John Boyle
Senior Research Scientist
Director the Informatics Core
Institute for Systems Biology
Biography:
Dr. Boyle is senior research scientist at the Institute for Systems
Biology, at the institute he also directs the Informatics Core. The
ISB Informatics Core develops adaptable and flexible enterprise
systems to support large scale systems biology, these systems allow
for the integration and analysis of heterogeneous semantically rich
experiment information. Dr. Boyle has extensive experience within both
academic and the commercial sector, he has run a research group and
held senior software project manager positions at Synomics, Incyte
Pharmaceuticals and Life Science Informatics Solutions. His
professional experience includes the development of a number of
enterprise systems, and he has overseen the design and deployment of
these systems for a number of "top-ten" pharmaceutical companies.
Within academia his work has focused on medical and bioinformatics.
Talk Title: Supporting diverse cellular imaging experiments and analyses through the provision of adaptable enterprise software -part I
Abstract: The majority of scientific information systems are targeted towards the end results of research, rather than aiding in the progression of scientific understanding. The reason is that there is a dichotomy that exists between scientific understanding and scientific elucidation: understanding requires the presentation of a formalization of ideas while the elucidation requires the application of intuition and reasoning to extract meaning from a quandary of data. Therefore, to support elucidation, we must develop flexible systems which can be rapidly adapted for new usage, rather than trying to adopt a "one size fits all" solution. Within this talk we illustrate the requirements for such flexibility by discussing examples of systems biology work that has made extensive use of cellular microscopy. This work involves a large number of imaging platforms (including microfluidic devices and confocal microscopy) which were used to study a number of biological phenomena (including peroxisome biogenesis, p-body dynamics, and protein signaling). Automated image analysis is a key component of all these studies. The high-throughput nature of the imaging platforms sets substantial requirements for both the image analysis itself as well as to the collection, storage, and annotation of the image data. To support this work we are developing a loosely coupled enterprise system which is designed to be: adaptable, so that it can support the diverse analyses that commonly undertaken; flexible, to allow for the rapid integration of new (typically high throughput) data sources; and maintainable, as it is built on standards to support interoperability (with different environments, applications, instruments and programming languages). This system uses a middle-out approach, where instead of focusing on interfaces and data models, a strong identity system with associated life cycle services is used. With such a 'middle-out' approach "top-down" data models are not tightly bound to the individual data stores, so that scientists are free to independently develop the required analysis tools ("bottom-up" development).