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 systems and methods to automatically reverse-engineer quantitative dynamic models from experimental data, produce testable hypothesis, and find the best next set of novel experiments to test at the bench. Our computational 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.
We develop computational methods to automatically reverse engineer dynamic models, discover novel elements, and find the best next experiments to test.
We build quantitative mathematical models to understand, analyze, and predict the behavior of biological systems.
We create ontologies, curate databases, and develop expert systems used by both human scientists and artificial intelligence machines.
We study how shapes and patterns are formed from a single cell during development and restored through regeneration.
We seek to understand why and how regulatory mechanisms go awry to produce cancer and other diseases.
We design and optimize regulatory and metabolic networks with desired dynamics and behaviors to solve specific bioengineering problems.