Emidio Capriotti e-mail: emidio.capriotti@gmail.com              emidio@stanford.edu              emidio.capriotti@uib.es

• Protein structural prediction by threading method and building by homology.
• Molecular dynamics of protein systems.
• Prediction of protein stability changes upon mutation.
• Prediction of disease-related SNP.
• Protein folding kinetics.
• RNA structure comparison and prediction.

• Jul 1999: Degree in Physics at the University of Bologna.
• Stochastic dynamics in protein folding.
• Jun 2004: Ph.D. in Physics at the University of Bologna.
• Computational methods for protein folding
• Sep 2004: Master in Bioinformatic at the University of Bologna (First level).

• Sep 2009 - Marie-Curie IOF: Postdoctoral Researcher at the Helix Group, Department of Bioengineering, Stanford University. and
  
• Sep 2009 - Researcher at the Department of Mathematics and Computer Sciences, University of Balearic Islands (UIB).

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• Sep 2001 - Aug 2002: SPINNER Consortium Research Fellowship (Regione Emilia-Romagna and University of Bologna)
• Jen 2003 - May 2004: INBB Fellowship (Istituto Nazionale Biostrutture Biosistemi)
• Sep 2004 - Sep 2006: Contract Researcher BioSapiens Network of Excellence
• Oct 2006 - Aug 2009: Postdoctoral Researcher at Structural Genomics Unit Bioinformatics and Genomics Department (CIPF).

• 2001 - 2002: Laboratory of Biophysics II - University of Bologna
• 2002 - 2003: Structural Biochemistry - University of Bologna
• 2003 - 2004: Laboratory of Biophysics II and Models for Biological Systems - University of Bologna
• 2004 - 2005: Bioinformatics - University of Bologna
• 2004 - 2005: Laboratory of Bioinformatics I - University of Bologna

Developed Web Predictors and Databases

• I-Mutant1.0: Neural Network based method to predict the sign of free energy change of proteins upon single point mutation.
• I-Mutant2.0: Support Vector Machine based method to predict the sign and the value of free energy change of proteins upon single point mutation.
• PhD-SNP: Support Vector Machine based-method to discriminate between neutral or disease-related single point protein mutations.
• K-Fold: Support Vector Machine based method to predict the mechanism and rate of protein folding kinetic.
• Omidios: Omidios, a database of pre-caluclated likely impact of a Single Nucleotide Polymorphism in the human genome.
SNPs&GO: Support Vector Machine based method for the prediction of disease-related SNPs using GO terms
• SARA: Structural Alignment of Ribonucleic Acids.

Selected Publications

2004
• Capriotti E, Fariselli P, Rossi I, Casadio R (2004). A Shannon entropy-based filter detects high-quality profile-profile alignments in searches for remote homologues. Proteins 54: 351-360.
• Compiani M, Capriotti E, Casadio R. (2004). The Dynamics of the Minimally Frustrated Helices Determine the Hierarchical Folding of Small Helical Proteins. Phys. Rev. E 65.
• Capriotti E, Fariselli P, Casadio R. (2004). A neural network-based method for predicting protein stability changes upon single point mutations. Bioinformatics Suppl 1: I63-I68.
  

2005
• Stizza A, Capriotti E, Compiani M. (2005). A Minimal Model of Three-State Folding Dynamics of Helical Proteins. J. Phys. Chem. B 109: 4215-4226.
  
• Capriotti E, Fariselli P, Casadio R. (2005) I-Mutant2.0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic Acids Res. 33(Web Server issue): W306-W310.
  
• Capriotti E, Fariselli P, Calabrese R, Casadio R. (2005) Predicting protein stability changes from sequences using support vector machines.Bioinformatics 21: ii54-ii58.
  

2006
• Capriotti E, Compiani M. (2006) Diffusion-collision of foldons elucidates the kinetic effects of point mutations and suggests control strategies of the folding process of helical proteins. Proteins 64: 198-209.
  
• Capriotti E, Calabrese R, Casadio R. (2006) Predicting the insurgence of human genetic diseases associated to single point protein mutations with support vector machines and evolutionary information. Bioinformatics 22: 2729-2734.
  
• Grandi F, Sandal M, Guarguaglini G, Capriotti E, Casadio R, Samori B. (2006) Hierarchical Mechanochemical Switches in Angiostatin. Chembiochem. 7: 1774-1782.
  

2007
• Fariselli P, Rossi I, Capriotti E, Casadio R. (2007) The WWWH of remote homolog detection: The state of the art. Brief. Bioinform. 8: 78-87.
  
• Capriotti E, Casadio R. (2007) K-Fold: a tool for the prediction of the protein folding kinetic order and rate. Bioinformatics 23: 385-386.
  

2008
• Bartoli L, Capriotti E, Fariselli P, Martelli PL, Casadio R (2008). The pros and cons of predicting protein contact maps. Methods Mol. Biol. 413: 199-218.
  
• Capriotti E, Arbiza L, Casadio R, Dopazo J, Dopazo H, Marti-Renom MA. (2008). The use of estimated evolutionary strength at the codon level improves the prediction of disease related protein mutations in human. Human Mutation 29: 198-204.
  
• Capriotti E, Marti-Renom MA. (2008). Computational RNA structure prediction. Current Bioinformatics 3: 32-45.
  
• Capriotti E, Fariselli P, Rossi I, Casadio R. (2008). A three-state prediction of single point mutations on protein stability changes. BMC Bioinfomatics. 9 (Suppl 2): S6.
  
• Capriotti E, Marti-Renom M. (2008) RNA structure alignment by a unit-vector approach. Bioinformatics, 24; i112-i116.
  
2009
• Capriotti E, Marti-Renom MA. (2009). SARA: a server for function annotation of RNA structures. Nucleic Acids Res. 37(Web Server issue); W260-W265.
  
• Calabrese R, Capriotti E, Fariselli P, Martelli PL, Casadio R. (2009). Functional annotations improve the predictive score of human disease-related mutations in proteins. Human Mutation. 30; 1237-1244.
  
2010
• Capriotti E, Marti-Renom MA. (2010). Quantifying the relationship between sequence and three-dimensional structure conservation in RNA . BMC Bioinformatics. 11; 322.
  
2011
• Bau D, Sanyal A, Lajoie BR, Capriotti E, Byron M, Lawrence JB, Dekker J, Marti-Renom MA. (2011). The three-dimensional folding of the alpha-globin gene domain reveals formation of chromatin globules. Nat Struct Mol Biol. 18:107-114.
  
• Capriotti E, Norambuena T, Marti-Renom MA, Melo F. (2011). All atom knowledge-based potential for RNA structure prediction and assessment. Bioinformatics. 27; 1086-1093.
  
• Liu T, Tang GW, Capriotti E. (2011). Comparative modeling: the state of the art and protein drug target structure prediction. Combinatorial Chemistry & High Throughput Screening. 14; 532-547.
  
• Fernald GH, Capriotti E, Daneshjou R, Karczewski KJ, Altman RB. (2011). Bioinformatics challenges for personalized medicine. Bioinformatics. 27: 1741-1748.
  
• Capriotti E, Altman RB. (2011). Improving the prediction of disease-related variants using protein three-dimensional structure. BMC Bioinformatics. 12 (Suppl 4): S3.
  
• Capriotti E, Altman RB. (2011). A new disease-specific machine learning approach for the prediction of cancer-causing missense variants. Genomics. Epub.