J. Bacardit

发表

Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data

Jonathan M. Garibaldi, Jaume Bacardit, Natalio Krasnogor, 2012, PloS one.

Application of machine learning to proteomics data: classification and biomarker identification in postgenomics biology.

A. Mobasheri, J. Bacardit, A. Swan, 2013, Omics : a journal of integrative biology.

Automated Alphabet Reduction for Protein Datasets

Alfonso Valencia, Jaume Bacardit, Natalio Krasnogor, 2009, BMC Bioinformatics.

BioHEL: Bioinformatics-oriented Hierarchical Evolutionary Learning

Jaume Bacardit, Natalio Krasnogor, J. Bacardit, 2006 .

Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule

Martin V. Butz, David E. Goldberg, Jaume Bacardit, 2005, IWLCS.

WeFold: A coopetition for protein structure prediction

Adam Liwo, Yi He, David Baker, 2014, Proteins.

Deep learning-based automated speech detection as a marker of social functioning in late-life depression

Ossama S. Alshabrawy, I. Ferrier, J. O'Brien, 2020, Psychological Medicine.

A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data

D. Stekel, A. Mobasheri, J. Bacardit, 2015, BMC Genomics.

Online Adaptation in Learning Classifier Systems : Stream Data Mining

H. Abbass, Martin Volker Butz, J. Bacardit, 2004 .

Volume-Centred Range Bars: Novel Interpretable Representation of Financial Markets Designed for Machine Learning Applications

J. Bacardit, A. Sokolovsky, Luca Arnaboldi, 2021, 2103.12419.

Developmental cell programs are co-opted in inflammatory skin disease

S. Teichmann, A. Villani, S. Behjati, 2021, Science.

Analysis of the initialization stage of a Pittsburgh approach learning classifier system

J. Bacardit, 2005, GECCO '05.

GECCO ’14: Proceedings of the 2014 conference on Genetic and evolutionary computation

Julian Togelius, Christine Zarges, Hitoshi Iba, 2014 .

The intersection of evolutionary computation and explainable AI

J. Bacardit, J. McCall, S. Cagnoni, 2022, GECCO Companion.

A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors

Jaume Bacardit, Ilias Kyriazakis, Thomas Plötz, 2018, Sensors.

Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer

J. Bacardit, R. Heer, R. Veeratterapillay, 2021, Cancers.

Stratification of amyotrophic lateral sclerosis patients: a crowdsourcing approach

Jung-Hsien Chiang, Devin C. Koestler, Celine Vens, 2018, bioRxiv.

Poised cell circuits in human skin are activated in disease

S. Teichmann, A. Villani, S. Behjati, 2020, bioRxiv.

Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases

A. Hurlbert, R. Kafieh, J. Bacardit, 2022, Translational vision science & technology.

The 2019 Conference on Artificial Life

Jaume Bacardit, Rudolf Marcel Füchslin, Harold Fellermann, 2019, The 2019 Conference on Artificial Life.

Curating a longitudinal research resource using linked primary care EHR data—a UK Biobank case study

P. Missier, M. Catt, J. Bacardit, 2021, J. Am. Medical Informatics Assoc..

Susceptibility to experimental infection of the invertebrate locusts (Schistocerca gregaria) with the apicomplexan parasite Neospora caninum

J. Bacardit, S. May, K. Kong, 2014, PeerJ.

Analysing BioHEL using challenging boolean functions

J. Bacardit, N. Krasnogor, María A. Franco, 2012, Evolutionary Intelligence.

KEEL: a software tool to assess evolutionary algorithms for data mining problems

María José del Jesús, Jesús Alcalá-Fdez, Francisco Herrera, 2008, Soft Comput..

Using Wearable Activity Trackers to Predict Type 2 Diabetes: Machine Learning–Based Cross-sectional Study of the UK Biobank Accelerometer Cohort

Ossama S. Alshabrawy, P. Missier, M. Catt, 2020, JMIR diabetes.

Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering

Alvaro Garcia-Piquer, Jaume Bacardit, Albert Fornells, 2014, IEEE Transactions on Evolutionary Computation.

Improving the scalability of rule-based evolutionary learning

Edmund K. Burke, Jaume Bacardit, Natalio Krasnogor, 2009, Memetic Comput..

t-SNE transformation: a normalization method for local features of single-cell RNA-seq data

Jaume Bacardit, An Chengrui, Zhang Nijia, 2019, bioRxiv.

Decoding human fetal liver haematopoiesis

David McDonald, Kerstin B. Meyer, Jaume Bacardit, 2019, Nature.

Single-cell multi-omics analysis of the immune response in COVID-19

Frances E. Muldoon, Nicola K. Wilson, Kenneth G. C. Smith, 2021, Nature Medicine.

Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis

Jaume Bacardit, Anil Wipat, Wendy Smith, 2021, Sensors.

Decoding the development of the blood and immune systems during human fetal liver haematopoiesis

Jaume Bacardit, Sarah A. Teichmann, Berthold Göttgens, 2019, bioRxiv.

Prediction of topological contacts in proteins using learning classifier systems

Jaume Bacardit, Natalio Krasnogor, Jonathan D. Hirst, 2008, Soft Comput..

Prediction of recursive convex hull class assignments for protein residues

Jaume Bacardit, Natalio Krasnogor, Jonathan D. Hirst, 2008, Bioinform..

Data Mining in Proteomics with Learning Classifier Systems

Jaume Bacardit, Natalio Krasnogor, Jonathan D. Hirst, 2008, Learning Classifier Systems in Data Mining.

Automated alphabet reduction method with evolutionary algorithms for protein structure prediction

Xavier Llorà, Kumara Sastry, Jaume Bacardit, 2007, GECCO '07.

Coordination number prediction using learning classifier systems: performance and interpretability

Jacek Blazewicz, Jaume Bacardit, Natalio Krasnogor, 2006, GECCO '06.

Prediction of human population responses to toxic compounds by a collaborative competition

Ana L. Teixeira, Eleni G. Christodoulou, Jeffrey T. Chang, 2015, Nature Biotechnology.

Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets

Alicia Troncoso Lora, José Cristóbal Riquelme Santos, Jaume Bacardit, 2015, Integr. Comput. Aided Eng..

Blood and immune development in human fetal bone marrow and Down syndrome

Monika S. Kowalczyk, Timothy L. Tickle, A. Regev, 2021, Nature.

Osteoarthritis endotype discovery via clustering of biochemical marker data

A. Mobasheri, J. Bacardit, F. Berenbaum, 2022, Annals of the Rheumatic Diseases.

Intrinsic and extrinsic regulation of human fetal bone marrow haematopoiesis and perturbations in Down syndrome

Monika S. Kowalczyk, Timothy L. Tickle, A. Regev, 2021, bioRxiv.

The eukaryotic N-end rule pathway: conserved mechanisms and diverse functions.

J. Bacardit, D. Gibbs, M. Holdsworth, 2014, Trends in cell biology.

Reduced Neonatal Mortality in Meishan Piglets: A Role for Hepatic Fatty Acids?

Jaume Bacardit, Michael E. Symonds, Frank Wessely, 2012, PloS one.

RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers

Jaume Bacardit, Nicola Lazzarini, J. Bacardit, 2017, BMC Bioinformatics.

Characterising the Influence of Rule-Based Knowledge Representations in Biological Knowledge Extraction from Transcriptomics Data

Jaume Bacardit, Simon Baron, Nicola Lazzarini, 2017, EvoApplications.

Functional networks inference from rule-based machine learning models

Jaume Bacardit, Natalio Krasnogor, Pawel Widera, 2016, BioData Mining.

