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Sara C. Madeira
Sara Cordeiro Madeira
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- affiliation: University of Lisbon, Instituto Superior Técnico, Portugal
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2020 – today
- 2024
- [j43]Eduardo N. Castanho, Helena Aidos, Sara C. Madeira
:
Biclustering data analysis: a comprehensive survey. Briefings Bioinform. 25(4) (2024) - [j42]Eduardo N. Castanho, João Lobo, Rui Henriques, Sara C. Madeira:
Correction: G-bic: generating synthetic benchmarks for biclustering. BMC Bioinform. 25(1): 16 (2024) - [j41]Miguel G. Silva
A Comprehensive Survey on Biclustering-based Collaborative Filtering. ACM Comput. Surv. 56(12): 313:1-313:32 (2024) - [j40]Diogo F. Soares
Comprehensive assessment of triclustering algorithms for three-way temporal data analysis. Pattern Recognit. 150: 110303 (2024) - [c43]Giovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2024. CLEF (2) 2024: 118-139 - [c42]Giovanni Birolo, Pietro Bosoni, Guglielmo Faggioli, Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Alessandro Guazzo, Enrico Longato, Sara C. Madeira, Umberto Manera, Stefano Marchesin, Laura Menotti, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Isotta Trescato, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2024: 1312-1331 - [c41]Andreia S. Martins, Daniela M. Amaral, Eduardo N. Castanho, Diogo F. Soares, Ruben Branco, Sara C. Madeira, Helena Aidos:
Predicting the Functional Rating Scale and Self-Assessment Status of ALS Patients with Sensor Data. CLEF (Working Notes) 2024: 1366-1379 - [c40]Helena Aidos, Roberto Bergamaschi, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Barbara Di Camillo, Mamede de Carvalho, Nicola Ferro, Piero Fariselli, Jose Manuel García Dominguez, Sara C. Madeira, Eleonora Tavazzi:
iDPP@CLEF 2024: The Intelligent Disease Progression Prediction Challenge. ECIR (6) 2024: 53-59 - 2023
- [j39]Erica Tavazzi
Artificial intelligence and statistical methods for stratification and prediction of progression in amyotrophic lateral sclerosis: A systematic review. Artif. Intell. Medicine 142: 102588 (2023) - [j38]Eduardo N. Castanho, João Lobo, Rui Henriques
G-bic: generating synthetic benchmarks for biclustering. BMC Bioinform. 24(1): 457 (2023) - [c39]Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2023. CLEF 2023: 343-369 - [c38]Guglielmo Faggioli, Alessandro Guazzo, Stefano Marchesin, Laura Menotti, Isotta Trescato, Helena Aidos, Roberto Bergamaschi, Giovanni Birolo, Paola Cavalla, Adriano Chiò, Arianna Dagliati, Mamede de Carvalho, Giorgio Maria Di Nunzio, Piero Fariselli, Jose Manuel García Dominguez, Marta Gromicho, Enrico Longato, Sara C. Madeira, Umberto Manera, Gianmaria Silvello, Eleonora Tavazzi, Erica Tavazzi, Martina Vettoretti, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2023: 1123-1164 - [c37]Ruben Branco, Diogo F. Soares, Andreia S. Martins, Joana Barros Valente, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos:
Investigating the Impact of Environmental Data on ALS Prognosis with Survival Analysis. CLEF (Working Notes) 2023: 1186-1198 - [c36]Ruben Branco, Joana Barros Valente, Andreia S. Martins, Diogo F. Soares, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos:
