When combating the spread of disease, researchers and scientists need to work together to understand the way in which networks interact at the cellular level. The work being undertaken by Algorithmic Network Science Group (ANSG) at West Point’s Network Science Center to study force and data scientists at Reveal to study influence begs analysts to ask how the community can apply powerful models to understand disease and the way it operates in the human body.
Spyros Artavanis-Tsakonas, Professor of Cell Biology at Harvard Medical School, recently published a report arguing that scientists need to understand how molecules function together as an integrated network and not just in isolation at the cellular level. His team published a large-scale complex map tracking interactions of proteins, an essential step toward understanding how disease is caused. While visualizing the cell structure, Artavanis-Tsakonas also successfully identified how proteins communicate and channel information between and amongst nodes. Moving forward, it seems that this work could be advanced with the use of analytic technologies that will enable researchers to assess the probability (p) of infection across the network over time, based on knowledge creation of the behavior of molecules, or influence, in relation to one another.
Applying analytic technologies in this way would not only assist the field of bioinformatics in examining how disease spreads at the cellular level, but also provide more detailed insight into how to model and employ methods to treat susceptible and infected cells in integrated networks. Developing a “spreader” methodology includes the application of advanced technologies to solve complex problems in varying fields, such as food security, counter-insurgency and social networking, where analysts must understand how people and organizations and governments operate in relation to one another.
Post by: Dan Potocki, who directs the Initiatives Group at Praescient Analytics, a collective of subject matter experts and thought leaders committed to solving the biggest problems with advanced analysis technologies.