Automatic recognition of feeding and foraging behaviour in pigs using deep learning

Jaume Bacardit, Ilias Kyriazakis, Ali Alameer, 2020, Biosystems Engineering.

Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs

Jaume Bacardit, Ilias Kyriazakis, Ali Alameer, 2020, Scientific Reports.

Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort

J. Bacardit, F. Berenbaum, P. Welsing, 2021, RMD Open.

Cohort profile: The Applied Public-Private Research enabling OsteoArthritis Clinical Headway (IMI-APPROACH) study: a 2-year, European, cohort study to describe, validate and predict phenotypes of osteoarthritis using clinical, imaging and biochemical markers

A. Mobasheri, J. Bacardit, H. Weinans, 2020, BMJ Open.

An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12

Adam Liwo, Yi He, Jilong Li, 2018, Scientific Reports.

Analysis of mass spectrometry data from the secretome of an explant model of articular cartilage exposed to pro-inflammatory and anti-inflammatory stimuli using machine learning

Jaume Bacardit, Ali Mobasheri, Anna L Swan, 2013, BMC Musculoskeletal Disorders.

Insight from data analytics in a facilities management company

Jaume Bacardit, Shirley Coleman, Daniel Walker, 2021, Qual. Reliab. Eng. Int..

Explainable Machine Learning-driven Strategy for Automated Trading Pattern Extraction A Case Study of CME Futures

Jaume Bacardit, Thomas Gross, Luca Arnaboldi, 2021 .

Transcriptional Biomarker Discovery Towards Building A Load Stress Reporting System for Engineered Escherichia coli Strains

J. Bacardit, A. Wipat, Yiming Huang, 2023, bioRxiv.

Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning

Jaume Bacardit, Ilias Kyriazakis, Jake Cowton, 2019, IEEE Access.

Learning Classifier Systems: Looking Back and Glimpsing Ahead

Martin V. Butz, Jaume Bacardit, Ester Bernadó-Mansilla, 2008, IWLCS.

A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women.

S. Bierma-Zeinstra, J. Bacardit, Y. Henrotin, 2017, Osteoarthritis and cartilage.

The application of radiomics in laryngeal cancer.

J. Bacardit, B. Obara, E. Aboagye, 2021, The British journal of radiology.

How data can change the automotive aftermarket

Shirley Coleman, Jaume Bacardit, Wayne S. Smith, 2018 .

Speeding up the evaluation of evolutionary learning systems using GPGPUs

Jaume Bacardit, Natalio Krasnogor, María A. Franco, 2010, GECCO '10.

Reverse Engineering DNA Origami Nanostructure Designs from Raw Scaffold and Staple Sequence Lists

J. Bacardit, N. Krasnogor, J. Elezgaray, 2023, bioRxiv.

MRPR: A MapReduce solution for prototype reduction in big data classification

Francisco Herrera, Salvador García, Jaume Bacardit, 2015, Neurocomputing.

Guest Editorial: Thematic Issue on ‘Metaheuristics for large scale data mining’

Xavier Llorà, Jaume Bacardit, J. Bacardit, 2010, Memetic Comput..

Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets[C][W][OA]

Jaume Bacardit, George W Bassel, Enrico Glaab, 2011, Plant Cell.

Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data

A. Mobasheri, J. Bacardit, H. Weinans, 2019, Scientific Reports.

Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort

A. Mobasheri, J. Bacardit, H. Weinans, 2022, Rheumatology.

Benchmark time series data sets for PyTorch - the torchtime package

P. Missier, J. Bacardit, Philip Darke, 2022, ArXiv.

ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem

Francisco Herrera, Jaume Bacardit, José Manuel Benítez, 2015, Knowl. Based Syst..

GPU-SME-kNN: Scalable and memory efficient kNN and lazy learning using GPUs

Francisco Herrera, Miguel Lastra, Jaume Bacardit, 2016, Inf. Sci..

