Evolving random boolean networks with genetic algorithms for regulatory networks reconstruction. - Mariana Recamonde Mendoza; Ana Lúcia C. Bazzan (GECCO, 2011)

Reverse engineering of GRNs: an evolutionary approach based on the tsallis entropy. - Mariana Recamonde Mendoza; Fabrício Martins Lopes; Ana Lúcia C. Bazzan (GECCO, 2012)

On the Ensemble Prediction of Gene Regulatory Networks: A Comparative Study. - Mariana Recamonde Mendoza; Ana L. C. Bazzan (SBRN, 2012)

An Epsilon-Greedy Mutation Operator Based on Prior Knowledge for GA Convergence and Accuracy Improvement: An Application to Networks Inference. - Mariana Recamonde Mendoza; Adriano Velasque Werhli; Ana L. C. Bazzan (SBRN, 2012)

RFMirTarget: A Random Forest Classifier for Human miRNA Target Gene Prediction. - Mariana Recamonde Mendoza; Guilherme C. da Fonseca; Guilherme L. de Morais; Ronnie Alves; Ana L. C. Bazzan; Rogerio Margis (BSB, 2012)

The Wisdom of Crowds in Bioinformatics: What Can We Learn (and Gain) from Ensemble Predictions? - Mariana Recamonde Mendoza; Ana Lúcia C. Bazzan (AAAI, 2013)

Spectral Alignment of Networks. - Soheil Feizi; Gerald T. Quon; Mariana Recamonde Mendoza; Muriel Médard; Manolis Kellis; Ali Jadbabaie (CoRR, 2016)

Social choice in distributed classification tasks: Dealing with vertically partitioned data. - Mariana Recamonde Mendoza; Ana L. C. Bazzan (Inf. Sci., 2016)

Social-Training: Ensemble Learning with Voting Aggregation for Semi-supervised Classification Tasks. - Matheus Alves; Ana L. C. Bazzan; Mariana Recamonde Mendoza (BRACIS, 2017)

Adaptive Incremental Gaussian Mixture Network for Non-Stationary Data Stream Classification. - Jorge C. Chamby-Diaz; Mariana Recamonde Mendoza; Ana L. C. Bazzan; Ricardo Grunitzki (IJCNN, 2018)

Dynamic Correlation-Based Feature Selection for Feature Drifts in Data Streams. - Jorge Cristhian Chamby-Diaz; Mariana Recamonde Mendoza; Ana Lúcia C. Bazzan (BRACIS, 2019)

Identifying and Fusing Duplicate Features for Data Mining. - Hortênsia Costa Barcelos; Mariana Recamonde Mendoza; Viviane Pereira Moreira (SBBD, 2020)

Detecting Aedes Aegypti Mosquitoes through Audio Classification with Convolutional Neural Networks. - Marcelo Schreiber Fernandes; Weverton Cordeiro; Mariana Recamonde Mendoza (CoRR, 2020)

A comparative evaluation of aggregation methods for machine learning over vertically partitioned data. - Bernardo Trevizan; Jorge C. Chamby-Diaz; Ana L. C. Bazzan; Mariana Recamonde Mendoza (Expert Syst. Appl., 2020)

Spectral Alignment of Graphs. - Soheil Feizi; Gerald T. Quon; Mariana Recamonde Mendoza; Muriel Médard; Manolis Kellis; Ali Jadbabaie (IEEE Trans. Netw. Sci. Eng., 2020)

Ensemble Feature Selection Compares to Meta-analysis for Breast Cancer Biomarker Identification from Microarray Data. - Bernardo Trevizan; Mariana Recamonde Mendoza (ICCSA (1), 2021)

Detecting Aedes aegypti mosquitoes through audio classification with convolutional neural networks. - Marcelo Schreiber Fernandes; Weverton Cordeiro; Mariana Recamonde Mendoza (Comput. Biol. Medicine, 2021)

Patterns of high-risk drinking among medical students: A web-based survey with machine learning. - Grasiela Marcon; Flávia de Ávila Pereira; Aline Zimerman; Bruno Castro da Silva; Lisia von Diemen; Ives Cavalcante Passos; Mariana Recamonde Mendoza (Comput. Biol. Medicine, 2021)

Cross-validation Strategies for Balanced and Imbalanced Datasets. - Thomas V. Fontanari; Tiago Comassetto Fróes; Mariana Recamonde Mendoza (BRACIS (1), 2022)

