Publications (Google Scholar citations for GP here)

65. G.Tradigo, F.Cristiano, S.Alcaro, S.Greco, G.Pollastri, P.Veltri, M.Prosperi, "G-quadruplex Structure Prediction and integration in the GenData2020 data model", Proceedings of the 7th ACM International Conference on Bioinformatics, Computational Biology, and Health InformaticsSeattle, WA, USA. October 02 - 05, 2016, 663-670.
Abstract and PDF)

64. I.Walsh, G.Pollastri, S.C.E.Tosatto, "Correct machine learning on protein sequences: a peer-reviewing perspective", Briefings in Bioinformatics, 2015, doi: 10.1093/bib/bbv082.
Abstract and PDF (Briefings in Bioinformatics web site)

63. V.Volpato, B.Alshomrani, G.Pollastri, "Accurate ab initio and Template-Based Predictions of Short, Intrinsically Disordered Regions via Bidirectional Recurrent Neural Networks", International Journal of Molecular Sciences, 2015, 16(8), 19868-19885; doi:10.3390/ijms160819868
Abstract and PDF (IJMS web site)

62. C.Mirabello, A.Adelfio, G.Pollastri, "Reconstructing proteins by Neural Network Pairwise Interaction Fields and Iterative Decoy Set Construction", Biomolecules, 4(1), 160-180, 2014
Abstract and PDF (Biomolecules web site)

61. P.Kukic, C.Mirabello, G.Tradigo, I.Walsh, P.Veltri, G.Pollastri, "Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks", BMC Bioinformatics, 15:6, 2014
Abstract and PDF (BMC Bioinformatics web site)

60. A.Adelfio, V.Volpato, G.Pollastri, "SCLpredT: Ab initio and homology-based prediction of subcellular localization by N-to-1 Neural Networks", SpringerPlus, 2:502, 2013. DOI: 10.1186/2193-1801-2-502
Abstract and PDF (SpringerPlus web site)

59. T.A.Holton, G.Pollastri, D.C.Shields, C.Mooney, "CPPpred: Prediction of Cell Penetrating Peptides", Bioinformatics, (2013) doi: 10.1093/bioinformatics/btt518.
Abstract and PDF (Bioinformatics web site)

58. W.Khan, F.Duffy, G.Pollastri, D.C.Shields, C.Mooney, "Predicting Binding within Disordered Protein Regions to Structurally Characterised Peptide-Binding Domains", PLOS ONE, 8(9): e72838, 2013.
Abstract and PDF (PLOS ONE web site)

57. A.Lusci, G.Pollastri, P.Baldi, "Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules", Journal of Chemical Information and Modeling, 2013, doi: 10.1021/ci400187y
Abstract and PDF (JCIM web site)

56. C.Mirabello, G.Pollastri, "Porter, PaleAle 4.0: high-accuracy prediction of protein secondary structure and relative solvent accessibility", Bioinformatics, 29(16):2056-2058, 2013, doi: 10.1093/bioinformatics/btt344
Toll free PDF (Bioinformatics web site)

55. C.Mooney, A.Cessieux, D.Shields, G.Pollastri, "SCL-Epred: A Generalised De novo Eukaryotic Protein Subcellular Localisation Predictor", Amino Acids, 45(2), 291-9, 2013; doi: 10.1007/s00726-013-1491-3.
Abstract and PDF (Amino Acids web site)

54. C.Mooney, N.Haslam, T.Holton, G.Pollastri, D.Shields, "PeptideLocator: Prediction of Bioactive Peptides in Protein Sequences", Bioinformatics, 2013; doi: 10.1093/bioinformatics/btt103, 2013.
Abstract and PDF (Bioinformatics web site)

53. V.Volpato, A.Adelfio, G.Pollastri, "Accurate prediction of protein enzymatic class by N-to-1 Neural Networks", BMC Bioinformatics, 14(Suppl 1):S11, 2013.
HTML and PDF (BMC Bioinformatics web site)

