Systems Biology impacts Biomedicine at USC Michelson

Biology, technology and computation all come together in the form of systems biology: the future of biomedical research. Dr. Gary K. Michelson, recognizing the potential of systems biology, has donated $50 million to fund the USC Michelson Center for Convergent Bioscience where a cross-disciplinary team of elite scientists will address this new field of medical research.

What Is Systems Biology?

What Is Systems Biology?

>What Is Systems Biology?

What Is Systems Biology?

The exact definition of systems biology depends upon each particular field of research. For example: ecologists are concerned with ecosystems, biologists focus on organisms, physiologists work with tissues, and molecular biologists are concerned with macromolecules. So, in an effort to provide better understanding of the evolution of systems biology, Dr. Westerhoff and Dr. Palsson published an article in the October 2004 issue of Nature Biotechnology which explores systems biology from a historical perspective [1].

Systems Biology | Systems Biology Trinity: Institute of Systems Biology’s innovation engine

(Fig.I) Systems Biology Trinity: Institute of Systems Biology’s innovation engine

The article discusses two paths merging to become systems biology: one path which focuses on scaling-up molecular biology by looking at many molecules simultaneously (e.g. human genome sequencing), the other path which focuses on building large-scale models by looking at how many molecules interact simultaneously (e.g. mathematical models of metabolic pathways). Therefore, the authors conclude that systems biology is simple; it is an integrated outlook of how a biological system works. Since the publication of their article in 2004, many organizations -including the Michelson Medical Research Foundation– have recognized the importance of systems biology in advancing biomedical research.

Envisioning Future Biomedical Research

Envisioning Future Biomedical Research

Envisioning Future Biomedical Research

Envisioning Future Biomedical Research

To imagine the trajectory of systems biology in biomedical research, one can examine research from the Institute for Systems Biology (a non-profit research institute in Seattle, Washington) [2]. The institute describes its approach to systems biology in solving challenging biological problems as a so-called innovation engine; outlining three major areas of activities:

  • Biology—Biologists raise new biological questions for making discoveries that drive the development of new technology.
  • Technology—Engineers generate new data with technology that drives the development of new software.
  • Computation—Computer scientists propose new hypotheses with mathematical models that provide new insight to biological research.

Systems Biology | (FIG.II) The Evolution of Molecular Biology into Systems Biology: The roots of systems biology in mainstream molecular biology

(Fig.II) The Evolution of Molecular Biology into Systems Biology: The top timeline represents the root of systems biology in mainstream molecular biology, with its emphasis on individual macromolecules. Scaled-up versions of this effort then induced systems biology as a way to look at all those molecules simultaneously, and consider their interactions. The lower timeline represents the lesser-known effort that constantly focused on the formal analysis of new functional states that arise when multiple molecules interact simultaneously.

USC Michelson Center for Convergent Bioscience

USC Michelson Center for Convergent Bioscience

USC Michelson Center for Convergent Bioscience

USC Michelson Center for Convergent Bioscience

Systems biology requires a cross-disciplinary team including biologists, engineers, computer scientists, mathematicians, chemists, physicists, physicians and others who can come together to tackle challenging biological problems. So, Dr. Gary K. Michelson, recognizing the potential of systems biology in medical research, donated $50 million to fund the Michelson Center for Convergent Bioscience located at the University of Southern California.

Especially relevant is the work of the core team of scientists and engineers at the USC Michelson Center: Dr. Steve A. Kay, Dr. Scott E. Fraser, Dr. Raymond C. Stevens, and Dr. Peter Kuhn. Their goal, along with Dr. Michelson, is to conduct research at the intersection of life and biomedical sciences in order solve problems in health and related fields.

Scientists Behind USC’s Michelson Center

Scientists Behind USC’s Michelson Center

Scientists Behind USC’s Michelson Center

Scientists Behind USC’s Michelson Center

Systems Biology | Steve A. Kay is the Director of Convergent Bioscience and Provost Professor of Neurology, Biomedical Engineering and Biological Sciences

Dr. Steve A. Kay is the Director of Convergent Bioscience and Provost Professor of Neurology, Biomedical Engineering and Biological Sciences at the USC Michelson Center for Convergent Bioscience.

Dr. Kay’s research focuses on the construction and evolution of complex regulatory networks (e.g. the evolutionary origins of circadian clocks).

