Graphic Encoding of Macromolecules for Efficient High-Throughput Analysis-Reference-Cited by-同舟云学术

Graphic Encoding of Macromolecules for Efficient High-Throughput Analysis

Published:2018-08-15 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2018 ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics
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Author:

Estrada Trilce¹,Benson Jeremy¹,Carrillo-Cabada Hector¹,Razavi Asghar M.²,Cuendet Michel A.²,Weinstein Harel²,Deelman Ewa³,Taufer Michela⁴

Affiliation:

1. University of New Mexico, Albuquerque, NM, USA

2. Weill Cornell Medical College, Cornell University, New York, NY, USA

3. University of Southern California, Los Angeles, CA, USA

4. University of Tennessee at Knoxville, Knoxville, TN, USA

Funder

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3233547.3233607

Reference44 articles.

1. Gene Ontology: tool for the unification of biology

2. A Parallel Implementation of the Needleman-Wunsch Algorithm for Global Gapped Pair-wise Alignment;David Barkan;J. Comput. Sci. Coll.,2002

3. Helen Berman Kim Henrick and Haruki Nakamura . 2003. Announcing the worldwide Protein Data Bank. Nature Structural Biology Vol. 980 10 (2003). Helen Berman Kim Henrick and Haruki Nakamura . 2003. Announcing the worldwide Protein Data Bank. Nature Structural Biology Vol. 980 10 (2003).

4. Helen Berman John Westbrook Zukang Feng Gary Gilliland T. N. Bhat Helge Weissig Ilya N. Shindyalov and Philip E. Bourne . 2000. Nucleic Acids Research. Nature Structural Biology Vol. 28 1 (2000). Helen Berman John Westbrook Zukang Feng Gary Gilliland T. N. Bhat Helge Weissig Ilya N. Shindyalov and Philip E. Bourne . 2000. Nucleic Acids Research. Nature Structural Biology Vol. 28 1 (2000).

5. Marenglen Biba Floriana Esposito Stefano Ferilli Teresa M. A. Basile and Nicola Di Mauro . 2007. Multi-class Protein Fold Recognition Through a Symbolic-Statistical Framework. Springer Berlin Heidelberg Berlin Heidelberg 666--673. 10.1007/978-3-540-73400-0_85 Marenglen Biba Floriana Esposito Stefano Ferilli Teresa M. A. Basile and Nicola Di Mauro . 2007. Multi-class Protein Fold Recognition Through a Symbolic-Statistical Framework. Springer Berlin Heidelberg Berlin Heidelberg 666--673. 10.1007/978-3-540-73400-0_85

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