In the operating room and patient ward of the future, it is envisioned that real-time monitoring of proteins and gene expression will be used to determine pharmacokinetic parameters, get intervention feedback, and other information- just as physicians today monitor heart rate, blood pressure, etc. In fact, some biomedical laboratories are already doing real-time monitoring of cellular protein abundance and gene expression. The temporal quality of music, coupled with alerts which can be triggered by inharmonious music, alarms, and other mechanisms, provides a means to notify doctors about the current status of the patient, without requiring full attention (as a visual monitor would). In fact, music (e.g., via radio) is already omnipresent in many operating rooms and wards. Monitoring equipment with alarms, from heart to oxygen monitors, are also common. Thus, why not add biomolecular-based music?

Musical expression has another application: science education. It has been shown that learning via multiple modalities improves comprehension. Current computer-based biology tools generally rely on visual representations. Sonification (or turning data into sound) of genetic and proteomic data according to our methods can be provided as part of a 3-D (and the fourth dimension, 4-D: with music representing time) virtual reality interactome visualization tool. This allows for novel and greater in-depth means for education, analysis, and discovery. Thus, this project actually falls under two of the themes: “Science and the Arts” as well as Innovations.” By transforming complex biological signals into the music of everyday life, this project also can also fall under the “Science in Everyday Life” theme.

The exhibit will include both visual and auditory aspects. It will be both educational and fun- and thus will be well suited for the Cambridge Science Festival (CSF) audience: from fun for K-12 to learning for adults and seniors interested in the new genomic revolution that has unfolded in the last decade.

The main impetus behind the original work was to develop a platform that combines novel approaches in real-time interactivity, dynamic data loading, and 4-D presentation. It can be used for visualizing, manipulating, and reporting about many kinds of biological networks such as gene regulation and protein interaction networks.

As shown in Figure 1, we have a three-prong approach that works synergistically. One element is dynamics: our approach is to allow dynamic loading of subparts of the graph as necessary during the session. This can be done in conjunction with interactivity: thus allowing the user to point and click in 3-D space on the graph (plus on a time axis) instead of manually entering, by text, the subparts of the graph desired. A fly-mode automatically navigates, in real-time, through selected nodes in a pathway to allow users to see both the local and global topology. Here, we try to use every feasible modality to present the network. By using true 3-D space visualization (via 3-D electronic shutter-based stereoscopic glasses) 1, the researcher can rotate, manipulate, and visualize the network in real three dimensional space.

We use 4-D navigation via head tracking and voice-based navigation 1- methods to allow for more natural interaction, so users so they can focus on the science behind the networks. Interactivity is also enhanced by 3-D spatial network manipulation and dynamic 3-D lighting that make it easier to work with the gene or protein network. The final aspect is 4-D. May not be available for CSF event. However, this equipment is relatively cheap to purchase if CSF is interested. . We use the aural temporospatial localization to present a forth dimension: time. For example, the user may explore the network and wish to know how genes are expressed over a temporal sequence.

Thus, one can follow its abundance/expression level over the course of a microarray or other temporal-based dataset. By combining dynamics, 4-D, and interactivity, this platform allows users to manipulate and visualize networks, so that they can learn about the underlying biological pathways. Examples of what this system looks like are shown in Figure 1 , Figure 2, Figure 3, Figure 4, Figure 5 .