A practical approach to feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
Molecular scene analysis: crystal structure determination through imagery
Artificial intelligence and molecular biology
Detecting feature interactions from accuracies of random feature subsets
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Feature Extraction, Construction and Selection: A Data Mining Perspective
Feature Extraction, Construction and Selection: A Data Mining Perspective
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This paper reports on TEXTAL™, a deployed application that uses a variety of AI techniques to automate the process of determining the 3D structure of proteins by x-ray crystallography. The TEXTAL™ project was initiated in 1998, and the application is currently deployed in three ways: (1) a web-based interface called WebTex, operational since June 2002; (2) as the automated model-building component of an integrated crystallography software called PHENIX, first released in July 2003; (3) binary distributions, available since September 2004. TEXTAL™ and its sub-components are currently being used by crystallographers around the world, both in the industry and in academia. TEXTAL™ saves up to weeks of effort typically required to determine the structure of one protein; the system has proven to be particularly helpful when the quality of the data is poor, which is very often the case. Automated protein modeling systems like TEXTAL™ are critical to the structural genomics initiative, a worldwide effort to determine the 3D structure of all proteins in a high-throughput mode, thereby keeping up with the rapid growth of genomic sequence databases.