His research relies on many experimental tools of systems biology, including mouse and Arabidopsis models, chemical screens, large-scale gene expression datasets, bioinformatics, and mathematical modeling.

Most recently, Dr. Kay’s work identified more than 1,000 potential direct targets of the clock protein (transcription factor Circadian Clock Associated 1), highlighted an expanded role of the clock in regulating a broad range of biological processes, and provided a comprehensive resource for functional studies [3].

Systems Biology | Scott E. Fraser, Elizabeth Garrett Chair in Convergent Bioscience, is the Provost Professor in the Departments of Biomedical Engineering and Biological Science.

Dr. Scott E. Fraser, Elizabeth Garrett Chair in Convergent Bioscience, is the Provost Professor in the Departments of Biomedical Engineering and Biological Science. He is also the Director of Science Initiatives at the University of Southern California. In 2015, Fraser was inducted as a fellow by the National Academy of Inventors.

His research focuses on molecular analyses and imaging of intact biology systems from embryonic development, genetics, and neuroscience. Earlier in his career Dr. Fraser co-authored an excellent review of imaging in systems biology, along with Dr. Sean G. Megason; published in the September, 2007 in the Cell, the article discusses the power of imaging tools in watching biological circuits over time in microorganisms, plants, and animals [4].

They propose that standardized, quantitative, and reusable digital imaging is essential for the progress of systems biology. Furthermore, in an article published in January of 2009 in PLOS Biology, Dr. Fraser along with Dr. Gregory T. Reeves, share their expertise on biological systems from an engineering point of view [5]. They describe biological systems as dynamic systems—discussing sensitivity analysis for measuring robustness of biological systems.

They explain the engineer’s perspective in the context of biological systems, concluding that a mathematical model for a biological system not only makes predictions about that system, but also provides an explanatory tool for better understanding said system.

Systems Biology | Raymond C. Stevens is the Provost Professor in the Department of Biomedical Engineering and the Department of Chemistry, as well as the Director of the Science Bridge Institute at the University of Southern California.

Dr. Raymond C. Stevens is the Provost Professor in the Department of Biomedical Engineering and the Department of Chemistry, as well as the Director of the Science Bridge Institute at the University of Southern California.

His research focuses on the study of the chemistry and biology of neurotransmission and neurological diseases. Dr. Stevens along with Dr. Vsevolod Katrich, and Dr. Vadim Cherezov published an article in the November, 2012 edition of Annual Reviews in Pharmacology and Toxicology, which discusses the structure-function of the G protein-coupled receptor superfamily [6].

Especially relevant is the the researchers focus on the challenges of studying the structure-function, and the required collaboration of experts from multiple disciplines to advance the fields at a rapid and efficient rate. In addition, they address the importance of computer modeling to generate a comprehensive picture of biological systems, look at molecular interactions, or prove a platform for drug discovery.

Systems Biology | Peter Kuhn is the Dean’s Professor of Biological Sciences, and Professor of Medicine and Engineering.

Dr. Peter Kuhn is the Dean’s Professor of Biological Sciences, and Professor of Medicine and Engineering. He is also the Associate Director of the Science Bridge Institute at the University of Southern California. His research focuses on the redesign of cancer care, especially personalized medicine and individualized patient care.

According to an article published in January of 2015 in Physical Biology, Dr. Kuhn and his colleagues have developed a methodology to analyze phenotypes, morphometrics, and genomes of circulating melanoma cells at the single cell level, in advanced stage patients [7].

Utilizing this methodology, they have found chondroitin sulfate proteoglycan 4 expressing circulating melanoma cells in the majority of advanced stage patients. In the article they suggest that high content analysis of those cells may be helpful for designing personalized cancer therapy [7].

Continuing Successful Research In Systems Biology

Continuing Successful Research In Systems Biology

Continuing Successful Research In Systems Biology

Continuing Successful Research In Systems Biology

By combining biological experiments with mathematical and computational models, systems biology is certain to be a potent approach in the study of how biological systems work. However, there is a risk of oversimplification and misconstruction in a complex biological system. In the October, 2015 publication of Science, Dr. Kirk (Cambridge School of Public Health), Dr. Babtie and Dr. Stumpf (Imperial College London) discuss the certainties and uncertainties of systems biology [8].

