Hybrid Approches for Structure Prediction

Structural bioinformatics is an exceptionally cost effective solution for protein structure determination. Purely computational prediction methods, like ab initio fragment assembly, advanced fold recognition, composite approaches, and molecular docking are regularly applied today to extend our understanding of protein structures. However, predicted structures are not given the same reliance as their experimental complements. Hybrid approaches are a means to overcome these limitations; by incorporating limited experimental measurements, reliable structures can be computed and unlikely predictions eliminated. Hybrid approaches take advantage of data derived from a wide range of different biophysical and biochemical methods. These methods are of growing interest in current researches of structural biology

Relevant Conferences

International Conference on Biochemistry, October 10-12, 2016 Kuala Lumpur, Malaysia, USA; 7th International Conference on Proteomics, October 24-26, 2016 Rome, Italy; 3rd International Conference on Big Data Analysis and Data Mining, September 26-28, 2016 London, UK; 5th International Conference on Computational Systems Biology, August 22-23, 2016 Philadelphia, USA; International Conference on Nucleic Acids August 04-06, 2016 Seattle, USA; 253rd ACS National Meeting, April 02-06, 2017 San Francisco, USA; Conference on Membrane Transport Proteins, June 12-17, 2016 Lucca, Italy; Conference on Protein Folding Dynamics, January 10-15, 2016 Galveston, USA; 9th International Workshop on X-ray Radiation Damage to Biological Crystalline Samples, March 09-11 2016 Lund, Sweden; Biophysical Society’s 60th Annual Meeting, February 27-March 02 2016 Los Angeles, USA; 15th European Conference on Computational Biology, September 03-07 2016 The Hague, Netherlands; The 31st Symposium of The Protein Society, July 24-27, 2017 Montreal, Canada.

  • Hybrid of experimental methods
  • Hybrid of computational methods
  • Hybrid of experimental and computational methods

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