Dr. Daniel Lobo

About

Associate Professor
Biological Sciences

Undergraduate Program Director
Bioinformatics and Computational Biology

Member, Center for Stem Cell Biology & Regenerative Medicine
University of Maryland, School of Medicine

Member, Marlene and Stewart Greenebaum Comprehensive Cancer Center
University of Maryland, Medical System

Research interests

The Lobo Lab aims to understand the regulation and mechanisms of biological growth, shape, and pattern formation with a systems biology approach. We combine both molecular and computational methods to gain a mechanistic understanding of development and regeneration, find personalized treatments for cancer, and streamline regulatory designs in synthetic biology. We have developed new techniques for the acquisition and formalization of microscopy spatial data, the formulation of mechanistic models of genetic, metabolic, and signaling networks, and high-performance machine learning methods for inferring such models. We combine these computational methods with molecular assays at the bench for obtaining quantitative spatial and dynamic data, such as gene expression and morphological outcomes, and for prediction validation including genetic, surgical, and pharmacological perturbations and the engineering of synthetic circuits. This ambitious research plan will have a long-term payoff for the streamline of our ability to infer and design dynamic mechanisms, which will be essential for advancing fundamental understanding in biology and developing new medical and industrial applications.

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

Education

  • Postdoc, Developmental, Regenerative, and Cancer BiologyTufts University (2015)
  • Ph D, Computer ScienceUniversity of Malaga (2010)
    Evolutionary development based on genetic regulatory models for behavior-finding
  • MS, Computer Science and Artificial IntelligenceUniversity of Malaga (2007)
    Automated design of complex structures using bio-inspired genetic methods
  • BS, Computer Science and Computer EngineeringUniversity of Seville (2005)
    A repository of software components specified by functionality