Prof. Jaume Bacardit
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| Prof. Jaume Bacardit |
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Yiming Huang, Anil Wipat and Jaume Bacardit Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains Biotechnology and Bioengineering 121.1 (2024): 355-365. access to the paper B. Shirt-Ediss, J. Connolly, J. Elezgaray, E. Torelli, S.A. Navarro, J. Bacardit, N. Krasnogor Reverse engineering DNA origami nanostructure designs from raw scaffold and staple sequence lists Computational and Structural Biotechnology Journal, 21(C):3615-3626, 2023 access to the paper Schmidt, L., Mohamed, S., Meader, N., Bacardit, J., & Craig, D. Automated data analysis of unstructured grey literature in health research: A mapping review. Research Synthesis Methods, in press. access to the paper Pawel Widera, Paco MJ Welsing, Samuel O Danso, Sjaak Peelen, Margreet Kloppenburg, Marieke Loef, Anne C Marijnissen, Eefje M van Helvoort, Francisco J Blanco, Joana Magalhães, Francis Berenbaum, Ida K Haugen, Anne-Christine Bay-Jensen, Ali Mobasheri, Christoph Ladel, John Loughlin, Floris PJG Lafeber, Agnès Lalande, Jonathan Larkin, Harrie Weinans, Jaume Bacardit Development and validation of a machine learning-supported strategy of patient selection for osteoarthritis clinical trials Osteoarthritis and Cartilage Open (2023): 100406. access to the paper Sadaf Iqbal, Jaume Bacardit, Bridget Griffiths, John Allen Deep learning classification of systemic sclerosis from multi-site photoplethysmography signals Frontiers in Physiology 14 (2023): 1242807 access to the paper Iqbal, Sadaf, Sharad Agarwal, Ian Purcell, Alan Murray, Jaume Bacardit, and John Allen. Deep learning identification of coronary artery disease from bilateral finger photoplethysmography sensing: A proof-of-concept study. Biomedical Signal Processing and Control 86 (2023): 104993. access to the paper Qiuke Wang, Jos Runhaar, Margreet Kloppenburg, Maarten Boers, Johannes WJ Bijlsma, Jaume Bacardit, Sita MA Bierma-Zeinstra A machine learning approach reveals features related to clinicians¿ diagnosis of clinically relevant knee osteoarthritis Rheumatology 62.8 (2023): 2732-2739 access to the paper Mylène P Jansen, Wolfgang Wirth, Jaume Bacardit, Eefje M van Helvoort, Anne CA Marijnissen, Margreet Kloppenburg, Francisco J Blanco, Ida K Haugen, Francis Berenbaum, Cristoph H Ladel, Marieke Loef, Floris PJG Lafeber, Paco M Welsing, Simon C Mastbergen, Frank W Roemer Machine-learning predicted and actual 2-year structural progression in the IMI-APPROACH cohort Quantitative Imaging in Medicine and Surgery 13.5 (2023): 3298. access to the paper Christian Taylor, Jonathan Guy, Jaume Bacardit Estimating individual-level pig growth trajectories from group-level weight time series using machine learning Computers and Electronics in Agriculture, Volume 208, 2023, access to the paper Yiming Huang, Nishant Sinha, Anil Wipat and Jaume Bacardit A knowledge integration strategy for the selection of a robust multi-stress biomarkers panel for Bacillus subtilis Synthetic and Systems Biotechnology, Volume 8, Issue 1, March 2023, Pages 97-106 access to the paper Sokolovsky, A., Arnaboldi, L., Bacardit, J., and Gross, T. Interpretable trading pattern designed for machine learning applications. Machine Learning with Applications, Volume 11, 15 March 2023, 100448 access to the paper E.M. van Helvoort, M.P. Jansen, A.C.A. Marijnissen, M. Kloppenburg, F.J. Blanco, I.K Haugen, F. Berenbaum, A.C. Bay-Jensen, C. Ladel, A. Lalande, J. Larkin, J. Loughlin, A. Mobasheri, H.H. Weinans, P. Widera, J. Bacardit, P.M.J. Welsing and F.P.J.G. Lafeber Predicted and actual 2-year structural and pain progression in the IMI-APPROACH knee osteoarthritis cohort Rheumatology, Volume 62, Issue 1, January 2023, Pages 147-157 access to the paper W. Wirth, S. Maschek, A.C.A. Marijnissen, A. Lalande, F.J. Blanco, F. Berenbaum, L.A. van de Stadt, M. Kloppenburg, I.K. Haugen, C.H. Ladel, J. Bacardit, A. Wisser, F. Eckstein, F.W. Roemer, F.P.J.G. Lafeber, H.H. Weinans, M. Jansen Test-retest precision and longitudinal cartilage thickness loss in the IMI-APPROACH cohort Osteoarthritis and Cartilage 31 (2), 238-248 access to the paper Frank W. Roemer, Mylène Jansen, Anne