The structure/function relationship is fundamental to our understanding of biological systems at all levels, and drives most, if not all, techniques for detecting, diagnosing, and treating disease. The concept is powerful enough to have inspired a 200+ year-long effort to describe the components of our biological universe in ever finer detail, beginning with the Linnean taxonomic system of cataloging organisms based on their structural similarities, and culminating with microscale descriptions such as the complete genomes of several organisms, including humans. However, having reduced the complex biological universe to a myriad of minute parts, we encounter new forms of complexity: data overload and curse of dimensionality. Simply put, we've taken our biological machine apart but can't put it back together again- our ability to accumulate reductionist data has outstripped our ability to understand it. Thus, we encounter a gap in the structure/function relationship: having accumulated an extraordinary amount of detailed information about biological structures, we can't assemble it in a way that explains the correspondingly complex biological functions these structures perform. We propose a novel approach to this problem based on representing tissues using graph theory and learning its structural properties by analyzing the underlying graphs. Our long-range objective is to close this gap by establishing quantitative features that link tissue structure to biological function. Our immediate goals for this project are to define three quantitatively different functional states (healthy, damaged, diseased) of three morphologically distinct tissues (brain, breast, bone) based on their distinguishing morphological characteristics, then test three hypotheses that propose to link these quantitative features to specific biological activities in these tissues Successful completion of this project will provide a new and powerful tool for quantitatively linking telltale structural properties of tissues (e.g., cellular distribution, morphology, contact) with specific disease states and fundamental behaviors of the cells comprising these tissues. This will be useful both to scientists conducting basic research to uncover the guiding principles of tissue structure and function, and to clinicians seeking to quickly and accurately detect and diagnose diseases that involve alterations in tissue structure.
Successful completion of this project will provide a new and powerful tool for quantitatively linking telltale structural properties of tissues (e.g., cellular distribution, morphology, contact) with specific disease states and fundamental behaviors of the cells comprising these tissues. This will be useful both to scientists conducting basic research to uncover the guiding principles of tissue structure and function, and to clinicians seeking to quickly and accurately detect and diagnose diseases that involve alterations in tissue structure.
