Spring Break
Systems biology series expounds on research
Suman Datta
Issue date: 12/3/04 Section: Sci-Tech
- Page 1 of 1
The Daniel Baugh Institute for functional genomics and computational biology at Thomas Jefferson University organizes Computational Biology Afternoon Tea Seminar Series, at which people in the field of computational biology present their work.
As the Web site states, topics include "data analysis, modeling and simulation, bioinformatics, functional genomics, and system biology."
Systems biology is rapidly gaining recognition in the biomedical student community at Drexel. This field is relatively new, and is changing the way scientists view and practice biology.
The Human Genome Project catalyzed the development of this field in the late 90s. A list of human genes emerged and biology has increasingly been seen as an information science.
High-thoroughput technologies were also developed. Computer science and mathematics became an integral part of biology.
Systems biology takes a systematic approach to the study and analysis of a biological system. Until recently, scientists took parts of an organism and studied it in detail.
Specific biomolecules, genes etcetera were isolated and studied. There was no concerted effort to find out how these elements fit into the larger biological system. High thoroughput technologies, which have now become available, are a boon to this new field.
These help acquire biological information, which can then be used to develop computational models. The models which scientists aim to develop are models of the complete system, be it a cellular pathway or an organism like yeast.
For example, the seminar Nov. 3 was presented by Dr. Theresa Good, an associate professor of chemical and biomedical engineering at the University of Maryland, Baltimore County, was titled "Problems in Biocomplexity from an Experimentalist's Perspective."
According to Dr. Good, we have been lagging behind in our ability to interpret the data that we have been collecting from biological systems in the past few years.
"As an experimentalist, our focus is not on the development of computational tools, but on using computational tools in order to understand data, or predict how to best obtain experimental data," she mentioned.
She explained how her research group has used computational tools to make sense out of the data collected from biological systems. Her examples included mathematical models and optimization tools used in tackling problems in Alzheimer's disease, HIV chemotherapy and T-cell diseases.
As the Web site states, topics include "data analysis, modeling and simulation, bioinformatics, functional genomics, and system biology."
Systems biology is rapidly gaining recognition in the biomedical student community at Drexel. This field is relatively new, and is changing the way scientists view and practice biology.
The Human Genome Project catalyzed the development of this field in the late 90s. A list of human genes emerged and biology has increasingly been seen as an information science.
High-thoroughput technologies were also developed. Computer science and mathematics became an integral part of biology.
Systems biology takes a systematic approach to the study and analysis of a biological system. Until recently, scientists took parts of an organism and studied it in detail.
Specific biomolecules, genes etcetera were isolated and studied. There was no concerted effort to find out how these elements fit into the larger biological system. High thoroughput technologies, which have now become available, are a boon to this new field.
These help acquire biological information, which can then be used to develop computational models. The models which scientists aim to develop are models of the complete system, be it a cellular pathway or an organism like yeast.
For example, the seminar Nov. 3 was presented by Dr. Theresa Good, an associate professor of chemical and biomedical engineering at the University of Maryland, Baltimore County, was titled "Problems in Biocomplexity from an Experimentalist's Perspective."
According to Dr. Good, we have been lagging behind in our ability to interpret the data that we have been collecting from biological systems in the past few years.
"As an experimentalist, our focus is not on the development of computational tools, but on using computational tools in order to understand data, or predict how to best obtain experimental data," she mentioned.
She explained how her research group has used computational tools to make sense out of the data collected from biological systems. Her examples included mathematical models and optimization tools used in tackling problems in Alzheimer's disease, HIV chemotherapy and T-cell diseases.
Be the first to comment on this story