C. A. Marijnissen, Ali Guermazi, Rafael Heiss, Susanne Maschek, Agnes Lalande, Francisco J. Blanco, Francis Berenbaum, Lotte A. van de Stadt, Margreet Kloppenburg, Ida K. Haugen, Christoph H. Ladel, Jaume Bacardit, Anna Wisser, Felix Eckstein, Floris P. J. G. Lafeber, Harrie H. Weinans and Wolfgang Wirth Structural tissue damage and 24-month progression of semi-quantitative MRI biomarkers of knee osteoarthritis in the IMI-APPROACH cohort BMC Musculoskeletal Disorders volume 23, Article 988 (2022) access to the paper Hajar Danesh; David H. Steel; Jeffry Hogg; Fereshteh Ashtari; Will Innes; Jaume Bacardit; Anya Hurlbert; Jenny C. A. Read; Rahele Kafieh Synthetic OCT Data Generation to Enhance the Performance of Diagnostic Models for Neurodegenerative Diseases Translational Vision Science & Technology October 2022, Vol.11, 10 access to the paper J. Bacardit, A.E.I. Brownlee, S. Cagnoni, G. Iacca, J. McCall, D. Walker The intersection of evolutionary computation and explainable AI Proceedings of the Genetic and Evolutionary Computation Conference Companion, pp 1757-1762, 2022 access to the paper C. Taylor, J. Guy and J. Bacardit Prediction of growth in grower-finisher pigs using recurrent neural networks Biosystems engineering 2022 v.220 pp. 114-134 access to the papepr F. Angelini, P. Widera, A. Mobasheri, J. Blair, A. Struglics, M. Uebelhoer, Y. Henrotin, A.C. Marijnissen, M. Kloppenburg, F. Blanco, I. Haugen, F. Berenbaum, C. Ladel, J. Larkin, A.C. Bay-Jensen and J. Bacardit Osteoarthritis endotype discovery via clustering of biochemical marker data Annals of the Rheumatic Diseases 81.5 (2022): 666-675. access to the paper D Walker, M Ruane, J Bacardit, S Coleman Insight from data analytics in a facilities management company Quality and Reliability Engineering International 38.3 (2022): 1416-1440 access to the paper P. Darke, S. Cassidy, M. Catt, R. Taylor, P. Missier, and J. Bacardit Curating a longitudinal research resource using linked primary care EHR data -- a UK Biobank case study Journal of the American Medical Informatics Association 29.3 (2022): 546-552. access to the paper B. Little, O. Alshabrawy, D. Stow, I. N. Ferrier, R. McNaney, D. G. Jackson, K. Ladha, C. Ladha, T. Ploetz, J. Bacardit, P. Olivier, P. Gallagher and J. T. O'Brien Deep learning-based automated speech detection as a marker of social functioning in late-life depression Psychological medicine 51 (9), 1441-1450 access to the paper E.M. van Helvoort, C. Ladel, S. Mastbergen, M. Kloppenburg, F.J. Blanco, I.K. Haugen, F. Berenbaum, J. Bacardit, P. Widera, P.M.J. Welsing, F. Lafeber Baseline clinical characteristics of predicted structural and pain progressors in the IMI-APPROACH knee OA cohort RMD open 7 (3), e001759 access to the paper A.D. Rajgor, S. Patel, D. McCulloch, B. Obara, J. Bacardit, A. McQueen, E. Aboagye, T. Ali, J. O'Hara, D.W. Hamilton The application of radiomics in laryngeal cancer The British Journal of Radiology 94, 20210499 access to the paper L. Jardine, S. Webb, I. Goh, M. Quiroga Londoño, . Reynolds, M. Mather, B. Olabi, E. Stephenson, R.A. Botting, D. Horsfall, J. Engelbert,D. Maunder, N. Mende, C. Murnane, E. Dann, J. McGrath, H. King, I. Kucinski, R. Queen, C.D. Carey, C. Shrubsole, E. Poyner, M. Acres, C. Jones, T. Ness, R. Coulthard, N. Elliott, S. O'Byrne, M.LR. Haltalli, J.E. Lawrence, S. Lisgo, P. Balogh, K.B. Meyer, E. Prigmore, K. Ambridge, M.S. Jain, M. Efremova, K. Pickard, T. Creasey, J. Bacardit, D. Henderson, J. Coxhead, A. Filby, R. Hussain, D. Dixon, D. McDonald, D.M. Popescu, M.S. Kowalczyk, B. Li, O. Ashenberg, M. Tabaka, D. Dionne, T.L. Tickle, M. Slyper, O. Rozenblatt-Rosen, A. Regev, S. Behjati, E. Laurenti, N.K. Wilson, A. Roy, B. Göttgens, . Roberts, S.A. Teichmann, M. Haniffa Blood and immune development in human fetal bone marrow and Down syndrome Nature 598 (7880), 327-331 access to the paper E. Stephenson, G. Reynolds, R.A. Botting, F.J. Calero-Nieto, M.D. Morgan, Z.K. Tuong, K. Bach, W. Sungnak, K.B. Worlock, M. Yoshida, N. Kumasaka, K. Kania, J. Engelbert, B. Olabi, J.S. Spegarova, N.K. Wilson, N. Mende, L. Jardine, L.C.S. Gardner, I. Goh, D. Horsfall, J. McGrath, S. Webb, M.W. Mather, R.G.H. Lindeboom, E. Dann, N. Huang, K. Polanski, E. Prigmore, F. Gothe, J. Scott, R.P. Payne, K.F. Baker, A.T. Hanrath, I.C.D.S. van