Conferences and Publications

From Chemical Informatics and Cyberinfrastructure Collaboratory

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Conferences

In reverse chronological order, with active entries (submissions or presentations pending) first and in bold.

Fall 2006 ACS San Francisco
- Advanced HTS data mining using web service workflows. (David Wild, Advances in Virtual HTS section). We will discuss the application of web services and workflows of these services in advanced data mining of HTS data. We have worked with HTS data from a number of sources, including the NIH DTP human tumor cell lines and MLSCN data from PubChem. Our workflows are able to find relationships and correlations of the HTS data using a wide variety of computational techniques, including docking, machine learning, similarity searching, and inclusion of genomic data. We are able to use models built from these analyses and workflows to provide virtual HTS environments within an information system targeted to particular disease areas.
- Submission for Guenter Grether's infrastructure session?
CompLife 06
- Sumbit joint IU/Cambridge abstract?
August 2006 Presentation to Microsoft eScience on Smart Mining for Drug Discovery Information
ACS Central Regional Meeting, May 18, 2006
- Mopping up the flood of data with web services. Gary Wiggins, Knowledge Management/Data Mining Symposium). The core of informatics is the relationships between the meaning of information and its representation as data. Our burgeoning ability to both generate and collect scientific information has created a number of challenges. The principal challenges are how to extract meaningful, sometimes latent, novel information and how to manage the information. The new field of Knowledge Discovery in Databases (KDD) seeks to provide answers to both of these problems. Data mining involves a strong machine-learning component to semi-automatically detect information that is useful. Unfortunately for the scientist, there is no set of standard tools at their disposal to conduct data mining. Furthermore, the sophisticated creation of algorithms, heuristics and their implementation is generally outside the expertise of scientists. Another distinguishing characteristic of scientific information is the much greater role played by "metadata" (data about data). The metadata problem has long vexed scientific information. With a fixed table approach, programs must be rewritten frequently to keep pace with changes in data representations. The huge increase in data volumes that stream from modern laboratory instruments has magnified the problems. Informatics schools train students to deal with scientific data handling problems, utilizing not only locally generated data, but the full spectrum of databases and resources available on the Web. Indiana University's approach to a Chemical Informatics and Cyberinfrastructure Collaboratory will be presented as an example of one solution to the data deluge problem.
Spring 2006 ACS Atlanta - papers by Xiao Dong and Huijun Wang on Web Services Infrastructure and NIH Data Mining respectively

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Outreach Activities

August / September 2006 Industry Day to showcase our work - include computer industry (Sun, IBM, HP) and Pharma (Pfizer, Lilly, etc)
April 11, 2006. Bridging Bioinformatics and Chemical Informatics. Lecture by Gary Wiggins at Eli Lilly and Company, Greenfield.

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