PREDICT - Personalized therapy for RhEumatic DIseases via machine learning

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Papers in international journals (23/12)

  1. Carolina Peixoto, Marta B. Lopes, Marta Martins, Luís Costa, and Susana Vinga, TCox: Correlation-Based Regularization Applied to Colorectal Cancer Survival Data, Biomedicines, 8(11):488 (November 2020). URL: https://doi.org/10.3390/biomedicines8110488
  2. Bruno Mera, The product of two independent Su-Schrieffer-Heeger chains yields a two-dimensional Chern insulator, Phys. Rev. B 102 (October 2020), 155150. URL: https://doi.org/10.1103/PhysRevB.102.155150
  3. Nuno M. Rodrigues, Sara Silva and Leonardo Vanneschi, A Study of Generalization and Fitness Landscapes for Neuroevolution, IEEE Access, vol. 8, pp. 108216-108234, (June 2020). URL: https://doi.org/10.1109/ACCESS.2020.3001505
  4. Mariano Lemus, Mariana F. Ramos, Preeti Yadav, Nuno A. Silva, Nelson J. Muga, André Souto, Nikola Paunkovic, Paulo Mateus, Armando N. Pinto, Generation and Distribution of Quantum Oblivious Keys for Secure Multiparty Computation, Applied Sciences 10 (12), 4080, (June 2020). URL: https://doi.org/10.3390/app10124080
  5. Nikola Paunkovic and Marko Vojinovic, Causal orders, quantum circuits and spacetime: distinguishing between definite and superposed causal orders, Quantum 4, 275 (May 2020). URL: https://doi.org/10.22331/q-2020-05-28-275
  6. Serena Di Giorgio, Paulo Mateus and Bruno Mera, Recoverability from direct quantum correlations, Journal of Physics A: Mathematical and Theoretical (April 2020). URL: https://doi.org/10.1088/1751-8121/ab7a52
  7. Bruno Mera, Localization anisotropy and complex geometry in two-dimensional insulators Physical Review B 101 (March 2020): 11518. URL: https://doi.org/10.1103/PhysRevB.101.115128
  8. Marta B. Lopes, Susana Vinga, Tracking intratumoral heterogeneity in glioblastoma via regularized classification of single-cell RNA-Seq data, BMC Bioinformatics 21, 59 (February 2020). URL: https://doi.org/10.1186/s12859-020-3390-4
  9. Pedro Branco, Paulo Mateus, Carlos Salema, André Souto, Using low-density parity check codes to improve McEliece cryptosystem, Information Sciences, 510, 243-255 (February 2020). URL: https://doi.org/10.1016/j.ins.2019.09.030
  10. Jorge Marques da Silva, Andreia Figueiredo, Jorge Cunha, José Eiras-Dias, Sara Silva, Leonardo Vanneschi, Pedro Mariano, Using Rapid Chlorophyll Fluorescence Transients to Classify Vitis Genotypes, Plants 2020, 9, 174 (February 2020). URL: https://doi.org/10.3390/plants9020174
  11. Mariana Gama, Paulo Mateus, André Souto, A Private Quantum Bit String Commitment, Entropy: 22(3), 272, (February 2020). URL: https://doi.org/10.3390/e22030272
  12. Irene Azzali, Leonardo Vanneschi, Illya Bakurov, Sara Silva, Marco Ivaldi, Mario Giacobini, Towards the use of vector based GP to predict physiological time series, Applied Soft Computing, Volume 89, (January 2020), 106097, ISSN 1568-4946. URL: https://doi.org/10.1016/j.asoc.2020.106097
  13. Rita T. Sousa, Sara Silva, Cátia Pesquita, Evolving knowledge graph similarity for supervised learning in complex biomedical domains, BMC Bioinformatics 21(1):6 (January 2020). URL: https://doi.org/10.1186/s12859-019-3296-1
  14. Telma Pereira, Sandra Cardoso, Alexandre de Mendonça, Manuela Guerreiro, Sara C. Madeira, Targeting the uncertainty of predictions at patient-level using an ensemble of classifiers coupled with calibration methods, Venn-ABERS, and Conformal Predictors: A case study in AD, Journal of Biomedical Informatics, 103350 (January 2020). URL: https://doi.org/10.1016/j.jbi.2019.103350
  15. Kishan Rama, Helena Canhão, Alexandra M. Carvalho, Susana Vinga, AliClu - Temporal sequence alignment for clustering longitudinal clinical data, BMC Medical Informatics and Decision Making 19, 289 (December 2019). URL: https://doi.org/10.1186/s12911-019-1013-7
  16. Mariano Lemus, João Beirão, Nikola Paunkovic, Alexandra M. Carvalho, Paulo Mateus Information-theoretical criteria for characterizing the earliness of time-series data, Entropy 2020, 22, 49 (December 2019). URL: https://doi.org/10.3390/e22010049
  17. Luis Muñoz, Leonardo Trujillo, Sara Silva, Transfer learning in constructive induction with Genetic Programming, Genetic Programming and Evolvable Machines (November 2019). URL: https://doi.org/10.1007/s10710-019-09368-y
  18. Francisco Pipa, Nikola Paunkovic, Marko Vojinovic, Entanglement-induced deviation from the geodesic motion in quantum gravity, Journal of Cosmology and Astroparticle Physics, JCAP09, 057-057 (September 2019). URL: https://iopscience.iop.org/article/10.1088/1475-7516/2019/09/057
  19. Serena Di Giorgio, Paulo Mateus, Efficiently Compressible Density Operators Via Entropy Maximization, Proceedings, 12 (39), 1-5 (August2019). URL: https://doi.org/10.3390/proceedings2019012039
  20. Preeti Yadav, Paulo Mateus, Nikola Paunkovic, André Souto, Quantum contract signing with entangled pairs Entropy, 21(9), 821 (August 2019). URL: https://doi.org/10.3390/e21090821
  21. Andrzej Zielezinski, Hani Z. Girgis, Guillaume Bernard, Chris-Andre Leimeister, Kujin Tang, Thomas Dencker, Anna Katharina Lau, Sophie Röhling, Jae Jin Choi, Michael S. Waterman, Matteo Comin, Sung-Hou Kim, Susana Vinga, Jonas S. Almeida, Cheong Xin Chan, Benjamin T. James, Fengzhu Sun, Burkhard Morgenstern, Wojciech M. Karlowski, Benchmarking of alignment-free sequence comparison methods. Genome Biology, 20 (July 2019). URL: https://doi.org/10.1186/s13059-019-1755-7
  22. Marta B. Lopes, Sandar Casimiro, Susana Vinga, Twiner: correlation-based regularization for identifying common cancer gene signatures. BMC Bioinformatics, 20 (June 2019). URL: https://doi.org/10.1186/s12859-019-2937-8
  23. Hugo Loureiro, Eunice Carrasquinha, Irina Alho, Arlindo R. Ferreira, Luís Costa, Alexandra M. Carvalho, Susana Vinga, Modelling cancer outcomes of bone metastatic patients: combining survival data with N-Telopeptide of type I collagen (NTX) dynamics through joint models, BMC Medical Informatics and Decision Making 19(1): 13:1-13:12 (January 2019). URL: https://doi.org/10.1186/s12911-018-0728-1