der Loeff, A.S. Barr, A. Sanchez-Gonzalez, L. Bergamaschi, F. Mescia, J.L. Barnes, E. Kilich, A. de Wilton, A. Saigal, A. Saleh, S.M. Janes, C.M. Smith, N. Gopee, C. Wilson, P. Coupland, J.M. Coxhead, V.Y. Kiselev, S. van Dongen, J. Bacardit, H.W. King, A.J. Rostron, A.J. Simpson, S. Hambleton, E. Laurenti, P.A. Lyons, K.B. Meyer, M.Z. Nikolic, C.J.A. Duncan, K.G.C. Smith, S.A. Teichmann, M.R. Clatworthy, J.C. Marioni, B. Göttgens, . Haniffa Single-cell multi-omics analysis of the immune response in COVID-19 Nature medicine 27 (5), 904-916 access to the paper A.C. Hepburn, N. Lazzarini, R. Veeratterapillay, L. Wilson, J. Bacardit, R. Heer Identification of CNGB1 as a Predictor of Response to Neoadjuvant Chemotherapy in Muscle-Invasive Bladder Cancer Cancers 13 (15), 3903 access to the paper A. Sokolovsky, T. Gross, J. Bacardit Is it feasible to detect FLOSS version release events from textual messages? A case study on Stack Overflow PloS one 16 (2), e0246464 access to the paper G. Reynolds, P. Vegh, J. Fletcher, E.F.M. Poyner, E. Stephenson, I. Goh, R.A. Botting, N. Huang, B. Olabi, A. Dubois, D. Dixon, K. Green, D. Maunder, J. Engelbert, M. Efremova, K. Polanski, L. Jardine, C. Jones, T. Ness, D. Horsfall, J. McGrath, C. Carey, D.M. Popescu, S. Webb, X.N. Wang, B. Sayer, J.E. Park, V.A. Negri, D. Belokhvostova, M.D. Lynch, D. McDonald, A. Filby, T. Hagai, K.B. Meyer, A. Husain, J. Coxhead, R. Vento-Tormo, S. Behjati, S. Lisgo, A.C. Villani, J. Bacardit, P.H. Jones, E.A. O'Toole, G.S. Ogg, N. Rajan, N.J. Reynolds, S.A. Teichmann, F.M. Watt, M. Haniffa Developmental cell programs are co-opted in inflammatory skin disease Science 371 (6527) access to the paper Y. Huang, W. Smith, C. Harwood, A. Wipat and J. Bacardit Computational Strategies for the Identification of a Transcriptional Biomarker Panel to Sense Cellular Growth States in Bacillus subtilis Sensors 2021, 21(7), 2436 access to the paper B. Lam, M. Catt, S. Cassidy, J. Bacardit, P. Darke, S. Butterfield, O. Alshabrawy, M. Trenell and P. Missier Using wearable activity trackers to predict type 2 diabetes: machine learning–based cross-sectional study of the UK Biobank accelerometer cohort JMIR diabetes 6.1 (2021): e23364. access to the paper A. Alameer, I. Kyriazakis and J. Bacardit Automated recognition of postures and drinking behaviour for the detection of compromised health in pigs Scientific Reports volume 10, Article number: 13665 (2020) access to the paper Eefje M van Helvoort, Willem E van Spil, Mylène P Janse1, Paco M J Welsing, Margreet Kloppenburgm, Marieke Loef, Francisco J Blanco, Ida K Haugen, Francis Berenbaum, Jaume Bacardit, Christoph H Ladel, John Loughlin, Anne C Bay-Jensen, Ali Mobasheri, Jonathan Larkin, Janneke Boere, Harrie H Weinans, Agnes Lalande, Anne C A Marijnissen and Floris P J G Lafeber 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 BMJ Open 2020;10:e035101. doi: 10.1136/bmjopen-2019-035101 access to the paper Maria A. Franco, Natalio Krasnogor and Jaume Bacardit Automatic Tuning of Rule-Based Evolutionary Machine Learning via Problem Structure Identification IEEE Computational Intelligence Magazine ( Volume: 15 , Issue: 3 , Aug. 2020 ) access to the paper Ali Alameer, Ilias Kyriazakis, Hillary A.Dalton, Amy L.Miller and Jaume Bacardit Automatic recognition of feeding and foraging behaviour in pigs using deep learning Biosystems Engineering, Volume 197, September 2020, Pages 91-104 access to the paper Paweł Widera, Paco M. J. Welsing, Christoph Ladel, John Loughlin, Floris P. F. J. Lafeber, Florence Petit Dop, Jonathan Larkin, Harrie Weinans, Ali Mobasheri and Jaume Bacardit Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data Scientific Reports volume 10, Article number: 8427 (2020) access to the paper Dorin-Mirel Popescu, Rachel A. Botting, Emily Stephenson, Kile Green, Simone Webb, Laura Jardine, Emily F. Calderbank, Krzysztof Polanski, Issac Goh, Mirjana Efremova, Meghan Acres, Daniel Maunder, Peter Vegh, Yorick Gitton, Jong-Eun Park, Roser Vento-Tormo, Zhichao Miao, David Dixon, Rachel Rowell, David McDonald, James Fletcher, Elizabeth Poyner, Gary Reynolds, Michael Mather, Corina Moldovan, Lira Mamanova, Frankie Greig, Matthew