52. C.Mooney, N.J.Haslam, G.Pollastri, D.C.Shields, "Towards the Improved Discovery and Design of Functional Peptides: Common Features of Diverse Classes Permit Generalized Prediction of Bioactivity", PLoS ONE, 7(10): e45012, 2012.
Abstract and PDF (PLoS ONE web site)

51. A.Lusci, I.Walsh, G.Pollastri, "Adaptive Virtual Screening of Drug-Like Molecules by Recursive Neural Networks for Undirected Graphs", iCBBE 2012 conference, 17-20 May 2012, Shanghai, China.
Provisional PDF

50. C.Mooney, G.Pollastri, D.C.Shields, N.J.Haslam, "Prediction of short linear protein binding regions", Journal of Molecular Biology, 415 (1), 193-204, 2011.
Abstract and PDF (JMB Web site)

49. C. Mooney, Y. Wang, G.Pollastri, "SCLpred: Protein Subcellular Localization Prediction by N-to-1 Neural Networks", Bioinformatics, 27 (20), 2812-2819, 2011.
Abstract and PDF (Bioinformatics web site)

48. G.Tradigo, P.Veltri, G.Pollastri, "Machine Learning approaches for Contact Map prediction in the CASP9 experiment", SEBD 2011 conference, 26-29 June 2011, Maratea, Italy.
Provisional PDF

47. I. Walsh, A.J.Martin, T. Di Domenico, A. Vullo , G.Pollastri, S.Tosatto, "CSpritz: accurate prediction of protein disorder segments with annotation for homology, secondary structure and linear motifs", Nucleic Acids Research,, 39(Suppl.2), W190-6, 2011.
Full text (NAR web site).

46. C. Mooney, Y. Wang, G.Pollastri, "De Novo Protein Subcellular Localization Prediction by N-to-1 Neural Networks", in Computational Intelligence Methods for Bioinformatics and Biostatistics, Lisboa and Rizzo eds., LNCS 6685, p31, Springer, 2011.

45. C. Mooney, N. Davey, A.J.M. Martin, I.Walsh, D.C.Shields, G.Pollastri, "In Silico Protein Motif Discovery and Structural Analysis", in In-Silico Tools in Gene Discovery, Methods in Molecular Biology, 760, 341-53, 2011.
Abstract and PDF (Springer web site).

44. A.J.M.Martin, C.Mirabello, G.Pollastri "Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment and Ab Initio Protein Folding" Current Protein and Peptide Science, 12(6), 549-62, 2011.
Abstract and PDF (CPPS web site).

43. P.Kukic, D.Farrell, U.Bjarnadottir, C.Søndergaard, G.Pollastri, J.E.Nielsen "Improving the analysis of NMR spectra tracking pH-induced conformational changes: Removing artefacts of the electric field on the NMR chemical shift" Proteins, 78(4), 971-84, 2010.
Abstract and PDF (Proteins web site).

42. A.J.M.Martin, C. Mooney, I.Walsh, G.Pollastri "Contact Map Prediction by Machine Learning" in Protein Structure Prediction, H.Rangwala and G.Karpys eds., Wileys, 2010.

41. C.Søndergaard, A.Garrett, T.Carstensen, G.Pollastri, J.E.Nielsen "Structural artefacts in protein-ligand X-ray structures: implications for the development of docking scoring functions" Journal of Medicinal Chemistry, 52(18), 5673-84, 2009.
Abstract and PDF (JMC web site).

40. I.Walsh, A.Vullo, G.Pollastri "Recursive Neural Networks for Undirected Graphs for learning molecular endpoints" Proceedings of the PRIB 2009 conference, Sep 7-9 2009, Sheffield, U.K., in LNCS, 5780/2009, 391-403.

