Visual Analysis of Chemical Data
239th ACS National Meeting
San Francisco, March 21-25, 2010
CINF Division
Dear Colleagues,
We are now accepting papers for an upcoming symposium focusing on innovative methods for visual representation and analysis of chemical data. Just as Edward Tufte has championed maximizing clarity and information content in statistical graphics, there is a need for methods to display chemical information that will maximize understanding, and allow rapid analysis and decision making.
We invite you to submit contributions that address various aspects of visualization of chemical data (such as structures, SAR data, literature, patents) including, but not limited to, the following topics:
- With an ever increasing pool of descriptors, along with new and more sophisticated machine learning methods, QSAR models are becoming more difficult to interpret. How can information on model reliability, the presence of activity cliffs, and the range of applicability of a model and other relevant model properties be easily depicted?
- Recently, virtual worlds 3D such as Second Life have presented new opportunities and challenges for the representation of chemical data. What is the potential of such a medium in education and communicating with the chemistry community?
- Social software allows for rapid and convenient sharing of chemical data. Examples include Google Spreadsheets, ManyEyes, DabbleDB, and wikis, including Wikipedia. What are the implications for chemical research and education?
- The visualization of the contents of large chemical datasets presents particular problems. How can an overview of the dataset be visualized so that it presents both the nature of the contents as well as the degree of diversity and similarity within the dataset? How can different datasets be visually compared?
- Depicting 3D chemical information in 2D involves a loss of information. However, innovative 2D visualization methods can restore the most relevant information.
- Chemical information comprises a diverse array of data types including chemical structures and diagrams (2D and 3D), associated assay results, conformations, QSAR models and their predictions. The visualization and integration of all these data into a single interface that aids interpretation and analysis is a continuing challenge.
We would also like to point out that sponsorship opportunities are available.
The on-line abstract submission system (PACS) is now open for submissions until 19th October.
Please contact Andrew, Jean-Claude or myself if you have any questions.
Yours sincerely,
Noel O'Boyle
On behalf of the symposium organizers:
Dr. Jean-Claude Bradley,
Drexel University, PA
bradlejc@drexel.edu
Dr. Andrew Lang,
Oral Roberts University, OK
alang@oru.edu
Dr. Noel O’Boyle,
University College Cork, Ireland
n.oboyle@ucc.ie
Image credit: prehensile
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