Our Publications


  • Exploring AI-Driven Machine Learning Approaches for Optimal Classification of Peri-Implantitis Based on Oral Microbiome Data: A Feasibility Study
  • Diagnostics 2025 πŸ”—

  • Linking peri-implantitis to microbiome changes in affected implants, healthy implants, and saliva: a cross-sectional pilot study
  • Frontiers in Cellular and Infection Microbiology 2025 πŸ”—

  • INSaFLU-TELEVIR: an open web-based bioinformatics suite for viral metagenomic detection and routine genomic surveillance
  • Genome Medicine 2024 πŸ”—

  • Facilitating β€œOmics” for Phenotype Classification Using a User-Friendly AI-Driven Platform: Application in Cancer Prognostics
  • BioMedInformatics 2023 πŸ”—

  • Predicting Cancer Prognostics from Tumour Transcriptomics Using an Auto Machine Learning Approach
  • Medical Sciences Forum 2023 πŸ”—

  • Predictive Modelling in Clinical Bioinformatics: Key Concepts for Startups
  • BioTech 2022 πŸ”—

  • A Rapid and Affordable Screening Tool for Early-Stage Ovarian Cancer Detection Based on MALDI-ToF MS of Blood Serum
  • Applied Sciences 2022 πŸ”—

  • MALDI-ToF Mass Spectra Phenomic Analysis for Human Disease Diagnosis Enabled by Cutting-Edge Data Processing Pipelines and Bioinformatics Tools
  • Current Medicinal Chemistry 2021 πŸ”—

  • Simulation of multiple microenvironments shows a pivot role of RPTPs on the control of Epithelial-to-Mesenchymal Transition
  • BioSystems 2020 πŸ”—

  • Predicting the evolution and control of the COVID-19 pandemic in Portuga
  • F1000Research 2020 πŸ”—

  • Bioinformatic identification of euploid and aneuploid embryo secretome signatures in IVF culture media based on MALDI-ToF mass spectrometry
  • Journal Assisted of Reproduction and Genetics 2020 πŸ”—








    Selected Publications


  • Exploring AI-Driven Machine Learning Approaches for Optimal Classification of Peri-Implantitis Based on Oral Microbiome Data: A Feasibility Study
  • Diagnostics 2025 πŸ”—

  • Facilitating β€œOmics” for Phenotype Classification Using a User-Friendly AI-Driven Platform: Application in Cancer Prognostics
  • BioMedInformatics 2023 πŸ”—

  • Predicting Cancer Prognostics from Tumour Transcriptomics Using an Auto Machine Learning Approach
  • Medical Sciences Forum 2023 πŸ”—





    Empowering Biotech and Biomedical Research instituitions with state-of-the-art predictive modelling and bioinformatics solutions.