39. I.Walsh, A.J.M.Martin, C. Mooney, E.Rubagotti, A.Vullo, G.Pollastri "Ab initio and homology based prediction of protein domains by recursive neural networks" BMC Bioinformatics, 10:195, 2009.
Open access abstract and PDF (BMC Bioinformatics web site).

38. I.Walsh, A.Vullo, G.Pollastri "An adaptive model for learning molecular endpoints" in Similarity-based learning on structures, M.Biehl, B.Hammer, S.Hochreiter, S.C Kremer and T.Villmann Eds., Dagstuhl Seminar Proceedings, Schloss Dagstuhl - Leibniz-Zentrum für Informatik, Germany, 2009.
Info and PDF (Dagstuhl seminars web site).

37. C. Mooney, G.Pollastri "Beyond the Twilight Zone: Automated prediction of structural properties of proteins by recursive neural networks and remote homology information" Proteins, 77(1), 181-90, 2009.
Abstract and PDF (Proteins web site)

36. I.Walsh, D.Baú, A.J.M.Martin, C. Mooney, A.Vullo, G.Pollastri "Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks" BMC Structural Biology, 9:5, 2009.
Open access abstract and PDF (BMC Structural Biology web site).

35. A.J.M.Martin, A.Vullo, G.Pollastri. "Neural Network Pairwise Interaction Fields for protein model quality assessment" Proceedings of the LION3 conference, Jan 14-18 2009, Trento, Italy (LNCS 5851).
Provisional PDF (conference web site).

34. Q.Le, G.Pollastri, P.Koehl. "Structural Alphabets for Protein Structure Classification: a Comparison Study" Journal of Molecular Biology, 387(2), 431-450, 2009.
Abstract and PDF (JMB web site)

33. D.Baú, I.Walsh, G.Pollastri*, A.Vullo. "Fast Modeling of Protein Structures Through Multi-level Contact Maps" in Computational Biology: New Research, Alona S. Russe editor, Nova Publishers, 2008.
Book web site

32. A.J.M.Martin, D.Baú, I.Walsh, A.Vullo, G.Pollastri. "Long-range information and physicality constraints improve predicted protein contact maps" Journal of Bioinformatics and Computational Biology, 6(5):1001-20, 2008.
Abstract and PDF

31. J.Cheng, Z.Wang, G.Pollastri. "A Neural Network Approach to Ordinal Regression" IJCNN2008, Hong Kong, 1-6 June 2008.
PDF

30. C.R.Søndergaard, J.P.McIntosh, G.Pollastri, J.E.Nielsen. "Determination of electrostatic interaction energies and protonation state populations in enzyme active sites" Journal of Molecular Biology, 376(1):269-87, 2008.

29. A. Vullo, A. Passerini, P. Frasconi, F. Costa, G. Pollastri. "On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways" Proceedings of the EVOBIO 2008 (acceptance 29%), Naples, Italy 26-28 March 2008, in LNCS 4973/2008, 200-11.
PDF

28. D. Baú, G. Pollastri, A. Vullo*. "Distill: a machine learning approach to ab initio protein structure prediction" in Analysis of Biological Data: A Soft Computing Approach, S. Bandyopadhyay, U. Maulik and J. T. L. Wang eds., World Scientific, 2007.
Book web site

27. G.Pollastri*, A. J. M. Martin, C. Mooney, A. Vullo. "Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information" BMC Bioinformatics, 8:201, 2007.
Open access abstract and PDF (BMC Bioinformatics web site).

26. D. Baú, A. J. M. Martin, C. Mooney, A. Vullo, I. Walsh, G. Pollastri*. "Distill: A suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins" BMC Bioinformatics, 7:402, 2006.
Open access abstract and PDF (BMC Bioinformatics web site).

25. C. Mooney, A. Vullo, G. Pollastri*. "Protein Structural Motif Prediction in Multidimensional φ-ψ Space leads to improved Secondary Structure Prediction" Journal of Computational Biology, 13:8, 1486-1502, 2006.
Abstract and PDF (JCB web site).