Survival Analysis for Multiple Sclerosis: Predicting Risk of Disease Worsening. CLEF (Working Notes) 2023: 1199-1209 - [c35]Helena Aidos
iDPP@CLEF 2023: The Intelligent Disease Progression Prediction Challenge. ECIR (3) 2023: 491-498 - [d1]Guglielmo Faggioli
iDPP@CLEF 2023 - Participants' repositories for the Intelligent Disease Prediction Progression Challenge. Zenodo, 2023 - 2022
- [j37]Maria Lua Nunes
Posture Risk Assessment in an Automotive Assembly Line Using Inertial Sensors. IEEE Access 10: 83221-83235 (2022) - [j36]Eduardo N. Castanho
Biclustering fMRI time series: a comparative study. BMC Bioinform. 23(1): 192 (2022) - [j35]Diogo F. Soares
Learning prognostic models using a mixture of biclustering and triclustering: Predicting the need for non-invasive ventilation in Amyotrophic Lateral Sclerosis. J. Biomed. Informatics 134: 104172 (2022) - [j34]Marta D. M. Noronha
Impact of metrics on biclustering solution and quality: A review. Pattern Recognit. 127: 108612 (2022) - [j33]Andreia S. Martins
Learning Prognostic Models Using Disease Progression Patterns: Predicting the Need for Non-Invasive Ventilation in Amyotrophic Lateral Sclerosis. IEEE ACM Trans. Comput. Biol. Bioinform. 19(5): 2572-2583 (2022) - [j32]Francisco Neves, Anna Carolina Finamore, Sara C. Madeira
Mining Actionable Patterns of Road Mobility From Heterogeneous Traffic Data Using Biclustering. IEEE Trans. Intell. Transp. Syst. 23(7): 6430-6445 (2022) - [c34]Alessandro Guazzo, Isotta Trescato
Intelligent Disease Progression Prediction: Overview of iDPP@CLEF 2022. CLEF 2022: 395-422 - [c33]Alessandro Guazzo, Isotta Trescato, Enrico Longato, Enidia Hazizaj, Dennis Dosso, Guglielmo Faggioli, Giorgio Maria Di Nunzio, Gianmaria Silvello, Martina Vettoretti, Erica Tavazzi, Chiara Roversi, Piero Fariselli, Sara C. Madeira, Mamede de Carvalho, Marta Gromicho, Adriano Chiò, Umberto Manera, Arianna Dagliati, Giovanni Birolo, Helena Aidos, Barbara Di Camillo, Nicola Ferro:
Overview of iDPP@CLEF 2022: The Intelligent Disease Progression Prediction Challenge. CLEF (Working Notes) 2022: 1130-1210 - [c32]Ruben Branco, Diogo F. Soares, Andreia S. Martins, Eleonora Auletta, Eduardo N. Castanho, Susana Nunes, Filipa Serrano, Rita Torres Sousa, Catia Pesquita, Sara C. Madeira, Helena Aidos:
Hierarchical Modelling for ALS Prognosis: Predicting the Progression Towards Critical Events. CLEF (Working Notes) 2022: 1211-1227 - [c31]Susana Nunes, Rita Torres Sousa, Filipa Serrano, Ruben Branco, Diogo F. Soares, Andreia S. Martins, Eleonora Auletta, Eduardo N. Castanho, Sara C. Madeira, Helena Aidos, Catia Pesquita:
Explaining Artificial Intelligence Predictions of Disease Progression with Semantic Similarity. CLEF (Working Notes) 2022: 1256-1268 - [i3]Miguel G. Silva, Rui Henriques
User-Specific Bicluster-based Collaborative Filtering: Handling Preference Locality, Sparsity and Subjectivity. CoRR abs/2211.08366 (2022) - 2021
- [j31]João Lobo, Rui Henriques
G-Tric: generating three-way synthetic datasets with triclustering solutions. BMC Bioinform. 22(1): 16 (2021) - [j30]Tiago Leão, Sara C. Madeira
Learning dynamic Bayesian networks from time-dependent and time-independent data: Unraveling disease progression in Amyotrophic Lateral Sclerosis. J. Biomed. Informatics 117: 103730 (2021) - [j29]Rui Henriques