D. Young, Kerstin B. Meyer, Steven Lisgo, Jaume Bacardit, Andrew Fuller, Ben Millar, Barbara Innes, Susan Lindsay, Michael J. T. Stubbington, Monika S. Kowalczyk, Bo Li, Orr Ashenberg, Marcin Tabaka, Danielle Dionne, Timothy L. Tickle, Michal Slyper, Orit Rozenblatt-Rosen, Andrew Filby, Peter Carey, Alexandra-Chloé Villani, Anindita Roy, Aviv Regev, Alain Chédotal, Irene Roberts, Berthold Göttgens, Sam Behjati, Elisa Laurenti, Sarah A. Teichmann and Muzlifah Haniffa Decoding human fetal liver haematopoiesis Nature 574:365-371 (2019) access to the paper Wayne S. Smith, Shirley Coleman, Jaume Bacardit and Syd Coxon Insight from data analytics with an automotive aftermarket SME Quality and Reliability Engineering International 35 (5), 1396-1407 access to the paper Jake Cowton, Ilias Kyriazakis and Jaume Bacardit Automated Individual Pig Localisation, Tracking and Behaviour Metric Extraction Using Deep Learning IEEE Access, vol. 7, pp. 108049-108060, 2019 access to the paper Harold Fellermann, Alexandra S Penn, Rudolf M Füchslin, Jaume Bacardit, Angel Goñi-More Towards low-carbon conferencing: Acceptance of virtual conferencing solutions and other sustainability measures in the alife community The 2019 Conference on Artificial Life, Newcastle, United Kingdom, 29 July-2 August 2019, pp. 21-27 access to the manuscript J Cowton, I Kyriazakis, T Ploetz, J Bacardit A Combined Deep Learning GRU-Autoencoder for the Early Detection of Respiratory Disease in Pigs Using Multiple Environmental Sensors Sensors 18(8):2521 access to the paper Keasar, C., McGuffin, L.J., Wallner, B., Chopra, G., Adhikari, B., Bhattacharya, D., Blake, L., Bortot, L. O., Cao, R., Dhanasekaran, B. K., Dimas, I., Faccioli, R.A., Faraggi, E., Ganzynkowicz, R., Ghosh, S., Ghosh, S., Gieldon A., Golon, L., He, Y., Heo, L., Hou, J., Khan, M., Khatib, F., Khoury, G.A., Kieslich, C., Kim, D.E., Krupa, P., Lee, G.R., Li, H., Li, J., Lipska, A., Liwo, A., Maghrabi, A.H.A., Mirdita, M., Mirzaei, S., Mozolewska, M.A., Onel, M., Ovchinnikov, S., Shah, A., Shah, U., Sidi, T., Sieradzan, A.K., Slusarz, M., Slusarz, R., Smadbeck, J., Tamamis, P., Trieber, N., Wirecki, T., Yin, Y., Zhang, Y., Bacardit, J., Baranowski, M., Chapman, N., Cooper, S., Defelicibus, A., Flatten, J., Koepnick, B., Popovic, Z., Zaborowski, B., Baker, D., Cheng, J., Czaplewski, C., Delbem, A.C.B., Floudas, C., Kloczkowski, A., Oldziej, S., Levitt, M., Scheraga, H., Seok, C., Soding, J., Vishveshwara, S., Xu, D., Crivelli, S. An analysis and evaluation of the WeFold collaborative for protein structure prediction and its pipelines in CASP11 and CASP12 Scientific Reports, 8(1), December 2018 access to the paper N. Lazzarini, J. Runhaar, A.C. Bay-Jensen, C.S. Thudium, S.M.A.Bierma-Zeinstra, Y. Henrotin and J.Bacardit A machine learning approach for the identification of new biomarkers for knee osteoarthritis development in overweight and obese women Osteoarthritis and Cartilage, Volume 25, Issue 12, December 2017, Pages 2014-2021 access to the paper N. Lazzarini and J. Bacardit RGIFE: a ranked guided iterative feature elimination heuristic for the identification of biomarkers BMC Bioinformatics 18:322, 2017 access to the paper S. Baron, N. Lazzarini and J. Bacardit Characterising the Influence of Rule-Based Knowledge Representations in Biological Knowledge Extraction from Transcriptomics Data Proceedings of EvoApplications 2017, LNCS 10199, p.125-141, Springer, 2017 access to the paper A Garcia-Piquer, J Bacardit, A Fornells and E Golobardes Scaling-up multiobjective evolutionary clustering algorithms using stratification Pattern Recognition Letters, 93:69-77, 2017 access to the paper N. Lazzarini, P. Widera, S. Williamson, R. Heer, N. Krasnogor and J. Bacardit Functional networks inference from rule-based machine learning models BioData Mining 2016, 9:28 access to the paper P.D. Gutiérrez, M. Lastra, J. Bacardit, J.M. Benítez and F. Herrera GPU-SME-kNN: Scalable and Memory Efficient kNN and Lazy Learning using GPUs Information Sciences, 330:385-402 access to the paper M. Franco, and J. Bacardit Large-scale experimental evaluation of GPU strategies for evolutionary machine learning Information Sciences, 330:385-402 access to the paper F. Eduati et al. Prediction of human population