Fuzzy Logic Predicts Cell Aging
June 18, 2010
Related
- Natural Ventilation in Historic Buildings Can Save Energy
- ‘Layer Down’ — Thin Coating of MXene Material Could Replace Thick Layers of Insulation
- Children Exposed to Antiseizure Meds During Pregnancy Face Neurodevelopmental Risks, Drexel Study Finds
- Standardized Autism Screening During Pediatric Well Visits Identified More, Younger Children with High Likelihood for Autism Diagnosis
The process of aging disturbs a broad range of cellular mechanisms in a complex fashion and is not well understood. Computer models using fuzzy logic might help to unravel these complexities and predict how aging progresses in cells and organisms, according to a study from Drexel University in Philadelphia and Children's Hospital Boston. "One important goal of computational approaches in aging is to develop integrated models of a unifying aging theory in order to better understand the progression of aging phenotypes grounded on molecular mechanisms," said Andres Kriete, Associate Professor at Drexel's School of Biomedical Engineering, Science and Health Systems and lead author of the study. The study, which will appear in the June issue of PLOS Computational Biology (http://www.ploscompbiol.org/doi/pcbi.1000820), relates progressive damage and dysfunction in aging, dubbed a vicious cycle, to inflammatory and metabolic stress response pathways. Interestingly, the activation of these pathways remodels the inner functioning of the cell in a protective and adaptive manner and thus extends lifespan. This is the first time that scientists have applied fuzzy logic modeling to the field of aging. "Since cellular biodynamics in aging may be considered a complex control system, a fuzzy logic approach seems to be particularly suitable," said Dr. William Bosl, co-author of this study. Dr. Bosl, a staff scientist in the Informatics Program at Children's Hospital Boston, developed a fuzzy logic modeling platform called Bionet together with a cell biologist, Dr. Rong Li of the Stowers Institute for Medical Research in Kansas City, to study the complex interactions that occur in a cell's machinery using the kind of qualitative information gained from laboratory experiments.Fuzzy logic can handle imprecise input, but makes precise decisions and has wide industrial applications from air conditioning to anti-lock break systems in cars, using predefined rules. In a similar fashion, the aging model relies on sets of rules drawn from experimental data to describe molecular interactions. "Integration of such data is the declared goal of systems biology, which enables simulation of the response of cells to signaling cues, cell cycling and cell death," said Glenn Booker, who is Faculty at the College of Information Science and Technology at Drexel and co-author on the study. Applications in aging are currently geared towards deciphering the underlying connections and networks. "We have to realize that the real strength of computational systems biology in aging is to be able to predict and develop strategies to control cellular networks better as they may be related to age related diseases," said Dr. Kriete, "and our approach is just a first step in this direction." News Media Contacts:Noah Cohen, for Drexel University 215-895-2705, 267-228-5599 (cell) or noah.cohen@drexel.eduKeri Stedman, for Children's Hospital Boston 617-919-3114 or keri.stedman@childrens.harvard.edu
In This Article
Drexel News is produced by
University Marketing and Communications.
now.editor@drexel.edu
For story suggestions or to share feedback
now.webmaster@drexel.edu
For questions concerning the website, or to report a technical problem