From Beaker to Bits: Graph Theory Yields Computational Model of Human Tissue
An all too seldom example of how reaching across disciplinary lines can lead to fundamental breakthroughs in more than one area.
First step, alert any graph or data store people you know, along with any medical research types.
Second step, if you are in CS/Math, think about another department that interests you. If you are in other sciences or humanities, strike up a conversation with the CS/Math department types.
In both cases, don’t take “no” or lack of interest as an answer. Talk to the newest faculty or even faculty at other institutions. Or even established companies.
No guarantees that you will strike up a successful collaboration, much less have a successful result. But, we all know how successful a project that never begins will be, don’t we?
Here is a story of a collaborative project that persisted and succeeded:
Computer scientists and biologists in the Data Science Research Center at Rensselaer Polytechnic Institute have developed a rare collaboration between the two very different fields to pick apart a fundamental roadblock to progress in modern medicine. Their unique partnership has uncovered a new computational model called “cell graphs” that links the structure of human tissue to its corresponding biological function. The tool is a promising step in the effort to bring the power of computational science together with traditional biology to the fight against human diseases, such as cancer.
The discovery follows a more than six-year collaboration, breaking ground in both fields. The work will serve as a new method to understand and predict relationships between the cells and tissues in the human body, which is essential to detect, diagnose and treat human disease. It also serves as an important reminder of the power of collaboration in the scientific process.
The new research led by Professor of Biology George Plopper and Professor of Computer Science Bulent Yener is published in the March 30, 2012, edition of the journal PLoS One in a paper titled, “ Coupled Analysis of in Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship.” They were joined in the research by Evrim Acar, a graduate student at Rensselaer in Yener’s lab currently at the University of Copenhagen. The research is funded by the National Institutes of Health and the Villum Foundation.
The new, purely computational tool models the relationship between the structure and function of different tissues in body. As an example of this process, the new paper analyzes the structure and function of healthy and cancerous brain, breast and bone tissues. The model can be used to determine computationally whether a tissue sample is cancerous or not, rather than relying on the human eye as is currently done by pathologists around the world each day. The objective technique can be used to eliminate differences of opinion between doctors and as a training tool for new cancer pathologists, according to Yener and Plopper. The tool also helps fill an important gap in biological knowledge, they said.
BTW, if you want to see all the details: Coupled Analysis of in Vitro and Histology Tissue Samples to Quantify Structure-Function Relationship