responses to toxic compounds by a collaborative competition Nature Biotechnology, 33,933-940 (2015) access to the paper I. Triguero, S. del Río, V. López, J. Bacardit, J.M. Benítez and F. Herrera ROSEFW-RF: The winner algorithm for the ECBDL'14 big data competition: An extremely imbalanced big data bioinformatics problem Knowledge-Based Systems, (2015) 87:69-79 access to the paper A.L. Swan, D.J. Stekel, C. Hodgman, D. Allaway, M.H Alqahtani, A. Mobasheri and J. Bacardit A machine learning heuristic to identify biologically relevant and minimal biomarker panels from omics data BMC Genomics 2015, 16(Suppl 1):S2 access to the paper I. Triguero, D. Peralta, J. Bacardit, S. Garcia and F. Herrera MRPR: A MapReduce Solution for Prototype Reduction in Big Data Classification Neurocomputing journal 150(A):331-345 access to the paper María Martínez-Ballesteros, Jaume Bacardit, Alicia Troncoso and José C. Riquelme Enhancing the scalability of a genetic algorithm to discover quantitative association rules in large-scale datasets Integrated Computer-Aided Engineering, 22(1):21-39 access to the paper Alkurashi MM, May ST, Kong K, Bacardit J, Haig D, Elsheikha HM. Susceptibility to experimental infection of the invertebrate locusts (Schistocerca gregaria) with the apicomplexan parasite Neospora caninum. PeerJ 2:e674 access to the paper J. Bacardit, P. Widera, N. Lazzarini and N. Krasnogor Hard Data Analytics Problems Make for Better Data Analysis Algorithms: Bioinformatics as an Example Big Data Journal, 2(3):164-176, September 2014 access to the paper D.J. Gibbs, J. Bacardit, A. Bachmair, and M.J. Holdsworth The eukaryotic N-end rule pathway: conserved mechanisms and diverse functions Trends in Cell Biology, 24(10):603-611 access to the paper I. Triguero, D. Peralta, J. Bacardit, S. Garcia and F. Herrera A Combined MapReduce-Windowing Two-Level Parallel Scheme for Evolutionary Prototype Generation Proceedings of the IEEE World Congress on Computational Intelligence 2014, pp. 3036--3043 access to the paper J. Blakes, O. Raz, U. Feige, J. Bacardit, P. Widera, T. Ben-Yehezkel, E. Shapiro and N. Krasnogor A heuristic for maximizing DNA reuse in synthetic DNA library assembly ACS synthetic biology 3 (8), 529-542 access to the paper G.A Khoury, A. Liwo, F. Khatib, H. Zhou, G. Chopra, J. Bacardit, L. Bortot, R.A. Faccioli, X. Deng, Y. He, P. Krupa, J. Li, M.A. Mozolewska, A.K. Sieradzan, J. Smadbeck, T. Wirecki, S. Cooper, J. Flatten, K. Xu, D. Baker, J. Cheng, A.C.B. Delbem, C.A. Floudas, C. Keasar, M. Levitt, Z. Popovic, H.A. Scheraga, J. Skolnick, S.N. Crivelli and Foldit Players WeFold: A Coopetition for Protein Structure Prediction PROTEINS: Structure, Function, and Bioinformatics 82(9):1850-1868, 2014 access to the paper A. Garcia-Piquer, A. Fornells, J. Bacardit, A. Orriols-Puig and E. Golobardes Large-Scale Experimental Evaluation of Cluster Representations for Multiobjective Evolutionary Clustering IEEE Transactions on Evolutionary Computation, 18(1):36-53, 2014 access to the paper A.L. Swan, K.L. Hillier, J.R. Smith, D. Allaway, S. Liddell, J. Bacardit and A. Mobasheri 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 BMC Musculoskeletal Disorders, 14:349, 2013 access to the paper A.L. Swan, A. Mobasheri,D. Allaway, S. Liddell and J. Bacardit Application of Machine Learning to Proteomics Data: Classification and Biomarker Identification in Postgenomics Biology OMICS: A Journal of Integrative Biology, 17(12): 595-610, 2013 (Please note, this journal has nothing to do with the Omics Publishing Group) access to the paper M. Franco, N. Krasnogor and J. Bacardit GAssist vs. BioHEL: Critical Assessment of Two Paradigms of Genetics-based Machine Learning Soft Computing, 17(6):953-981, June 2013 access to the paper D.A. Calian and J. Bacardit Integrating memetic search into the BioHEL evolutionary learning system for large-scale datasets Memetic Computing, 5(2):95-130, June 2013 access to the paper J. Bacardit and X. Llorà Large-scale data mining using genetics-based machine learning WIREs Data Mining and Knowledge Discovery 2013, 3: 37-61 doi: 10.1002/widm.1078 eprint access to the paper H.P. Fainberg, K. Bodley, J. Bacardit, D. Li, F. Wessely, N.P. Mongan, M.E. Symonds, L. Clarke and A. Mostyn