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Pedro T. Monteiro
   Tecnico
INESC-ID
Affiliation: INESC-ID / IST - Universidade de Lisboa
Address: INESC-ID Lisboa
Rua Alves Redol 9
P-1000-029 Lisboa
PORTUGAL
Email:
Telef: Alameda campus - ext: 2320 / tel: +351 21 3100 320
TagusPark campus - ext: 5281
Index - Teaching - Supervision - Publications - Software - MEIC Scholarly IDs

PhD students
  • Diogo Couceiro (2023-ongoing). Co-supervised by Miguel C. Teixeira
    Targeting pathogenesis and engineering cell factories by developing mixed regulatory metabolic genomic models in yeasts
    Ph.D. thesis in Biotechnology and Biosciences, IST - University of Lisbon
  • Fábio Cruz (2023-ongoing). Supervised by Andreia Sofia Teixeira
    Predicting progression of neurodegenerative diseases with temporal networks
    Ph.D. thesis in Informatics, FC - University of Lisbon
  • Filipe Gouveia (2016-2021). Co-supervised by Inês Lynce
    Inference and Revision of Models of Biological Regulatory Networks
    Ph.D. thesis in Computer Science and Engineering, IST - University of Lisbon
  • Alexandre Lemos (2016-2021). Supervised by Inês Lynce
    Re-Solving Hard Computational Problems
    Ph.D. thesis in Computer Science and Engineering, IST - University of Lisbon
  • Pedro Varela (2015-2019). Co-supervised by Claudine Chaouiya
    Efficient attractor characterization in large discrete event systems: application to biological regulatory networks
    Ph.D. thesis in Computer Science and Engineering, IST - University of Lisbon
Short-stay visiting PhD students
  • Robert Schwieger (2018). Supervised by Heike Siebert. Freie Universität Berlin, Germany.
  • Praveen Kumar Guttula (2018). Supervised by Mukesh K. Gupta. National Institute of Technology Rourkela, India.

MSc students
  • António Romeu Pinheiro (MEIC 2023/2024). Python library for Boolean model revision
  • Yhya Dabah (MEIC 2023/2024). Deep learning techniques for cancer classification using multi omics data
  • Gonçalo Nascimento (MEIC 2023/2024). Learning geo/temporal patterns from IPST blood collection/consumption data
  • Miguel Pereira (MEIC 2023/2024). Responsive UI para portal YEASTRACT+
  • Patrícia Tenera Roxo (MMA 2022/2023). Vicinity Characterization of Monotone Non-Degenerate Boolean Functions
  • Sebastião Santos (MEIC 2022/2023). Development of Python library to integrate metabolic and regulatory networks
  • Miguel Dauphinet (MEIC 2022/2023). Learning temporal-geographical patterns on IPST blood collection/consumption data
  • Nelson Trindade (MEIC 2022/2023). Deep neural networks for multi omics integration
  • André Marinho (MEIC 2022/2023). Comparative study and development of automated assessment tools
  • Guilherme Carlota (MEIC 2022/2023). IPST blood collection/consumption data: Models for blood collections optimization
  • José Diogo Castro (MECD 2022/2023). Descriptive and predictive modelling of blood activity in Portugal to support sourcing and campaign decisions
  • Mariana Brejo (MEIC 2021/2022). Exploring and Forecasting Nation-Wide Data of Blood donations and Demand
  • Tomás Inácio (MEIC 2021/2022). Optimization models for IPST blood collection
  • Guilherme Ribeiro (MEIC 2021/2022). Spanning edge betweenness for large graphs and percolation
  • Fábio Cruz (MEIC 2021/2022). Community structure in transcriptional regulatory networks of yeast species
  • Maria Jacinto (MBioMed 2021/2022). Using Network Science and Clustering for the characterization and stratification of Migraine patients
  • Sofia Torres (MBCB@FCUL 2020/2021). Extending EpiLog functionalities, validation with a multi-cellular model of Epithelial-to-Mesenchymal Transition
  • João Castanheira (MDS@FCUL 2020/2021). Learning temporal and geographical patterns from IPST blood collection data
  • Carolina Parada (MBioEng 2020/2021). A Metabolic-Regulatory Genome-Scale Integration for Saccharomyces cerevisiae: Predicting Targets for Increased Ethanol Production
  • Paulo Dias (MEIC 2020/2021). Functional characterization of transcriptional regulatory networks of yeast species
  • Joana Alves (MEIC 2020/2021). Development of models to optimize IPST blood collections
  • Francisco Lopes (MEIC 2020/2021). Learning temporal and geographic patterns from IPST blood collection data
  • Yu Cheng (MEIC 2020/2021). Attractor reachability estimation in logical models
  • Ruben Teixeira (MEIC 2019/2020). SoC-FPGA Accelerated BDD-Based Model Checking
  • Vanda Pinto Dias (MBioEng 2018/2019). Genome-wide analysis of the molecular bases of the probiotic activity of S. boulardii strains, through the development of new Yeastract tools
  • Melike Yilmaz (MBioEng 2017/2018). Genome-wide analysis of the molecular bases of the probiotic activity of S.boulardii strains, through the development of new Yeastract tools
  • Rui Miguel Costa (MBioNano 2017/2018). Peripheral molecular targets for adiposity control
  • Alexandre Lemos (MEIC 2015/2016). Inference in Biological Regulatory Networks
  • Sauvagya Manna (MBiotech 2015/2016). PathoYeastract: Extending the YEASTRACT database to pathogenic yeasts

BSc students
  • Inês Trigueiro (LBioMed 2023/2024). Cancer classification using proteomics data
  • Margarida Almeida (LBiolEng 2023/2024). Training classifiers on proteomics data to identify cancer tissue types
  • Maria Pereira (LBioMed 2022/2023). Definição e geração de modelos lógicos de regulação na base de dados YEASTRACT

IEEE-IST interships (CoLab Sessions)
  • Maria Pereira (LBioMed 2021/2022). Construction of a regulatory-metabolic genome-scale model for S. cerevisiae
  • Sara Costa (LBioEng 2019/2020). From network topology to function