfang Yuan; Wei Pang (CoRR, 2024)

GeMID: Generalizable Models for IoT Device Identification. - Kahraman Kostas; Rabia Yasa Kostas; Mike Just; Michael A. Lones (CoRR, 2024)

Scale Invariance of Graph Neural Networks. - Qin Jiang; Chengjia Wang; Michael Lones; Wei Pang (CoRR, 2024)

Avoiding common machine learning pitfalls. - Michael A. Lones (Patterns, 2024)

IoTGeM: Generalizable models for behaviour-based IoT attack detection. - Kahraman Kostas; Mike Just; Michael A. Lones (Comput. Networks, 2025)

Demystifying MPNNs: Message Passing as Merely Efficient Matrix Multiplication. - Qin Jiang; Chengjia Wang; Michael Lones; Wei Pang (CoRR, 2025)

Self-Supervised Learning for Pre-training Capsule Networks: Overcoming Medical Imaging Dataset Challenges. - Heba El-Shimy; Hind Zantout; Michael A. Lones; Neamat El Gayar (CoRR, 2025)

Individual Packet Features are a Risk to Model Generalization in ML-Based Intrusion Detection. - Kahraman Kostas; Mike Just; Michael A. Lones (IEEE Netw. Lett., 2025)

Navigating Pitfalls: Evaluating LLMs in Machine Learning Programming Education. - Smitha S. Kumar; Michael A. Lones; Manuel Maarek; Hind Zantout (CoRR, 2025)