Reduced Neonatal Mortality in Meishan Piglets: A Role for Hepatic Fatty Acids? PLoS ONE 7(11):e49101. doi:10.1371/journal.pone.0049101 access to the paper J. Bacardit, P. Widera, A. Márquez-Chamorro, F. Divina, J.S. Aguilar-Ruiz and Natalio Krasnogor Contact map prediction using a large-scale ensemble of rule sets and the fusion of multiple predicted structural features Bioinformatics (2012) 28 (19): 2441-2448. doi:10.1093/bioinformatics/bts472 access to the paper E. Glaab, J. Bacardit, J.M. Garibaldi and N. Krasnogor Using Rule-Based Machine Learning for Candidate Disease Gene Prioritization and Sample Classification of Cancer Gene Expression Data PLoS ONE 7(7):e39932. 2012. doi:10.1371/journal.pone.0039932 access to the paper Analysing BioHEL using challenging boolean functions M. Franco, N. Krasnogor and J. Bacardit Evolutionary Intelligence, 5(2):87-102, June 2012 access to the paper Post-processing Operators for Decision Lists M. Franco, N. Krasnogor and J. Bacardit In Proceedings of the 14th Annual Conference on Genetic and Evolutionary Computation - GECCO2012, pages 847-854. ACM, 2012 access to the paper Functional Network Construction in Arabidopsis Using Rule-Based Machine Learning on Large-Scale Data Sets George W. Bassel, Enrico Glaab, Julietta Marquez, Michael J. Holdsworth and Jaume Bacardit The Plant Cell, 23(9):3101-3116, 2011 access to the paper
Modelling the Initialisation Stage of the ALKR Representation for Discrete Domains and GABIL Encoding M. Franco, N. Krasnogor and J. Bacardit In Proceedings of the 13th Annual Conference on Genetic and Evolutionary Computation - GECCO2011, pages 1291-1298. ACM, 2011 Best Paper Award of the GBML track access to the paper Evolutionary symbolic discovery for bioinformatics, systems and synthetic biology. P. Widera, J. Bacardit, N. Krasnogor, C. Garcia-Martinez, and M. Lozano. In GECCO '10: Proceedings of the 12th annual conference comp on Genetic and evolutionary computation, pages 1991-1998. ACM, 2010 access to the paper Analysing BioHEL Using Challenging Boolean Functions M. Franco, N. Krasnogor and J. Bacardit 13th International Workshop on Learning Classifier Systems - IWLCS 2010 In GECCO '10: Proceedings of the 12th annual conference comp on Genetic and evolutionary computation, pages 1855-1862. ACM, 2010 access to the paper Speeding Up the Evaluation of Evolutionary Learning Systems using GPGPUs M. Franco, N. Krasnogor and J. Bacardit In Proceedings of the 12th Annual Conference on Genetic and Evolutionary Computation (GECCO2010), 1039-1046, ACM Press, 2010 Best Paper Award of the GBML track access to the paper A learning classifier system with mutual-information-based fitness R.E. Smith, M.K. Jiang, J. Bacardit, M. Stout, N. Krasnogor and J.D. Hirst Evolutionary Intelligence, 3(1):31-50, 2010 access to the paper Bacardit, J. and Krasnogor, N. A Mixed Discrete-Continuous Attribute List Representation for Large Scale Classification Domains In Proceedings of the 11th Annual Conference on Genetic and Evolutionary Computation (GECCO2009), pp. 1155-1162, ACM Press, 2009 p1155-bacardit.pdf J. Bacardit, M. Stout, J.D. Hirst, A. Valencia, R.E. Smith and N. Krasnogor Automated Alphabet Reduction for Protein Datasets BMC Bioinformatics 10:6, 2009 Access to the paper J. Bacardit, E.K. Burke and N. Krasnogor Improving the scalability of rule-based evolutionary learning Memetic Computing journal 1(1):55-67, 2009 paperAttListKR.pdf J. Bacardit and N. Krasnogor Performance and Efficiency of Memetic Pittsburgh Learning Classifier Systems Evolutionary Computation Journal, 17(3):307-342, 2009 paperMPLCS.pdf Stout, M., Bacardit, J., Hirst, J.D., Smith, R.E. and Krasnogor, N. Prediction of Topological Contacts in Proteins Using Learning Classifier Systems Soft Computing Journal, 13(3):245-258, 2009 Access to the paper Alcalá-Fdez, J., Sánchez, L., García S., del Jesus, M.J., Ventura, S., Garrell, J.M., Otera, J., Romero, C., Bacardit, J., Rivas, V.M., Fernández, J.C. and Herrera, F. KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems Soft Computing Journal, 13(3):307-318, 2009. Access to the paper
