Luciano Joins Web Science Constellation
Joanne Sylvia Luciano
Joanne Sylvia Luciano has joined Rensselaer as research associate professor in the Tetherless World Research Constellation. Luciano’s research uses computational modeling and the World Wide Web to improve health care and advance medical discovery.
Luciano is an experienced technology consultant to major hospitals and biotechnology and pharmaceutical companies. In addition to her nearly 30 years as a consultant, she held a joint appointment with Harvard Medical School and Massachusetts General Hospital for nine years, where she served as a lecturer and research scientist using computational modeling to study human disease.
She joins an interdisciplinary research team within the Tetherless World Research Constellation at Rensselaer, dedicated to advancing science and society through understanding and utilization of the World Wide Web.
“There’s a vast amount of medically relevant data sitting in databases or websites and not being utilized,” Luciano said. “The focus of my research is to create technologies that make it easy to do medical research whether you are a doctor, patient, pharmaceutical company, or searching for alternative therapies or lifestyle changes.”
To accomplish these aims, Luciano utilizes computational languages, known as ontologies, and advanced mathematical modeling and computer simulation to understand illness, share medical data, and advance medical discovery and patient care. She builds computer-based technologies that improve healthcare by translating discoveries made at the laboratory or computer bench to the care received at an individual patient’s bedside known as bench to bedside care.
“There is an urgent need to shorten the time it takes to bring basic life science research results to clinical practice, and to get the clinical observations back to the research lab for further analysis,” she said. “To do this, technologies need to be in place that allow scientists to better represent, reuse, and communicate medical data.”
Luciano has helped develop several important ontologies including BioPAX, which is an international standard used for data related to cellular processes. BioPAX enables data to be combined in ways that were not possible before, making it possible to ask and answer complex biological questions. The language enables data to be combined automatically by computers, and because the representations are true to the current understanding of biology, other technology can be used to make inferences and reason over the data.
At the MITRE Corporation, she developed InfluenzO, an ontology to support influenza research, surveillance, and outbreak monitoring. She continues to lead this collaboration with the University of Maryland, the University of Texas Southwestern Medical Center, and the Canadian government.
She helped create the World Wide Web Consortium Health Care and Life Sciences (HCLSIG) special interest group. The HCLSIG integrates the efforts of pharmaceutical and clinical researchers, doctors, and technologists to build the next generation of medical Web-based technology standards.
She is also a co-organizer of the BioPathways Consortium, a group of scientists working to support scientific advancement in the area of biological pathways. Such research, which has been a foundation of Luciano’s career, uses computation to understand cell development, genetics, drug development, and disease.
In addition to ontologies, Luciano also utilizes mathematical modeling to study the dynamics of medical treatment response, looking for patterns that will help clinicians make more informed treatment choices. Patterns of treatment response often exist in groups of individuals. This study of treatment response patterns leads to so-called “personalized medicine” in which individual response to treatment can be modeled effectively and is important because individuals may respond differently to a treatment. She began this research at McLean Hospital while at Boston University, where she earned her doctorate. The work began as a study of different treatments (drug and therapy) for major depressive disorder.
That research led to the development of patented methods to select the best treatment for individual patients and predict the expected recovery patterns of treatments.
Luciano earned bachelor’s and master’s degrees in computer science and a doctorate in cognitive and neural systems from Boston University.