FleBiC: Learning classifiers from high-dimensional biomedical data using discriminative biclusters with non-constant patterns. Pattern Recognit. 115: 107900 (2021) - 2020
- [j28]Telma Pereira
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. J. Biomed. Informatics 101: 103350 (2020) - [c30]André Ferreira
Predictive Medicine Using Interpretable Recurrent Neural Networks. ICPR Workshops (1) 2020: 187-202 - [c29]Joana Matos
Unravelling Disease Presentation Patterns in ALS Using Biclustering for Discriminative Meta-Features Discovery. IWBBIO 2020: 517-528 - [c28]Sofia Pires
Patient Stratification Using Clinical and Patient Profiles: Targeting Personalized Prognostic Prediction in ALS. IWBBIO 2020: 529-541 - [c27]Diogo F. Soares
Towards Triclustering-Based Classification of Three-Way Clinical Data: A Case Study on Predicting Non-invasive Ventilation in ALS. PACBB 2020: 112-122
2010 – 2019
- 2019
- [j27]Rui Henriques
Triclustering Algorithms for Three-Dimensional Data Analysis: A Comprehensive Survey. ACM Comput. Surv. 51(5): 95:1-95:43 (2019) - [c26]João M. C. Sousa
An Architecture Based on Fuzzy Systems for Personalized Medicine in ICUs. FUZZ-IEEE 2019: 1-6 - [i2]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. CoRR abs/1907.13070 (2019) - 2018
- [j26]Rui Henriques
BSig: evaluating the statistical significance of biclustering solutions. Data Min. Knowl. Discov. 32(1): 124-161 (2018) - [j25]Telma Pereira
Neuropsychological predictors of conversion from mild cognitive impairment to Alzheimer's disease: a feature selection ensemble combining stability and predictability. BMC Medical Informatics Decis. Mak. 18(1): 137:1-137:20 (2018) - [c25]Sofia Pires, Marta Gromicho
Predicting Non-invasive Ventilation in ALS Patients Using Stratified Disease Progression Groups. ICDM Workshops 2018: 748-757 - [i1]Telma Pereira, Sandra Cardoso, Dina Silva, Manuela Guerreiro, Alexandre de Mendonça, Sara C. Madeira:
Ensemble learning with Conformal Predictors: Targeting credible predictions of conversion from Mild Cognitive Impairment to Alzheimer's Disease. CoRR abs/1807.01619 (2018) - 2017
- [j24]Rui Henriques
BicPAMS: software for biological data analysis with pattern-based biclustering. BMC Bioinform. 18(1): 82:1-82:16 (2017) - [j23]Rui Henriques
Erratum to: BicPAMS: software for biological data analysis with pattern-based biclustering. BMC Bioinform. 18(1): 162:1-162:2 (2017) - [j22]Telma Pereira
Predicting progression of mild cognitive impairment to dementia using neuropsychological data: a supervised learning approach using time windows. BMC Medical Informatics Decis. Mak. 17(1): 110:1-110:15 (2017) - [c24]Telma Pereira, Alexandre de Mendonça, Francisco L. Ferreira, Sara C. Madeira, Manuela Guerreiro:
Towards a reliable prediction of conversion from Mild Cognitive Impairment to Alzheimer's Disease: stepwise learning using time windows. MIH@KDD 2017: 19-26 - [c23]Telma Pereira, Sandra Cardoso, Dina Silva
Towards Trustworthy Predictions of Conversion from Mild Cognitive Impairment to Dementia: A Conformal Prediction Approach. PACBB 2017: 155-163 - [c22]Francisco L. Ferreira, Sandra Cardoso, Dina Silva
Improving Prognostic Prediction from Mild Cognitive Impairment to Alzheimer's Disease Using Genetic Algorithms. PACBB 2017: 180-188 - 2016
- [j21]Rui Henriques
