High-Performance Computing at the NIH
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The Helix Systems group is responsible for the planning and management of high-performance computing systems specifically for the intramural NIH community. These systems include Helix, a multiprocessor shared-memory system for interactive use; Biowulf, a 12,000+ processor Linux cluster; and Helixweb, which provides a number of scientific tools via the web. We provide access to a wide range of computational applications for molecular and structural biology, mathematical and graphical analysis, and other scientific fields.



Recent Publications Citing Helix and Biowulf:

thumbnail image from paper A Subset-Based Approach Improves Power and Interpretation for the Combined Analysis of Genetic Association Studies of Heterogeneous Traits
Samsiddhi Bhattacharjee, Preetha Rajaraman, Kevin B. Jacobs, William A. Wheeler, Beatrice S. Melin, Patricia Hartge, GliomaScan Consortium, Meredith Yeager, Charles C. Chung, Stephen J. Chanock, Nilanjan Chatterjee
Am. J. Human Genetics , doi:/10.1016/j.ajhg.2012.03.015 (2012)

thumbnail image from paper Seeing is believing: video classification for computed tomographic colonography using multiple-instance learning.
Shijun Wang, Matthew T McKenna, Tan B Nguyen, Joseph E Burns, Nicholas Petrick, Berkman Sahiner, Ronald M Summers
IEEE Transactions on Medical Imaging 31 (5) :1141 (2012)

thumbnail image from paper Cross-seeding and Conformational Selection between Three- and Four-repeat Human Tau Proteins
Xiang Yu, Yin Luo, Paul Dinkel, Jie Zheng, Guanghong Wei, Martin Margittai, Ruth Nussinov, Buyong Ma
J. Biol. Chem. , doi: 10.1074/jbc.M112.340794 (2012)

thumbnail image from paper An Integrative Segmentation Method for Detecting Germline Copy Number Variations in SNP Arrays
Jianxin Shi, Peng Li
Genetic Epidemiology 36(4) :373-383, DOI: 10.1002/gepi.21631 (2012)