Study on the Complexity of Omics Data: An Analysis for Cancer Survival Prediction. - Carlos Daniel Andrade; Thomas V. Fontanari; Mariana Recamonde Mendoza (BSB, 2022)

Machine learning methods for prediction of cancer driver genes: a survey paper. - Renan Andrades; Mariana Recamonde Mendoza (Briefings Bioinform., 2022)

A hybrid ensemble feature selection design for candidate biomarkers discovery from transcriptome profiles. - Felipe Colombelli; Thayne Woycinck Kowalski; Mariana Recamonde Mendoza (Knowl. Based Syst., 2022)

EPGAT: Gene Essentiality Prediction With Graph Attention Networks. - João Schapke; Anderson R. Tavares; Mariana Recamonde Mendoza (IEEE ACM Trans. Comput. Biol. Bioinform., 2022)

"A Nova Eletricidade": Aplicações, Riscos e Tendências da IA Moderna. - Ana L. C. Bazzan; Anderson R. Tavares; André G. Pereira; Cláudio R. Jung; Jacob Scharcanski; Joel Luís Carbonera; Luís C. Lamb; Mariana Recamonde Mendoza; Thiago L. T. da Silveira; Viviane P. Moreira (Escola de Computação PPGC/UFRGS 50 Anos, 2023)

Prediction of Cancer-Related miRNA Targets Using an Integrative Heterogeneous Graph Neural Network-Based Method. - Emanoel Aurelio Vianna Fabiano; Mariana Recamonde Mendoza (BRACIS (3), 2023)

Explainability of COVID-19 Classification Models Using Dimensionality Reduction of SHAP Values. - Daniel M. Kuhn; Melina Loreto; Mariana Recamonde Mendoza; João Luiz Dihl Comba; Viviane Pereira Moreira (BRACIS (1), 2023)

COVID-VR: A Deep Learning COVID-19 Classification Model Using Volume-Rendered Computer Tomography. - Noemí Maritza Lapa Romero; Ricco Vasconcellos; Mariana Recamonde Mendoza; João Luiz Dihl Comba (CoRR, 2023)

"A Nova Eletricidade: Aplicações, Riscos e Tendências da IA Moderna - "The New Electricity": Applications, Risks, and Trends in Current AI. - Ana L. C. Bazzan; Anderson R. Tavares; André G. Pereira; Cláudio R. Jung; Jacob Scharcanski; Joel Luis Carbonera; Luís C. Lamb; Mariana Recamonde Mendoza; Thiago L. T. da Silveira; Viviane P. Moreira (CoRR, 2023)

Predicting Cancer Driver Genes: Leveraging Graph Convolutional Networks and Ensemble Learning. - Renan Soares de Andrades; Mariana Recamonde Mendoza (CIBCB, 2024)

Evaluating the Generalization of Neural Network-Based Pan-Cancer Classification Models for Cohort-Specific Predictions. - Thomas V. Fontanari; Mariana Recamonde Mendoza (BSB, 2024)

Acoustic identification of Ae. aegypti mosquitoes using smartphone apps and residual convolutional neural networks. - Kayuã Oleques Paim; Ricardo Rohweder; Mariana Recamonde Mendoza; Rodrigo Brandão Mansilha; Weverton Cordeiro (Biomed. Signal Process. Control., 2024)

Graph Neural Networks for Heart Failure Prediction on an EHR-Based Patient Similarity Graph. - Heloísa Oss Boll; Ali Amirahmadi; Amira Soliman 002; Stefan Byttner; Mariana Recamonde Mendoza (CoRR, 2024)

Graph neural networks for clinical risk prediction based on electronic health records: A survey. - Heloísa Oss Boll; Ali Amirahmadi; Mirfarid Musavian Ghazani; Wagner Ourique de Morais; Edison Pignaton de Freitas; Amira Soliman 002; Farzaneh Etminani; Stefan Byttner; Mariana Recamonde Mendoza (J. Biomed. Informatics, 2024)

Exploring the Feasibility of AI-Assisted Spine MRI Protocol Optimization Using DICOM Image Metadata. - Alice Vian; Diego Andre Eifer; Mauricio Anés; Guilherme Ribeiro Garcia; Mariana Recamonde Mendoza (CoRR, 2025)

Comparing Cluster-Based Cross-Validation Strategies for Machine Learning Model Evaluation. - Afonso Martini Spezia; Mariana Recamonde Mendoza (CoRR, 2025)