J. Bacardit, E. Bernaó-Mansilla, and M.V. Butz Learning Classifier Systems: Looking Back and Glimsing Ahead Learning Classifier Systems. 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Paper, LNAI 4998, pp. 1-21, 2008, Springer LCS-Looking-Glimsing.pdf J. Bacardit and N. Krasnogor Empirical evaluation of ensemble techniques for a Pittsburgh Learning Classifier System Learning Classifier Systems. 10th International Workshop, IWLCS 2006, Seattle, MA, USA, July 8, 2006, and 11th International Workshop, IWLCS 2007, London, UK, July 8, 2007, Revised Selected Paper, LNAI 4998, pp. 255-268, 2008, Springer EnsemblesLCSbook.pdf M. Tabacman, N. Krasnogor, J. Bacardit and I. Loiseau Learning classifier systems for optimization problems: A case study on the fractal travelling salesman problem Eleventh International Workshop on Learning Classifier Systems, IWLCS2008 iwlcs2008.pdf Bacardit, J. and Krasnogor, N. Fast Rule Representation for Continuous Attributes in Genetics-Based Machine Learning In Proceedings of the 10th Annual Conference on Genetic and Evolutionary Computation (GECCO2008), pp. 1421-1422, ACM Press, 2008 gecco2008.pdf Stout, M., Bacardit, J., Hirst, J.D. and Krasnogor, N. Prediction of Recursive Convex Hull Class Assignments for Protein Residues Bioinformatics, 24(7):916-923, 2008 Access to paper J. Bacardit, M. Stout, J.D. Hirst and N. Krasnogor Data Mining in Proteomics with Learning Classifier Systems Bull, L., Bernado Mansilla, E. and Holmes, J. (eds), Learning Classifier Systems in Data Mining, pages 17-46, Springer, 2008 DataMiningLCS.pdf Bacardit, J. and Butz, M.V. Data Mining in Learning Classifier Systems: Comparing XCS with GAssist Learning Classifier Systems, Revised Selected Papers of the International Workshop on Learning Classifier Systems 2003-2005, Lecture Notes in Computer Science 4399, pp. 282-290, 2007, Springer bacardit07data.pdf Bacardit, J., Goldberg D.E. and Butz, M.V. Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule Learning Classifier Systems, Revised Selected Papers of the International Workshop on Learning Classifier Systems 2003-2005, Lecture Notes in Computer Science 4399, pp. 291-307, 2007, Springer bacardit07improving.pdf Bacardit, J. and Garrell, J.M. Bloat control and generalization pressure using the minimum description length principle for a Pittsburgh approach Learning Classifier System Learning Classifier Systems, Revised Selected Papers of the International Workshop on Learning Classifier Systems 2003-2005, Lecture Notes in Computer Science 4399, pp. 59-79, 2007, Springer bacardit07bloat.pdf J. Bacardit, M. Stout, J.D. Hirst, K. Sastry, X. Llorà and N. Krasnogor Automated Alphabet Reduction Method with Evolutionary Algorithms for Protein Structure Prediction In Proceedings of the 9th Annual Conference on Genetic and Evolutionary Computation (GECCO2007), pp. 346-353, ACM Press, 2007 gecco2007-ar.pdf J. Bacardit and N. Krasnogor Empirical evaluation of ensemble techniques for a Pittsburgh Learning Classifier System Ninth International Workshop on Learning Classifier Systems, IWLCS2006 iwlcs2006.pdf J. Bacardit and N. Krasnogor Smart Crossover operator with multiple parents for a Pittsburgh Learning Classifier System Genetic and Evolutionary Computation Conference 2006, GECCO'06 In Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (GECCO2006), pp. 1441 - 1448, ACM Press, 2006 gecco2006-sx.pdf J. Bacardit, M. Stout, J.D. Hirst, N. Krasnogor and J. Blazewicz Coordination number prediction using Learning Classifier Systems: Performance and interpretability In Proceedings of the 8th Annual Conference on Genetic and Evolutionary Computation (GECCO2006), pp. 247-254, ACM Press, 2006 gecco2006-cn.pdf M. Stout, J. Bacardit, J.D. Hirst, N. Krasnogor and J. Blazewicz From HP Lattice Models to Real Proteins: coordination number prediction using Learning Classifier Systems 4th European Workshop on Evolutionary Computation and Machine Learning in Bioinformatics 2006 Lecture Notes in Computer Science vol. 3907, pp. 208-220, Springer, 2006 evobio2006.pdf M. Stout, J. Bacardit, J.D. Hirst, J. Blazewicz and N. Krasnogor Prediction of Residue Exposure and Contact Number for Simplified HP Lattice Model Proteins Using Learning Classifier Systems In D. a. Ruan, P. D'hondt, P. F. Fantoni, M. D. Cock, M. Nachtegael and E. E. Kerre, eds., 7th International FLINS Conference on Applied Artificial Intelligence,, World