BicNET: Flexible module discovery in large-scale biological networks using biclustering. Algorithms Mol. Biol. 11: 14 (2016) - [j20]Rui Henriques
BiC2PAM: constraint-guided biclustering for biological data analysis with domain knowledge. Algorithms Mol. Biol. 11: 23 (2016) - 2015
- [j19]Rui Henriques
Multi-period classification: learning sequent classes from temporal domains. Data Min. Knowl. Discov. 29(3): 792-819 (2015) - [j18]Rui Henriques
Generative modeling of repositories of health records for predictive tasks. Data Min. Knowl. Discov. 29(4): 999-1032 (2015) - [j17]André Valério Carreiro
Prognostic models based on patient snapshots and time windows: Predicting disease progression to assisted ventilation in Amyotrophic Lateral Sclerosis. J. Biomed. Informatics 58: 133-144 (2015) - [j16]Rui Henriques
A structured view on pattern mining-based biclustering. Pattern Recognit. 48(12): 3941-3958 (2015) - [j15]Rui Henriques
Biclustering with Flexible Plaid Models to Unravel Interactions between Biological Processes. IEEE ACM Trans. Comput. Biol. Bioinform. 12(4): 738-752 (2015) - [c21]Rui Henriques
Pattern-Based Biclustering with Constraints for Gene Expression Data Analysis. EPIA 2015: 326-339 - [c20]Rui Henriques
BicNET: Efficient Biclustering of Biological Networks to Unravel Non-Trivial Modules. WABI 2015: 1-15 - 2014
- [j14]Rui Henriques
BicPAM: Pattern-based biclustering for biomedical data analysis. Algorithms Mol. Biol. 9: 27 (2014) - [j13]Rui Henriques
BicSPAM: flexible biclustering using sequential patterns. BMC Bioinform. 15: 130 (2014) - [j12]Miguel Cacho Teixeira
The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae. Nucleic Acids Res. 42(Database-Issue): 161-166 (2014) - [j11]Joana P. Gonçalves
LateBiclustering: Efficient Heuristic Algorithm for Time-Lagged Bicluster Identification. IEEE ACM Trans. Comput. Biol. Bioinform. 11(5): 801-813 (2014) - [c19]André Vale, Sara C. Madeira, Cláudia Antunes:
Mining coherent evolution patterns in education through biclustering. EDM 2014: 391-392 - 2013
- [c18]Cecília Nunes, Dina Silva
Class Imbalance in the Prediction of Dementia from Neuropsychological Data. EPIA 2013: 138-151 - [c17]Joana P. Gonçalves
Heuristic approaches for time-lagged biclustering. BIOKDD 2013: 1-9 - [c16]Hugo López-Fernández
A Workflow for the Application of Biclustering to Mass Spectrometry Data. PACBB 2013: 145-153 - [c15]Rui Henriques
Methods for the Efficient Discovery of Large Item-Indexable Sequential Patterns. NFMCP 2013: 100-116 - 2012
- [j10]Joana P. Gonçalves
AliBiMotif: Integrating alignment and biclustering to unravel transcription factor binding sites in DNA sequences. Int. J. Data Min. Bioinform. 6(2): 196-215 (2012) - [j9]André Valério Carreiro
Towards a Classification Approach using Meta-Biclustering: Impact of Discretization in the Analysis of Expression Time Series. J. Integr. Bioinform. 9(3) (2012) - [c14]André Valério Carreiro
Prognostic Prediction Using Clinical Expression Time Series: Towards a Supervised Learning Approach Based on Meta-biclusters. PACBB 2012: 11-20 - [c13]Filipe Cristóvão, Sara C. Madeira
Parallel e-CCC-Biclustering: Mining Approximate Temporal Patterns in Gene Expression Time Series Using Parallel Biclustering. PACBB 2012: 21-31 - 2011
- [j8]Joana P. Gonçalves