Communications in international scientific meetings (23/10)

  1. André Ferreira, Susana Vinga, Alexandra M. Carvalho, Predictive Medicine Using Interpretable Recurrent Neural Networks, International Worshop on Artificial Intelligence for Healthcare Applications (AIHA'20), accepted
  2. Joana Godinho, Alexandra M. Carvalho, Susana Vinga, Latent variable modelling and variational inference for scRNA-seq differential expression analysis, International Conference on Computational Advances in Bio and medical Sciences (ICCABS'20), accepted
  3. Andreia S. Martins, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira, Learning Prognostic Models using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis, ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD'20), accepted
  4. R. Ribeiro, L. Castro, T. Henriques, A. Teixeira, A. Souto, L. Antunes, C. Santos, The Entropy Universe, In Entropy 2020: The Scientific Tool of the 21st Century's, MDPI, accepted
  5. A. Teixeira, L. Antunes, A. Souto, Conditional Tsallis entropy, In Entropy 2020: The Scientific Tool of the 21st Century's, MDPI, accepted
  6. Cláudia Constantino, Alexandra M. Carvalho, Susana Vinga, Sparse consensus classification for discovering novel biomarkers in rheumatoid arthritis, In Nicosia G. et al. (eds), Machine Learning, Optimization, and Data Science. LOD 2020, Revised Selected Papers. Lecture Notes in Computer Science, vol 12565 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-64583-0_13
  7. Eunice Carrasquinha, André Veríssimo, Marta B. Lopes, Susana Vinga, Network-Based Variable Selection for Survival Outcomes in Oncological Data, In Rojas I., Valenzuela O., Rojas F., Herrera L., Ortuno F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science, vol 12108 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-45385-5_49
  8. Inês Diegues, Susana Vinga, Marta B. Lopes, Identification of Common Gene Signatures in Microarray and RNA-Sequencing Data Using Network-Based Regularization, In Rojas I., Valenzuela O., Rojas F., Herrera L., Ortuno F. (eds) Bioinformatics and Biomedical Engineering. IWBBIO 2020. Lecture Notes in Computer Science, vol 12108 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-45385-5_2
  9. André Veríssimo, Marta B. Lopes, Eunice Carrasquinha, Susana Vinga, Random Sample Consensus for the Robust Identification of Outliers in Cancer Data, In Cazzaniga P., Besozzi D., Merelli I., Manzoni L. (eds) Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019. Lecture Notes in Computer Science, vol 12313 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-63061-4_11
  10. Uriel López, Leonardo Trujillo, Sara Silva, Leonardo Vanneschi, and Pierrick Legrand, Unlabeled multi-target regression with genetic programming, In Proceedings of the 2020 Genetic and Evolutionary Computation Conference (GECCO'20). Association for Computing Machinery, New York, NY, USA, 976-984. URL: https://doi.org/10.1145/3377930.3389846
  11. N. M. Rodrigues, Sara Silva and Leonardo Vanneschi, A Study of Fitness Landscapes for Neuroevolution, 2020 IEEE Congress on Evolutionary Computation (CEC), Glasgow, United Kingdom, 2020, pp. 1-8. URL: https://doi.org/10.1109/CEC48606.2020.9185783
  12. João E. Batista and Sara Silva, Improving the Detection of Burnt Areas in Remote Sensing using Hyper-features Evolved by M3GP, 2020 IEEE Congress on Evolutionary Computation (CEC), Glasgow, United Kingdom, 2020, pp. 1-8. URL: https://doi.org/10.1109/CEC48606.2020.9185630
  13. Nuno M. Rodrigues, João E. Batista, Sara Silva, Ensemble Genetic Programming, In Hu T., Lourenço N., Medvet E., Divina F. (eds), Genetic Programming. EuroGP 2020. Lecture Notes in Computer Science, vol 12101 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-44094-7_10
