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Profile Photo for Daniel Lobo

Daniel Lobo

Assistant Professor

Biological Sciences
Biological Sciences, Room 115
Postdoc, Tufts University (2015)
Ph D, University of Malaga (2010)
MS, University of Malaga (2007)
BS, University of Seville (2005)
CV View CV
Research Interests

What are the dynamic regulatory mechanisms, the information processing, and the specific molecular elements that control complex biological processes? At the Lobo Lab we develop new computational and mathematical methods to build quantitative dynamic models, produce testable hypothesis, and validate them in vivo with molecular assays at the bench. Our integrated systems biology approach aims to understand the regulatory dynamics controlling multidimensional biological phenomena such as development and regeneration, the formation of cancer and other diseases when this process goes awry, and their applications to systems and synthetic biology. To this end, we also create mathematical and computational models, high-performance in silico experiments and simulators, and novel formalisms, ontologies, and databases to centralize and unambiguously describe biological experiments and their results.

Teaching Interests

BIOL 737 - Research Seminar in Bioinformatics and Computational Biology

BIOL 615 - Systems Biology (graduate)

BIOL 415 - Systems Biology

BIOL 313 - Introduction to Bioinformatics and Computational Biology

Intellectual Contributions

bbab104 Briefings in Bioinformatics

Computational systems biology of morphogenesis Computational Systems Biology in Medicine and Biotechnology Springer

Formalizing Phenotypes of Regeneration Whole Body Regeneration Springer

vol. 117 3876-3890 Biotechnology and Bioengineering

vol. 48 427-435 Nucleic Acids Research

9 vol. 36 2881–2887 Bioinformatics

11 vol. 117 2166-2179 Biophysical Journal

vol. 485 110042 Journal of Theoretical Biology

vol. 381 229–249 Information Sciences

vol. 7 41339 Scientific Reports

Advances in Unconventional Computing: Emergence, Complexity and Computation 637–654 Switzerland Springer International Publishing

17 vol. 32 2681–2685 Bioinformatics

2 vol. 3 78–102 Regeneration

Artificial Neural Network Modelling vol. 628 45–65 Springer International Publishing

4 vol. 23 291–297 Journal of Computational Biology

vol. 1288 F1000Research

11 vol. 16 27865–27896 International Journal of Molecular Sciences

397 vol. 8 ra99 Science Signaling