Large‐scale data mining using genetics‐based machine learning

Xavier Llorà, Jaume Bacardit, J. Bacardit, 2013, GECCO.

Large scale data mining using genetics-based machine learning

Xavier Llorà, Jaume Bacardit, J. Bacardit, 2009, GECCO '09.

A knowledge integration strategy for the selection of a robust multi-stress biomarkers panel for Bacillus subtilis

J. Bacardit, A. Wipat, N. Sinha, 2022, bioRxiv.

Estimating individual-level pig growth trajectories from group-level weight time series using machine learning

J. Bacardit, Christian Taylor, Jonathan Guy, 2023, Computers and Electronics in Agriculture.

Prediction of growth in grower-finisher pigs using recurrent neural networks

J. Bacardit, Jonathan Guy, C. Taylor, 2022, Biosystems Engineering.

Large scale data mining using genetics-based machine learning

Xavier Llorà, Jaume Bacardit, J. Bacardit, 2011, GECCO.

Artificial Life in a Challenged World

Jaume Bacardit, Rudolf Marcel Füchslin, Ángel Goñi Moreno, 2019, Artificial Life Conference Proceedings.

Reverse engineering DNA origami nanostructure designs from raw scaffold and staple sequence lists

J. Bacardit, N. Krasnogor, J. Elezgaray, 2023, bioRxiv.

Heuristic for maximizing DNA reuse in synthetic DNA library assembly.

Uriel Feige, Jaume Bacardit, Natalio Krasnogor, 2014, ACS synthetic biology.

Automatic Tuning of Rule-Based Evolutionary Machine Learning via Problem Structure Identification

Jaume Bacardit, Natalio Krasnogor, Maria A. Franco, 2020, IEEE Computational Intelligence Magazine.

Interpretable trading pattern designed for machine learning applications

J. Bacardit, A. Sokolovsky, Luca Arnaboldi, 2023, Machine Learning with Applications.

Interpretable ML-driven Strategy for Automated Trading Pattern Extraction pdf

Jaume Bacardit, Thomas Gross, Luca Arnaboldi, 2021, ArXiv.

Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example

Jaume Bacardit, Natalio Krasnogor, Paweł Widera, 2014, Big Data.

Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology

Jaume Bacardit, Natalio Krasnogor, Carlos García-Martínez, 2010, GECCO '10.

HARD DATA ANALYTICS PROBLEMS MAKE FOR BETTER DATA ANALYSIS ALGORITHMS: as an Example

Jaume Bacardit, Natalio Krasnogor, Nicola Lazzarini, 2014 .

WeFold: A coopetition for protein structure prediction

George A. Khoury, Adam K. Sieradzan, Tomasz K. Wirecki, 2014, Proteins.

Towards Low-Carbon Conferencing: Acceptance of Virtual Conferencing Solutions and Other Sustainability Measures in the ALIFE Community

Jaume Bacardit, Alexandra S. Penn, Rudolf Marcel Füchslin, 2019, Artificial Life Conference Proceedings.

The 2019 Conference on Artificial Life (full proceedings pdf)

J. Bacardit, R. Füchslin, Ángel Goñi-Moreno, 2019, Artificial Life Conference Proceedings.

Is it feasible to detect FLOSS version release events from textual messages? A case study on Stack Overflow

J. Bacardit, A. Sokolovsky, T. Gross, 2021, PloS one.

2019 Preface

J. Bacardit, R. Füchslin, Ángel Goñi-Moreno, 2019, Artificial Life Conference Proceedings.

Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets[C][W][OA]

E. Glaab, J. Bacardit, G. Bassel, 2011, Plant Cell.

A NSGA-II Algorithm for the Residue-Residue Contact Prediction

Federico Divina, Jesús S. Aguilar-Ruiz, Jaume Bacardit, 2012, EvoBIO.

S0033291719003994jra 1441..1450

Ossama S. Alshabrawy, I. Ferrier, T. Ploetz, 2021 .