Carlos Boto

Carlos BotoThis email address is being protected from spambots. You need JavaScript enabled to view it. | FCTUNL | Bioengineering PhD | Entering year: 2009 | Graduation year: 2015

pdf CV Carlos Boto (1.50 MB)


Current Position: Co-founder, Operations & Sales Officer at doDOC, Coimbra/Lisbon/Boston, Portugal/USA

Thesis Title: Leukemia Cell Differentiation by Light Activatable Nanoparticles

Supervisors: Lino Ferreira, Tariq Enver, Isidro Sanchez-Garcia

Thesis Abstract: The main goal of this project was to develop a light-activatable nanoparticle system to improve the intracellular delivery of RA in leukemic cells. The possibility of remotely activating the drug delivery system opens new therapeutic opportunities due to the possibility of activating the differentiation of the cells at the bone marrow niche and potentially interfering with the leukemic stem cell niche.


  • Carlos Boto, Emanuel Quartin, Yijun Cai, Alberto Martin-Lorenzo, Maria Begona Garcia Cenador, Sandra Pinto, Rajeev Gupta, Tariq Enver, Isidro Sanchez-Garcia, Deng Li, Ricardo Neves, Lino Ferreira. “Prolonged intracellular accumulation of light-inducible nanoparticles in leukemia cells allows their remote activation”. Nature Communications (Accepted) 2017
  • Tiago Santos, Carlos Boto, Cláudia Saraiva, Liliana Bernardino, Lino Ferreira. “Nanomedicine approaches to modulate stem cells in brain repair”. Trends in Biotechnology 2016, 34(6), 437-439
  • Tiago Santos, Raquel Ferreira, Emanuel Quartin, Carlos Boto, Cláudia Saraiva, José Bragança, João Peça, Cecília Rodrigues, Lino Ferreira, Liliana Bernardino. “Light potentiates retinoic acid-induced neuronal differentiation of neural stem cells”. (Submitted) 2016 
  • Patent: Cismondi, F., Boto, C., Melo, P., Jensen, S. “A Computer-implemented Method of Interacting with a Search Engine”. EP14195156, 2014
  • Patent: Boto, C., Neves, R., Ferreira, L. “Light-activatable polymeric nanoparticles”. PAT20131000066281, 2013

Carlos Daniel Machado

daniel.machado.jpgThis email address is being protected from spambots. You need JavaScript enabled to view it. | UMinho | Bioengineering PhD | Entering year: 2007 | Graduation year: 2011

ThesisTitle: Novel modeling formalisms and simulation tools in Computational Biosystems

Supervisors: Eugénio Ferreira (UMinho), Isabel Rocha (UMinho), Bruce Tidor (MIT)

Thesis Abstract: The goal of Systems Biology is to understand the complex behavior that emerges from the interaction among the cellular components. Industrial biotechnology is one of the areas of application, where new approaches for metabolic engineering are developed, through the creation of new models and tools for simulation and optimization of the microbial metabolism. Although whole-cell modeling is one of the goals of Systems Biology, so far most models address only one kind of biological network independently. This work explores the integration of dierent kinds of biological networks with a focus on the improvement of simulation of cellular metabolism. The bacterium Escherichia coli is the most well characterized model organism and is used as our case-study. 

An extensive review of modeling formalisms that have been used in Systems Biology is presented in this work. It includes several formalisms, including Boolean networks, Bayesian networks, Petri nets, process algebras, constraint-based models, dierential equations, rule-based models, interacting state machines, cellular automata and agent-based models. We compare the features provided by these formalisms and classify the most suitable ones for the creation of a common framework for modeling, analysis and simulation of integrated biological networks. Currently, there is a separation between dynamic and constraint-based modeling of metabolism. Dynamic models are based on detailed kinetic reconstructions of central metabolic pathways, whereas constraint-based models are based on genome-scale stoichiometric reconstructions. Here, we explore the gap between both formulations and evaluate how dynamic models can be used to reduce the solution space of constraint-based models in order to eliminate kinetically infeasible solutions. The limitations of both kinds of models are leading to new approaches to build kinetic models at the genome-scale. The generation of kinetic models from stoichiometric reconstructions can be performed within the same framework as a transformation from discrete to continuous Petri nets. However, the size of these networks results in models with a large number of parameters. In this scope, we develop and implement structural reduction methods that adjust the level of detail of metabolic networks without loss of information, which can be applied prior to the kinetic inference to build dynamic models with a smaller number of parameters. In order to account for enzymatic regulation, which is not present in constraint-based models, we propose the utilization of Extended Petri nets. This results in a better scaold for the kinetic inference process. We evaluate the impact of accounting for enzymatic regulation in the simulation of the steady-state phenotype of mutant strains by performing knockouts and adjustment of enzyme expression levels. It can be observed that in some cases the impact is signicant and may reveal new targets for rational strain design. In summary, we have created a solid framework with a common formalism and methods for metabolic modeling. This will facilitate the integration with gene regulatory networks, as we have already addressed many issues also associated with these networks, such as the trade-o between size and detail, and the representation of regulatory interactions.

Full thesis available for download at Universidade do Minho Repositorium.


  • Daniel Machado, Nuno Preguiça, Carlos Baquero, J. Legatheaux Martins. VC^2 - Providing Awareness in Off-The-Shelf Version Control Systems. In IWCES9: Proceedings of the 9th International Workshop on Collaborative Editing Systems. November, 2007.
  • Daniel Machado, Miguel Rocha. getALife - An Artificial Life Environment for the Evaluation of Agent-Based Systems and Evolutionary Algorithms for Reinforcement Learning. At the 21st International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems. June, 2008 (accepted).

Research interests: Computational Biology / Systems Biology; Formal Methods / Modeling, Specification and Software Development; Artificial Life / Machine Learning / Artificial Intelligence.

Carlos Rodriguez

carlos.rodriguez.jpgThis email address is being protected from spambots. You need JavaScript enabled to view it. | IST  | Bioengineering PhD | Entering year: 2007

Research interests: Design and operation of bioreactor systems for the expansion and controlled neural differentiation of stem cells (Stem Cells Bioengineering).

Links: (IST) (Institute for Biotechnology and Bioengineering) (BioEngineering Research Group)

Cláudia Vistas

claudia.mistas.jpgThis email address is being protected from spambots. You need JavaScript enabled to view it. | IST | Bioengineering PhD  | Entering year: 2007

Research topic/area: Optical Nanosensors based on Semiconductor nanocrystals and metal nanoparticles for biomedical applications (Biomedical Devices & Technologies).

Communications/Conference presentations:

  • Vistas, C.; Silva, A.C.; Thibaud, C.; Brayner, R. “Biosynthesis of new hybrid materials based on Alginate-Au, [email protected] and Carrageenan-Ag. SERS effect for bio-detection applications”, Therapeutic Nano-objects Genoconference,12th June 2007, Evry/France


Cristiana da Silva Faria

This email address is being protected from spambots. You need JavaScript enabled to view it. | FCTUNL| Bioengineering Systems PhD | Entering year: 2011 | Graduation year: 2017

Thesis Title: Development of hydrogel-based constructs with encapsulated cells

Supervisors: Helena Santos (ITQB), Isabel Rocha (UM)