  14. Leornardo Vanneschi, Mauro Castelli, Luca Manzoni, Sara Silva, Leonardo Trujillo, Is k Nearest Neighbours Regression Better than GP?, In Hu T., Lourenço N., Medvet E., Divina F. (eds), Genetic Programming. EuroGP 2020. Lecture Notes in Computer Science, vol 12101 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-44094-7_16
  15. Manuel Anacleto, Susana Vinga, Alexandra M. Carvalho, MSAX: Multivariate symbolic aggregate approximation for time series classification. In Cazzaniga P., Besozzi D., Merelli I., Manzoni L. (eds). Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2019, Revised Selected Papers. Lecture Notes in Computer Science, vol 12313 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-63061-4_9
  16. João Brito, Marta Lopes, Alexandra M. Carvalho, Susana Vinga, Unravelling breast and prostate common gene signatures by Bayesian network learning. In Raposo M., Ribeiro P., Sério S., Staiano A., Ciaramella A. (eds). Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2018, Revised Selected Papers. Lecture Notes in Computer Science, vol 11925 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-34585-3_25
  17. Pedro Ferreira, Alexandra M. Carvalho, Sara Vinga, Variational inference in probabilistic single-cell RNA-seq models. In Raposo M., Ribeiro P., Sério S., Staiano A., Ciaramella A. (eds). Computational Intelligence Methods for Bioinformatics and Biostatistics. CIBB 2018, Revised Selected Papers. Lecture Notes in Computer Science, vol 11925 (2020). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-34585-3_2
  18. Marta B. Lopes, André Veríssimo, Eunice Carrasquinha, Susana Vinga, On the Role of Hub and Orphan Genes in the Diagnosis of Breast Invasive Carcinoma. In Nicosia G., Pardalos P., Umeton R., Giuffrida G., Sciacca V. (eds), Machine Learning, Optimization, and Data Science. LOD 2019. Lecture Notes in Computer Science, vol 11943 (2019). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-37599-7_52
  19. Telma Pereira, Sofia Pires, Marta Gromicho, Susana Pinto, Mamede de Carvalho, Sara C. Madeira, Predicting assisted ventilation in Amyotrophic Lateral Sclerosis using a mixture of experts and conformal predictors. In KDD 2019 Workshop on Applied Data Science, August 2019. URL: http://arxiv.org/abs/1907.13070
  20. João E. Batista, Nuno M. Rodrigues, Sara Silva, To adapt or not to adapt, or the beauty of random settings. In Proceedings of the GECCO-2019 Companion. ACM, New York, NY, USA, 336-337 (July 2019). URL: https://doi.org/10.1145/3319619.3321994
  21. Pedro Branco, Paulo Mateus, A Traceable Ring Signature Scheme Based on Coding Theory. In Ding J., Steinwandt R. (eds) Post-Quantum Cryptography. PQCrypto 2019, Lecture Notes in Computer Science, vol 11505 (July 2019). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-25510-7_21
  22. Irene Azzali, Leonardo Vanneschi, Sara Silva, Illya Bakurov, Mario Giacobini, A Vectorial Approach to Genetic Programming. In Proceedings of EuroGP-2019. Lecture Notes in Computer Science, vol 11451 (March 2019). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-16670-0_14
  23. Margarida Sousa, Alexandra M. Carvalho, Learning consistent tree-augmented dynamic Bayesian networks. In Nicosia G., Pardalos P., Giuffrida G., Umeton R., Sciacca V. (eds), Machine Learning, Optimization, and Data Science. LOD 2018, Revised Selected Papers. Lecture Notes in Computer Science, vol 11331 (February 2019). Springer, Cham. URL: https://doi.org/10.1007/978-3-030-13709-0_15

