Large-scale testing of chemical shift prediction algorithms and improved machine learning-based approaches to shift prediction

Proceedings - 2004 IEEE Computational Systems Bioinformatics Conference, CSB 2004

Volumn , Issue , 2004, Pages 712-713

  Arun, K ^b   Langmead, Christopher James ^a,b  

^a Carnegie Mellon University   (United States)

^b CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PROTEIN DATA BANK (PDB); ROOT MEAN SQUARE ERROR (RMSE); SHIFT PREDICTION PROGRAMS; SUPPORT VECTOR MACHINES (SVM);

ALGORITHMS; AMINO ACIDS; DATABASE SYSTEMS; LARGE SCALE SYSTEMS; LEARNING SYSTEMS; NUCLEAR MAGNETIC RESONANCE; SIGNAL FILTERING AND PREDICTION; VECTORS;

PROTEINS;

EID: 14044270763     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (4)

1. J. Meiler. PROSHIFT Protein chemical shift prediction using artificial neural networks. J. Biomol. NMR, 26:25-37, 2003.
2. 15N chemical shifts. J. Biomol. NMR, 26:215-240, 2003.
3. 13C′ chemical shifts in proteins using a density functional database. J. Biomol. NMR, 21:321-333, Dec 2001.
4. H. Zhang, S. Neal, and D. S. Wishart. RefDB: A database of uniformly referenced protein chemical shifts. J. Biomol. NMR, 25:173-195, 2003.