MUSTA - A General, Efficient, Automated Method for Multiple Structure Alignment and Detection of Common Motifs: Application to Proteins-Reference-Cited by-同舟云学术

MUSTA - A General, Efficient, Automated Method for Multiple Structure Alignment and Detection of Common Motifs: Application to Proteins

Published:2001-04 Issue:2 Volume:8 Page:93-121
ISSN:1066-5277
Container-title:Journal of Computational Biology
language:en
Short-container-title:Journal of Computational Biology

Author:

Leibowitz Nathaniel¹,Nussinov Ruth²,Wolfson Haim J.¹

Affiliation:

1. School of Computer Science, Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv 69978, Israel

2. Sackler Institute of Molecular Medicine, Department of Human Genetics and Molecular Medicine, Sackler Faculty of Medicine, Tel Aviv University, Tel Aviv 69978, Israel; Intramural Research Support Program-SAIC, Laboratory of Experimental and Computational Biology, NCI - FCRDC, Building 469, Room 151, Frederick, MD 21702

Publisher

Mary Ann Liebert Inc

Subject

Computational Theory and Mathematics,Computational Mathematics,Genetics,Molecular Biology,Modeling and Simulation

Link

http://www.liebertpub.com/doi/pdf/10.1089/106652701300312896

Reference29 articles.

1. On the approximation of largest common subtrees and largest common point sets

2. Trees, Stars, and Multiple Biological Sequence Alignment

3. Least-Squares Fitting of Two 3-D Point Sets

4. A computer vision based technique for 3-D sequence-independent structural comparison of proteins

5. The protein data bank: A computer-based archival file for macromolecular structures

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