In citing the ConSurf server please refer to

1. Ashkenazy H., Abadi S., Martz E., Chay O., Mayrose I., Pupko T., and Ben-Tal N. 2016
   ConSurf 2016: an improved methodology to estimate and visualize evolutionary conservation in macromolecules
   Nucl. Acids Res. 2016; DOI: 10.1093/nar/gkw408; PMID: 27166375 [ABS], [PDF]

2. Celniker G., Nimrod G., Ashkenazy H., Glaser F., Martz E., Mayrose I., Pupko T., and Ben-Tal N. 2013.
   ConSurf: Using Evolutionary Data to Raise Testable Hypotheses about Protein Function
   Isr. J. Chem. 2013 March 10, doi: 10.1002/ijch.201200096 [ABS], [PDF]

3. Ashkenazy H., Erez E., Martz E., Pupko T. and Ben-Tal N. 2010
   ConSurf 2010: calculating evolutionary conservation in sequence and structure of proteins and nucleic acids.
   Nucl. Acids Res. 2010; DOI: 10.1093/nar/gkq399; PMID: 20478830 [ABS], [PDF]

When using the server with protein structures (ConSurf method) please also refer to:

• Landau M., Mayrose I., Rosenberg Y., Glaser F., Martz E., Pupko T. and Ben-Tal N. 2005.
  ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures.
  Nucl. Acids Res. 33:W299-W302. [ABS], [PDF]

• Glaser F., Pupko T., Paz I., Bell R.E., Bechor D., Martz E. and Ben-Tal N. 2003.
  ConSurf: Identification of Functional Regions in Proteins by Surface-Mapping of Phylogenetic Information.
  Bioinformatics 19:163-164. [ABS], [PDF]

When using the server with sequence only (ConSeq method) please also refer to:

• Berezin C., Glaser F., Rosenberg J., Paz I., Pupko T., Fariselli P., Casadio R. and Ben-Tal N.
  ConSeq: The Identification of Functionally and Structurally Important Residues in Protein Sequences.
  Bioinformatics. Vol. 20 1322-1324, 2004. [PDF]

• Mayrose I., Graur D., Ben-Tal N. and Pupko T. 2004.
  Comparison of site-specific rate-inference methods for protein sequences: empirical Bayesian methods are superior.
  Mol. Biol. Evol. 21:1781-1791. PDF

• Pupko T., Bell R.E., Mayrose I., Glaser F. and Ben-Tal N. 2002.
  Rate4Site: an algorithmic tool for the identification of functional regions in proteins by surface mapping of evolutionary determinants within their homologues.
  Bioinformatics 18 Suppl 1:S71-S77. PDF

• Armon A., Graur D. and Ben-Tal N. 2001.
  ConSurf: An Algorithmic Tool for the Identification of Functional Regions in Proteins by Surface-Mapping of Phylogenetic Information.
  J. Mol. Biol. 307:447-463. PDF

• Martz E. 2005.
  FirstGlance in Jmol (firstglance.jmol.org)

• Martz E. 2002.
  Protein Explorer: easy yet powerful macromolecular visualization.
  Trends in Biochemical Sciences.27:107-109. (PDF available on request.)

• Pettersen, E.F., Goddard, T.D., Huang, C.C., Couch, G.S., Greenblatt, D.M., Meng, E.C., and Ferrin, T.E.
  UCSF Chimera - A Visualization System for Exploratory Research and Analysis.
  J. Comput. Chem. 25(13):1605-1612 (2004).
  

• Piero Fariselli and Rita Casadio.
  RCNPRED: prediction of the residue co-ordination numbers in proteins.
  Bioinformatics, 17, 202-204, 2001. (PDF)

• AS Rose and PW Hildebrand.
  NGL Viewer: a web application for molecular visualization.
  Nucl Acids Res, (1 July 2015) 43 (W1): W576-W579 first published online April 29, 2015. doi:10.1093/nar/gkv402. (ABS), (PDF)

• AS Rose, AR Bradley, Y Valasatava, JM Duarte, A Prlić and PW Rose.
  Web-based molecular graphics for large complexes.
  ACM Proceedings of the 21st International Conference on Web3D Technology (Web3D '16): 185-186, 2016. doi:10.1145/2945292.2945324 (ABS)

• Sali A., and Blundell T.L.
  Comparative protein modelling by satisfaction of spatial restraints.
  J. Mol. Biol. 234:779-815, 1993 (ABS)

• Meier A., and Söding J.
  Automatic prediction of protein 3D structures by probabilistic multi-template homology modeling.
  PLoS Comput. Biol. 11:e1004343; 2015 (ABS)

• Lorenz R., Bernhart S.H., Höner Zu Siederdissen C., Tafer H., Flamm C., Stadler P.F., and Hofacker I.L.
  ViennaRNA Package 2.0.
  Algorithms Mol. Biol. 6:26. 2011. (ABS)

Acknowledgements:

• We are grateful to the Bioinformatics Unit, the Life-Science IT Unit and the George S. Wise Faculty of Life Sciences at Tel Aviv University for providing technical assistance and computation facilities.

• The development was funded in part by Edmond J. Safra Center for Bioinformatics at Tel-Aviv university.

• Development of Protein Explorer was supported by a grant to Eric Martz from the US National Science Foundation, Division of Undergraduate Education.

• UCSF Chimera is developed by the Resource for Biocomputing, Visualization, and Informatics at the University of California, San Francisco (supported by NIH P41 RR-01081).