Scientific, 2006, pp. 601-608. CIBB2006.pdf Jaume Bacardit Analysis of the Initialization Stage of a Pittsburgh Approach Learning Classifier System Genetic and Evolutionary Computation Conference 2005, GECCO'05 gecco2005.pdf Jaume Bacardit Pittsburgh Genetics-Based Machine Learning in the Data Mining era: Representations, generalization, and run-time Doctoral disertation, Ramon Llull University, Barcelona, Catalonia, Spain thesis.pdf Jaume Bacardit, David E. Goldberg, Martin V. Butz, Xavier Llorà and Josep M. Garrell Speeding-up Pittsburgh Learning Classifier Systems: Modeling Time and Accuracy 8th International Conference on Parallel Problem Solving from Nature - PPSN VIII ppsn04.pdf Jaume Bacardit and Martin V. Butz Data Mining in Learning Classifier Systems: Comparing XCS with GAssist Seventh International Workshop on Learning Classifier Systems (IWLCS-2004) iwlcs2004b.ps.gz Jaume Bacardit, David E. Goldberg and Martin V. Butz Improving the Performance of a Pittsburgh Learning Classifier System Using a Default Rule Seventh International Workshop on Learning Classifier Systems (IWLCS-2004) iwlcs2004.ps.gz Jaume Bacardit and Josep M. Garrell Analysis and improvements of the Adaptive Discretization Intervals knowledge representation Genetic and Evolutionary Computation Conference 2004, GECCO'04 gecco2004.ps.gz Jesus Aguilar--Ruiz, Jaume Bacardit and Federico Divina Experimental Evaluation of Discretization Schemes for Rule Induction Genetic and Evolutionary Computation Conference 2004, GECCO'04 gecco2004b.ps.gz Jaume Bacardit, Josep M. Garrell and Pere Miralles Combinando multiples discretizadores para aprendizaje de reglas evolutivo con enfoque de Pittsburgh Proceedings of the "Tercer Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados", pages 192-202 maeb04.ps.gz Teixidó, M., Belda, I., Rosell&ocaute;, X., Gonzàlez, S., Fabre, M., Llorà, X., Bacardit, J., Garrell, J.M., Vilaró, S., Albericio, F., and Giralt, E. Development of a Genetic Algorithm to Design and Identify Peptides that can Cross the Blood-Brain Barrier: Design and validation in silico Journal of QSAR and Combinatorial Science. Vol. 22, No. 7, pp. 745--753, Wiley-VCH. Jaume Bacardit and Josep M. Garrell Comparison of training set reduction techniques for Pittsburgh approach Genetic Classifier Systems X Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA2003) caepia2003.ps.gz Jaume Bacardit and Josep M. Garrell Bloat control and generalization pressure using the minimum description length principle for a Pittsburgh approach Learning Classifier System Sixth International Workshop on Learning Classifier Systems (IWLCS-2003) Chicago, July 2003 iwlcs03.ps.gz Jaume Bacardit and Josep M. Garrell Evolving multiple discretizations with adaptive intervals for a Pittsburgh Rule-Based Learning Classifier System Genetic and Evolutionary Computation Conference 2003, GECCO'03 Lecture Notes in Computer Science 2724, pages 1818--1831, Springer-Verlag gecco03.ps.gz Jaume Bacardit and Josep M. Garrell Incremental Learning for Pittsburgh Approach Classifier Systems Proceedings of the "Segundo Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados", pages 303-311 maeb03.ps.gz Jaume Bacardit and Josep M. Garrell Evolution of Multi-Adaptive Discretization Intervals for a Rule-Based Genetic Learning System Proceedings of the 7th Iberoamerican Conference on Artificial Intelligence (IBERAMIA2002) LNAI vol. 2527, pages 350-360, Springer iberamia02.ps.gz Jaume Bacardit and Josep M. Garrell The role of interval initialization in a GBML system with rule representation and adaptive discrete intervals Proceedings of the 5th Catalan Conference on Artificial Intelligence (CCIA'2002) LNAI vol. 2504, pages 184-195, Springer ccia2002.ps.gz Jaume Bacardit and Josep M. Garrell Evolution of Adaptive Discretization Intervals for a Rule-Based Genetic Learning System Proceedings of the 4th Genetic and Evolutionary Computation converence (GECCO-2002) page 677 (poster page) gecco2002_abstract_page.ps.gz Jaume Bacardit and Josep M. Garrell Métodos de generalización para sistemas clasificadores de Pittsburgh Proceedings of the "Primer Congreso Español de Algoritmos Evolutivos y Bioinspirados (AEB'02)", pages 486-493 aeb02_bacardit+garrell.ps.gz(spanish) |
