Programme offers a multidisciplinary approach to study by integrating research techniques and methodologies from biology, chemistry, physics, engineering, mathematics and computer science.
Imagine being able to take a fantastic voyage into the human body and see how life evolves in a single cell, observe what triggers and sustains a beating heart - or perhaps journey into a tumor to witness how cancer destroys life and what doctors might be able to do to successfully treat it.
Such a possibility is not the stuff of overactive imaginations or sci-fi films; it's the domain of assistant professor Santiago Schnell, who heads the systems biology laboratory at the Indiana University School of Informatics.
The programme offers a multidisciplinary approach to study biological phenomena by integrating research techniques and methodologies from biology, chemistry, physics, engineering, mathematics and computer science.
This collaborative endeavour uses mathematical modeling to better understand the origin and progression of life systems.
And that approach is explained in large part in 'Multiscale Modeling in Biology', featured in the March-April issue of American Scientist.
Schnell, the principal author, is joined by Ramon Grima, of London's Imperial College, and Philip Mani, of the University of Oxford.
"Firmly rooted in observation and experiment, biology for decades had little use for mathematical modeling, which was, in any event, a slow business until computers made it possible to simulate large complex systems of non-linear equations," said Schnell, assistant professor of informatics, who holds adjunct appointments in physics and biology.
"Today," Schnell added, "biologists and mathematicians desperately need one another - not just to find structure in the vast quantities of data flowing from experiment but also to integrate this information into models that explain at multiple scales of time and of space how life works".
Schnell and his colleagues have numerous ongoing research projects using multiscale modeling.
One endeavour, funded by the National Institutes of Health, studies how early embryo segments work to form blocks of cells that are precursors of the spine.
Failures in segmentation can be fatal or can cause developmental abnormalities such as scoliosis and spina bifida.
Schnell has been working on a modeling project based on genetic and molecular features of the evolution of colorectal cancer, and the effectiveness of treatments.
The study appeared Theoretical Biology and Medical Modelling a year ago and has garnered much attention from cancer researchers and scientists and is ranked first among the most viewed articles of all time in the journal.
"We now have a good deal of information about the genetic mutations underlying colon cancer and how activation of the mutated genes is affected by oxygen starvation and overcrowding," Schnell said, who is associate director at the Biocomplexity Institute at IU.
"We can model the life cycle of a cell in its various stages and how it is influenced by environmental changes".
More specifically, they are constructing a model to predict what proportion of cells would be sensitive to radiation therapy at different stages of tumour evolution.
Currently, radiation is administered to cancer patients using extensions of a 20-year-old model which assumes tumour sensitivity and population growth are constant during radiotherapy.
"We found that radiation doses administered to stressed cells is effective, but radiation administered after the tumour reaches an oxygen-starved condition has little effect because most of the cells have become inactive," said Schnell.
Mathematical modeling of biological systems, including cancer, poses challenges on several fronts, Schnell said.
The first is to ensure the collection of qualitative and quantitative experimental observations, and that requires closer collaborations with scientists from several disciplines.
A second task is to construct a model that has a reasonable amount of precise parameters to simplify a problem without losing its essentials.
"The use of mathematical ideas, models and techniques is rapidly growing and increasingly important throughout life sciences," Schnell observed.
"The development of new programs has eliminated the well-demarcated divisions between theory and experiment.
The culture of biology is changing with a growing awareness that, as a colleague recently told me, "to think is to model".