Other publications (9)

  1. Carolina Barata, Ana M. Rodrigues, Helena Canhão, Susana Vinga, Alexandra M. Carvalho, Predicting biologic therapy failure in spondyloarthritis' patients using joint models for longitudinal and survival analysis, JMIR Medical Informatics (2021), submitted
  2. Alexandra M. Carvalho, Margarida Sousa, Mário Figueiredo, Complete Minimum Description Length for Learning Bayesian Networks, Journal of Machine Learning Research (2020), submitted
  3. Cláudia Constantino, Alexandra M. Carvalho, Susana Vinga, Coupling sparse Cox models with clustering of longitudinal transcriptomics data for trauma prognosis, BioData Mining (2020), submitted
  4. Jorge L. Serras, Susana Vinga, Alexandra M. Carvalho, Outlier detection for multivariate time series using dynamic Bayesian networks, Applied Sciences (2020), submitted
  5. Tiago Leão, Sara C. Madeira, Marta Gromicho, Mamede de Carvalho, Learning dynamic Bayesian networks from time-dependent and time-independent data: Unraveling disease progression in Amyotrophic Lateral Sclerosis, Journal of Biomedical Informatics (2020), submitted
  6. Bruno Mera, Paulo Mateus, Alexandra M. Carvalho, On the minmax regret for statistical manifolds: the role of curvature, arXiv:2007.02904 (2020), submitted
  7. Hector Silva, Bruno Mera, Nikola Paunkovic, Interferometric geometry from symmetry-broken Uhlman gauge group and applications to topological phase transitions, arXiv:2010.06629 (2020), submitted
  8. D. Zorro, P. Mateus, P. Adão, A. Souto, Information flow security with encryption, Journal of Logical and Algebraic Methods in Programming (2020), submitted
  9. F. Massa, P. Yadav, A. Moqanaki, W. O. Krawec, P. Mateus, N. Paunkovic, A. Souto, and P. Walther, Experimental semi-quantum key distribution with classical users, NPJ - Quantum Information (2020), submitted

Reports (3/6)

  1. Carolina de Seixas Serra Domingos Barata, Grant report in preparation (Feb 2021)
  2. Vasco de Campos Candeias, Grant report in preparation (Jan 2021)
  3. Sara Cristina Pontes Vieira, Analysis of heterogeneous and high-dimensional data of rheumatic diseases patients through clustering methods. MSc extended abstract (Nov 2019)

Organization of scientific meeting and seminars (7/6)

  1. 28/Dez/2020 - 7th meeting, Zoom
  2. 24/Jul/2020 - 6th meeting, Zoom
  3. 27/Mar/2020 - 5th meeting, Zoom
  4. 9/Jan/2020 - 4th meeting/seminar, NMS/CEDOC
  5. 27/June/2019 - 3rd meeting/seminar, FCiências.ID
  6. 29/March/2019 - 2nd meeting/seminar, INESC-ID
  7. 5/July/2018 - Kick-off meeting/seminar, IT

PhD thesis (1/1)

  1. Luis Muñoz Delgado (2019). Multidimensional Transformations of the Feature Space with Genetic Programming. PhD Thesis, Instituto Tecnológico de Tijuana, Mexico.

