With the advent of high throughput life sciences, todays life scientist are entrusted with deciphering knowledge and discerning patterns from a deluge of raw and processed information as part of a relatively complex discovery process. Core technologies generating the raw data such as sequences, images and traces are consistently producing higher resolution of modality both in terms of quality and quantity. Attempting to keep pace with this growth are underlying analysis techniques that employ technologies such as grid, high performance computing, web services, embedded databases, robotics, machine learning, semantic web to name a few. Typical life sciences discovery processes involve complex scenarios that necessitate cross-cutting, interdisciplinary approaches and collaborations.

This talk will present work being done at the Biotechnology Computing group at the University of Arizona in the area of sample management and translational use of  technologies for visualizing and tracking samples ranging in size from molecules to shuttle buses.

The purpose of the talk is to provide information and background to students and faculty members looking for applications and translational use of technologies and solutions from their domain of expertise to
problems and questions in  the life sciences arena. The intention is to further enhance and foster interdisciplinary collaborations between departments at the University of Arizona.