24. A. Vullo, O. Bortolami, G. Pollastri*, S. Tosatto. "Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines" Nucleic Acids Research, 34:W164-W168, 2006.
Open access abstract and PDF (Nucleic Acids Research web site).

23. A. Vullo, I. Walsh, G. Pollastri*. "A two-stage approach for improved prediction of residue contact maps" BMC Bioinformatics, 7:180, 2006.
Open access abstract and PDF (BMC Bioinformatics web site).

22. G. Pollastri*, A. Vullo, P. Frasconi, P. Baldi. "Modular DAG-RNN Architectures for Assembling Coarse Protein Structures" Journal of Computational Biology, 13:3, 631-650, 2006.
Abstract and PDF (JCB web site).

21. A. Ceroni, P. Frasconi, G. Pollastri. "Learning Protein Secondary Structure from Sequential and Relational Data" Neural Networks, 18(8):1029-39, special issue on Neural Networks and Kernel Methods for Structured Domains, 2005.
Download Abstract and PDF (Science Direct)

20. G. Pollastri*, A. McLysaght. "Porter: a new, accurate server for protein secondary structure prediction" Bioinformatics, 21(8):1719-20, 2005.
Download Abstract and PDF (toll-free link, Bioinformatics web site)

19. Y. Dou, P. Baisnee, G. Pollastri, Y. Pecout, J. Nowick, and P. Baldi. "ICBS: A Database of Protein-Protein Interactions Mediated by beta-Sheet Formation", Bioinformatics, 20, 2767-2777, 2004.
Download PDF (Bioinformatics web site)

18. Y.Guermeur, G. Pollastri, A.Eliseeff, D.Zelus, H. Paugam-Moisy, P.Baldi. "Combining Protein Secondary Structure Prediction Models With Ensemble Methods of Optimal Complexity", Neurocomputing, 56C, 305-327, 2004.
Download PDF

17. P. Baldi, G. Pollastri. "The Principled Design of Large-Scale Recursive Neural Network Architectures -- DAG-RNNs and the Protein Structure Prediction Problem", Journal of Machine Learning Research 4(Sep):575-602, 2003.
Download PDF, HTML abstract (JMLR web site).

16. G. Pollastri, P. Baldi, A. Vullo, P. Frasconi. "Prediction of Protein Topologies Using GIOHMMs and GRNNs", Advances in Neural Information Processing Systems (NIPS) 15, MIT Press, 2003.
Download PDF

15. P.Baldi, G.Pollastri, P.Frasconi, and A.Vullo. "New Machine Learning Methods for the Prediction of Protein Topologies", in Artificial Intelligence and Heuristic Methods in Bioinformatics, P. Frasconi and R. Shamir Editors, IOS Press, 2003.
Download PDF.

14. G.Pollastri, P.Baldi. "Prediction of Contact Maps by Recurrent Neural Network Architectures and Hidden Context Propagation from All Four Cardinal Corners", Bioinformatics, 18 Suppl 1, S62-S70, 2002.
Download HTML and PDF (Bioinformatics web site).

13. P.F. Baisnee, G. Pollastri, P.F. Baldi, J.S. Nowick. "Identification of protein-protein interactions mediated by interchain beta-sheet formation" Abstracts of Papers of the American Chemical Society, 224: 054-BIOL Part 1 AUG 18, 2002.

12. P.Baldi, G.Pollastri. "A Machine-Learning Strategy for Protein Analysis", IEEE Intelligent Systems (Intelligent Systems in Biology II), 17, 2, 28-35, 2002.
Download PDF

11. G.Pollastri, P.Baldi, P.Fariselli, R.Casadio. "Prediction of Coordination Number and Relative Solvent Accessibility in Proteins", Proteins, 47, 142-153, 2002.
Download PDF, Abstract and HTML (Proteins web site)

10. G.Pollastri, D.Przybylski, B.Rost, P.Baldi. "Improving the Prediction of Protein Secondary Structure in Three and Eight Classes Using Recurrent Neural Networks and Profiles", Proteins, 47, 228-235, 2002.
Download PDF, Abstract and HTML (Proteins web site)

9. G.Pollastri, P.Baldi, P.Fariselli, R.Casadio. "Improved Prediction of the Number of Residue Contacts in Proteins by Recurrent Neural Networks", Bioinformatics, 17 Suppl 1, S234-S242, 2001.
Download HTML and PDF (Bioinformatics web site).