Master thesis (12/7)

  1. Joana Alter Palhinha, Machine Learning methods for finding predictors of Rheumatoid Arthritis' treatment response, Master in Biomedical Engineering, Instituto Superior Técnico, University of Lisbon (Jan 2021). Supervisors: Susana Vinga and Alexandra M. Carvalho
  2. Vasco de Campos Candeias, Cloud-based web application for multivariate time series analysis: A language-agnostic integrative architecture for short- and long-running machine learning algorithms, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Jan 2021). Supervisors: Alexandra M. Carvalho and Susana Vinga
  3. José Pedro de Almeida Gabriel Vieira Borges, Clustering multivariate time series using dynamic Bayesian networks, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Nov 2020). Supervisors: Alexandra M. Carvalho and Susana Vinga
  4. Carolina de Seixas Serra Domingos Barata, Longitudinal and survival data analysis for rheumatic diseases' prognosis, Master in Biomedical Engineering, Instituto Superior Técnico, University of Lisbon (Out 2020). Supervisors: Susana Vinga and Alexandra M. Carvalho
  5. Nuno Rodrigues, Exploring Neuroevolution Fitness Landscapes for Optimization and Generalization, Master in Informatics Engineering, Faculdade de Ciências, University of Lisbon (Jul 2020). Supervisors: Sara Silva and Leonardo Vanneschi
  6. Joana Matos, Biclustering Electronic Health Records to Unravel Disease Presentation Patterns, Master in Data Science, Faculdade de Ciências, University of Lisbon (Nov 2019). Supervisor: Sara C. Madeira
  7. Sara Cristina Pontes Vieira, Analysis of heterogeneous and high-dimensional data of rheumatic diseases patients through clustering methods, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Nov 2019). Supervisors: Alexandra M. Carvalho and Susana Vinga
  8. João Henrique Fialho Rodrigues, Time series analysis using restricted Boltzmann machines and dynamic Bayesian networks, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Nov 2019). Supervisors: Alexandra M. Carvalho and Paulo Mateus
  9. Manuel Pereira da Conceição Monteiro Anacleto, MSAX: Multivariate symbolic aggregate approximation for time series classification, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Nov 2019). Supervisors: Alexandra M. Carvalho and Susana Vinga
  10. Guilherme Reis de Moura, Time series data imputation - Comparison of Dynamic Time Warping with Needleman-Wunsch algorithm, Master in Electrical and Computer Engineering, Instituto Superior Técnico, University of Lisbon (Nov 2019). Supervisors: Alexandra M. Carvalho and Susana Vinga
  11. Joana de Oliveira Mira Godinho, Latent variable modelling and variational inference for single-cell RNA-seq differential expression analysis, Master in Computer Science, Instituto Superior Técnico, University of Lisbon (Oct 2019). Supervisors: Susana Vinga and Alexandra M. Carvalho
  12. Rita Sousa, Evolving meaning: using Genetic Programming to learn similarity perspectives for mining biomedical data, Master in Bioinformatics and Computational Biology, Faculdade de Ciências, University of Lisbon (Jul 2019). Supervisors: Cátia Pesquita and Sara Silva

Models (1/3)

  1. Temporal sequence alignment for clustering medical longitudinal data: AliClu

Computational applications (10/5)

  1. Dynamic Bayesian networks online: MAESTRO
  2. A tDBN framework with static and dynamic variables: sdtDBN
  3. Outlier detection in multivariate time series: METEOR
  4. Early classification in multivariate time series: MCEC
  5. Consistent and BFS-consistent k-graph dynamic Bayesian networks: cDBN and bcDBN
  6. Clustering with dynamic Bayesian multinets: Clustering with DBMs
  7. Missing value imputation with dynamic Bayesian networks: MVI with DBNs
  8. Combing BoLtzmAnn Machines with Dynamic Bayesian nEtworks: BLADE
  9. SIngle-cEll differeNtial Analysis: SIENA
  10. Extended ZINBayes: ext-ZINBayes