TFRank: network-based prioritization of regulatory associations underlying transcriptional responses. Bioinform. 27(22): 3149-3157 (2011) - [j7]André Valério Carreiro
Prognostic Prediction through Biclustering-Based Classification of Clinical Gene Expression Time Series. J. Integr. Bioinform. 8(3) (2011) - [j6]Dário Abdulrehman, Pedro T. Monteiro
YEASTRACT: providing a programmatic access to curated transcriptional regulatory associations in Saccharomyces cerevisiae through a web services interface. Nucleic Acids Res. 39(Database-Issue): 136-140 (2011) - [j5]Daniela Nitsch, Léon-Charles Tranchevent
PINTA: a web server for network-based gene prioritization from expression data. Nucleic Acids Res. 39(Web-Server-Issue): 334-338 (2011) - [c12]Ricardo Santos Aires, João A. Carriço, Alexandre P. Francisco
Baiacu: A Tool for the Visual Analysis of the Saccharomyces Cerevisiae Regulatory Network. PACBB 2011: 49-56 - [c11]André Valério Carreiro
Biclustering-Based Classification of Clinical Expression Time Series: A Case Study in Patients with Multiple Sclerosis. PACBB 2011: 229-239 - 2010
- [j4]Ignacio Medina
Babelomics: an integrative platform for the analysis of transcriptomics, proteomics and genomic data with advanced functional profiling. Nucleic Acids Res. 38(Web-Server-Issue): 210-213 (2010) - [j3]Sara C. Madeira
Identification of Regulatory Modules in Time Series Gene Expression Data Using a Linear Time Biclustering Algorithm. IEEE ACM Trans. Comput. Biol. Bioinform. 7(1): 153-165 (2010) - [c10]Joana P. Gonçalves, Sara C. Madeira:
e-BiMotif: Combining Sequence Alignment and Biclustering to Unravel Structured Motifs. IWPACBB 2010: 181-191 - [c9]Joana P. Gonçalves, Sara C. Madeira, Yves Moreau:
Network-Based Disease Candidate Gene Prioritization: Towards Global Diffusion in Heterogeneous Association Networks. NyNaK 2010
2000 – 2009
- 2009
- [j2]Sara C. Madeira
A polynomial time biclustering algorithm for finding approximate expression patterns in gene expression time series. Algorithms Mol. Biol. 4 (2009) - [c8]Sara C. Madeira
Efficient Biclustering Algorithms for Time Series Gene Expression Data Analysis. IWANN (2) 2009: 1013-1019 - [c7]Paulo Moura
High Level Thread-Based Competitive Or-Parallelism in Logtalk. PADL 2009: 107-121 - 2008
- [c6]Paulo Moura
Thread-Based Competitive Or-Parallelism. ICLP 2008: 713-717 - 2007
- [c5]Sara C. Madeira, Arlindo L. Oliveira:
An Efficient Biclustering Algorithm for Finding Genes with Similar Patterns in Time-series Expression Data. APBC 2007: 67-80 - 2005
- [c4]Sara C. Madeira
A Linear Time Biclustering Algorithm for Time Series Gene Expression Data. WABI 2005: 39-52 - 2004
- [j1]Sara C. Madeira
Biclustering Algorithms for Biological Data Analysis: A Survey. IEEE ACM Trans. Comput. Biol. Bioinform. 1(1): 24-45 (2004) - 2003
- [c3]Sara C. Madeira
A Data Mining Approach to Credit Risk Evaluation and Behaviour Scoring. EPIA 2003: 184-188 - [c2]João M. C. Sousa, Sara C. Madeira
Modeling charity donations using target selection for revenue maximization. FUZZ-IEEE 2003: 654-659 - 2002
- [c1]João M. C. Sousa, Uzay Kaymak
A comparative study of fuzzy target selection methods in direct marketing. FUZZ-IEEE 2002: 1251-1256
Coauthor Index
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last updated on 2024-12-02 21:25 CET by the dblp team
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