8. P.Baldi, S.Brunak, P.Frasconi, G.Pollastri, and G.Soda. "Bidirectional Dynamics for Protein Secondary Structure Prediction", in Sequence Learning: Paradigms, Algorithms, and Applications (LNCS), R. Sun and L. Giles Editors, Springer Verlag, 2000.
Download PDF, Abstract (Book web site)

7. P.Baldi, G.Pollastri, C.A.F. Andersen, and S. Brunak. "Matching Protein beta-Sheet Partners by Feedforward and Recurrent Neural Networks". Proceedings of the 2000 Conference on Intelligent Systems for Molecular Biology, (ISMB 2000), La Jolla, CA, AAAI Press, 2000.

6. P.Baldi, S.Brunak, P.Frasconi, and G.Pollastri. "Bidirectional IOHMMs and recurrent neural networks for protein secondary structure prediction". Protein Sequence Analysis in the Genomic Era, Rita Casadio and Lanfranco Masotti Editors, CLUEB, Bologna, Italy, 2000.

5. P.Baldi, G.Pollastri, C.A.F. Andersen, and S. Brunak. "Protein beta-Sheet Partner Prediction by Neural Networks". In: Artificial Neural Networks in Medicine and Biology. Proceedings of the ANNIMAB-1 Conference (LNCS), Göteborg, Sweden, H. Malmgren, M. Borga and L. Niklasson Editors, Springer Verlag, 2000.

4. P.Baldi, S.Brunak, P.Frasconi, G.Soda and G.Pollastri. "Exploiting the Past and the Future in Protein Secondary Structure Prediction", Bioinformatics, 15, 937-946, 1999.
Download HTML and PDF (Bioinformatics web site).

3. P.Baldi, S.Brunak, P.Frasconi, G.Pollastri, and G.Soda. "Bidirectional Dynamics for Protein Secondary Structure Prediction", Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence (IJCAI99), Stockholm, Sweden, 1999.

2. Gianluca Pollastri. "Modelli Connessionistici non causali per l'analisi di sequenze e loro impiego nella classificazione delle proteine", AI*IA Notizie, XII, 4, 5-9, 1999.

1. Gianluca Pollastri. "Risoluzione dei giochi dell'8 e del 15 con algoritmo IDA* e funzione euristica calcolata mediante MLP", AI*IA Notizie, X, 3bis, 14-17, 1997.


Conference/Workshop abstracts

18. C.Mirabello, A.Adelfio, G.Pollastri, "Distill for CASP11", CASP11 (2014), Riviera Maya, Mexico.
PDF

17. C.Mirabello, G.Tradigo, G.Pollastri, "Distill for CASP10", CASP10 (2012), Gaeta, Italy.
PDF

16. C.Mirabello, G.Tradigo, G.Pollastri, "Distill: protein structure prediction by Machine Learning", CASP9 (2010), Asilomar, California.
PDF

15. Q.Le, P. Koehl, G.Pollastri, "Combining Kernels for SVM-based Classification of protein structral sequences", ISMB 2009, Stockholm, Sweden.

14. A.J.M.Martin, G.Pollastri, "Neural Network Pairwise Interaction Fields for protein model quality assessment", ISMB 2009, Stockholm, Sweden.