For a small biological system, the approach of systems biology might largely rely on robust prior knowledge, and established molecular interactions. So, there may be limitations in generating a biological model if all terms or parameters are not directly observed or known while for a large biological system, systems biology is likely to rely on automated network inference algorithms. Therefore, it may be difficult to generate new hypotheses worthy of further investigation due to the fact that not all algorithms are accurate or effective. Consequently, the authors conclude that the success of mathematical and computational modeling of biological systems depends on better assessing, communicating, and understanding certainties and uncertainties of the model.

“Deriving mathematical models in biology is rarely straightforward.”

Mathematical models usually represent elements of a biological system at one scale.

Choosing the appropriate degree of abstraction and simplification can be influenced by current knowledge about the system, the quality and quantity of experimental data, the computational demands of a particular modeling approach, and the modeling aims.

(Fig.III) Systems biology (un)certainties

Systems Biology | Mathematical models usually represent elements of a biological system at one scale.
(Fig.IIIa) Parameters in biological models aren’t known.

Typically, not all terms or parameters in a biological model are known or observable directly — except for some highly specific systems.

The abundances of all the key players (molecules, cells, or individuals) cannot be measured simultaneously and continuously.

Thus, despite being often overlooked, the challenge is not only to identify suitable mathematical descriptions of biological systems (such as gene regulatory networks) and mathematical representations of such systems that provide mechanistic insight-

It is also to communicate the inevitable uncertainty in the model’s (possibly many) unknowns.

Systems Biology | The number of unknowns in a model is partly determined by the scale of the system being studied
(Fig.IIIb) The unknowns in a model is partly determined by the scale of the system.

A biological system may range in scale from a few interacting molecules to whole populations of organisms, and this can have a huge impact on both the modeling approach and the associated assessment of uncertainty.

Although large-scale grand unifying biological models have occasionally been sought, these efforts remain the exception and only exist in early draft forms. Challenges remain for models of such scope, incl. how to validate their quality and adequately report uncertainty in both overall global structure and implied submodels.

Whatever the scale of the system and data set, many different models are likely to provide plausible fits, while still remaining consistent with current knowledge.

Systems Biology | Models are simplified (but not simplistic) representations of real systems
(Fig.IIIc) Models are simplified representations.

Models represent simplified systems and this is precisely the property that makes them attractive to explore the consequences of our assumptions, and to identify where we lack understanding of the principles governing a biological system.

Models are tools to uncover mechanisms that cannot be directly observed, akin to microscopes or nuclear magnetic resonance machines.

Used and interpreted appropriately, with due attention paid to inherent uncertainties, the mathematical and computational modeling of biological systems allows the exploration of hypotheses. But the relevance of these models depends on the ability to assess, communicate, and, ultimately, understand their uncertainties.

The Michelson Center for Convergent Bioscience [USC] continues to bring together researchers from multiple disciplines in order to confront challenges in health and other, related fields. Through the integration of systems biology tools and resources, the USC Michelson Center and its research teams drive innovation in medicine and medical devices.

Image Credit

Credit: English Text curated by Jinnah Griffin

Wanqiu Hou is the Founder of Scientific HealthSense, a website based application in mining health data for a consumer service. He received his PhD from the Chinese Academy of Sciences. Dr. Hou has more than 10 years of experience in medical research, writing and communications.

Wanqiu Hou is the Founder of Scientific HealthSense, a website based application in mining health data for a consumer service. He received his PhD from the Chinese Academy of Sciences. Dr. Hou has more than 10 years of experience in medical research, writing and communications.

Wanqiu Hou is the Founder of Scientific HealthSense, a website based application in mining health data for a consumer service. He received his PhD from the Chinese Academy of Sciences. Dr. Hou has more than 10 years of experience in medical research, writing and communications.

Wanqiu Hou is the Founder of Scientific HealthSense, a website based application in mining health data for a consumer service. He received his PhD from the Chinese Academy of Sciences. Dr. Hou has more than 10 years of experience in medical research, writing and communications.



The Michelson Medical Research Foundation's Groundwork blog is brought to you thanks to the generous support of Dr. Gary K. Michelson and his wife, Alya Michelson.

The Michelson Medical Research Foundation's Groundwork blog is brought to you thanks to the generous support of Dr. Gary K. Michelson and his wife, Alya Michelson.

The Michelson Medical Research Foundation's Groundwork blog is brought to you thanks to the generous support of Dr. Gary K. Michelson and his wife, Alya Michelson.

The Michelson Medical Research Foundation's Groundwork blog is brought to you thanks to the generous support of Dr. Gary K. Michelson and his wife, Alya Michelson.