13. A.J.M.Martin, D.Baú, C.Mooney, C.Roche, E.Rubagotti, A.Vullo, I.Walsh, G.Pollastri, "Protein structural features prediction and modelling of Cα traces through predicted structural constraints", CASP8, Cagliari, Italy

12. C.Mooney, G.Pollastri, "Automated prediction of protein backbone structural motifs by recursive neural networks and remote homology information", ECCB 2008, Cagliari, Italy.

11. C.Mooney, A.J.M.Martin, A.Vullo, G.Pollastri, "Exploiting similarity to proteins of known structure leads to improved protein structural motif prediction", ISMB 2007, Vienna, Austria.

10. E.Rubagotti, I.Walsh, G.Pollastri, "Domain prediction using exons", ISMB 2007, Vienna, Austria.

9. D.Baú, A. Vullo, G. Pollastri, "A new neural network ranker to evaluate protein structure prediction", ISMB 2007, Vienna, Austria.

8. C.Søndergaard, L.P.McIntosh, G.Pollastri, J.E.Nielsen, "Determination of electrostatic interaction energies and protonation state populations in enzyme active sites by global fits of NMR titration data and pH-activity profiles", 21st Annual Symposium of The Protein Society, Boston, U.S.A. (selected for Young Protein Scientist Talk)

7. M. A. Murphy, F. Furlong, N. G. Docherty, J. Howlin, E. McArdle, G. Pollastri, A. Droguette, S. Mezzano, H. Brady, B. Griffin, C. Godson, F. Martin, "A mitochondrial protein that amplifies TGF-beta signaling is upregulated in diabetic nephropathy", World Congress of Nephrology, Rio de Janeiro, Brazil, April 2007.

6. D.Baú, A.J.M.Martin, C.Mooney, A.Vullo, I.Walsh, G.Pollastri, "Modelling of protein Cα traces through residue contact maps predicted by machine learning", CASP7, Asilomar, California, U.S.A.

5. C. Mooney, A. Vullo, G. Pollastri, "Porter+: A server for protein structural motif prediction", ISMB 2006, Fortaleza, Brazil.

4. I. Walsh, A. Vullo, G. Pollastri, "XXStout: Improving the Prediction of Long range residue contacts", ISMB 2006, Fortaleza, Brazil.

3. D.Baú, A. Vullo, G. Pollastri, "Ab initio modelling of protein Cα traces through residue contact maps predicted by machine learning", ISMB 2006, Fortaleza, Brazil.

2. A. J. M. Martin, A. Vullo, G. Pollastri, "A Filtering Approach for Improved Modelling of Predicted Contact Maps", ISMB 2006, Fortaleza, Brazil.

1. D.Baú, A. Vullo, G. Pollastri, "Ab initio modelling of protein Cα traces through residue contact maps predicted by machine learning", MGMS International Meeting 2005, Dublin, Ireland.


Technical reports

6. A.Lusci, G.Pollastri. "Pairwise Interaction Field Neural Networks For Drug Discovery", Technical Report UCD-CSI 2013-02
PDF

5. W.Khan, F.Duffy, G.Pollastri, D.C.Shields, C.Mooney. "Potential utility of docking to identify protein-peptide binding regions", Technical Report UCD-CSI 2013-01
PDF

4. D.Bau, G.Pollastri. "A New Neural Network Ranker to Evaluate Protein Structure Predictions", Technical Report UCD-CSI 2012-03
PDF

3. A. Vullo, C.P.Roche, G.Pollastri. "Template-based Recognition of Natively Disordered Regions in Proteins", Technical Report UCD-CSI 2012-01
PDF

2. C. Mooney, A. Vullo, G. Pollastri. "Protein Backbone Angle Prediction in Multidimensional φ-ψ Space", Technical Report UCD-CSI-2006-1.
PDF

1. P. Baisnee, G. Pollastri, Y. Pecout, P. Baldi. "ICBS: A Database of Protein-Protein Interactions Mediated by β-Sheet Formation", Technical Report SICS-UCI, 2003.