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Gianluca Pollastri

Gianluca Pollastri

Biography

Research Interests:
General
My Photograph
Name and Title: 
Dr Gianluca Pollastri MSC PhD
Position: 
Senior Lecturer
Phone: 
+353 1 716 5382
Email: 
Office: 
CASL / 3J
Address:
School of Computer Science &
Informatics
UCD Casl
Belfield Office Park, Dublin 4

Biography

Since September 2003 I've been a College Lecturer (and Senior Lecturer since October 2008) in the School of Computer Science and Informatics at University College Dublin. Before then I was a working in Pierre Baldi's group at University of California, Irvine, where it was a little bit dryer than in Dublin, but Guinness tasted remarkably foul.
I am the head of the AmMBio lab, which has employed up to two postdoctoral fellows and ten postgraduate students, funded through a number of grants from Science Foundation Ireland, the Health Research Board of Ireland, the Irish Research Council for Science, Engineering and Technology (IRCSET) and UC Dublin.

Professional

Education:

  • Year 1999 Institution: University of Florence
    Qualification: MSc Subject:
  • Year 2003 Institution: Uni of California, Irvine, CA
    Qualification: PhD Subject:

Publications

Book Chapters:

  • C. Mooney, N. Davey, A.J.M. Martin, I.Walsh, D.C.Shields, G.Pollastri (2011) 'In Silico Protein Motif Discovery and Structural Analysis' In: In Silico Tools for Gene Discovery. -: Springer. [Details]
  • C. Mooney, Y. Wang, G.Pollastri (2011) 'De Novo Protein Subcellular Localization Prediction by N-to-1 Neural Networks' In: Computational Intelligence Methods for Bioinformatics and Biostatistics. -: Springer. Available Online [Details]
  • A.J.M.Martin, C. Mooney, I.Walsh, G.Pollastri (2010) 'Contact Map Prediction by Machine Learning' In: H.Rangwala and G.Karpys (eds). Protein Structure Prediction. Wiley's. [Details]
  • Ian Walsh, Alessandro Vullo, Gianluca Pollastri (2009) 'Recursive Neural Networks for Undirected Graphs for Learning Molecular Endpoints' In: Pattern Recognition in Bioinformatics. Heidelberg: Springer. [DOI] [Details]
  • Bau, D. and Walsh, I. and Pollastri, G. and Vullo, A. (2009) 'Fast Modeling of Protein Structures Through Multi-level Contact Maps' In: Alona S. Russe (eds). Computational Biology: New Research. Hauppauge, New York: Nova Publishers. [Details]
  • G.Pollastri, D.Bau, A.Vullo (2007) 'Distill: a machine learning approach to ab initio protein structure prediction' In: S. Bandyopadhyay, U. Maulik and J. T. L. Wang (eds). Analysis of Biological Data: A Soft Computing Approach. London: World Scientific. Available Online [Details]
  • P.Baldi, G.Pollastri, P.Frasconi, and A.Vullo (2003) 'New Machine Learning Methods for the Prediction of Protein Topologies' In: P. Frasconi and R. Shamir (eds). Artificial Intelligence and Heuristic Methods in Bioinformatics. Amsterdam: IOS press. [Details]
  • P.Baldi, G.Pollastri, C.A.F. Andersen, and S. Brunak (2000) 'Protein β-Sheet Partner Prediction by Neural Networks' In: H. Malmgren, M. Borga and L. Niklasson (eds). Artificial Neural Networks in Medicine and Biology (proceedings of the ANNIMAB-1 Conference, Göteborg, Sweden). New York: Springer Verlag. Available Online [Details]
  • P.Baldi, S.Brunak, P.Frasconi, and G.Pollastri (2000) 'Bidirectional IOHMMs and recurrent neural networks for protein secondary structure prediction' In: Rita Casadio and Lanfranco Masotti Editors (eds). Protein Sequence Analysis in the Genomic Era. Bologna: CLUEB. [Details]
  • P.Baldi, S.Brunak, P.Frasconi, G.Pollastri, and G.Soda (2000) 'Bidirectional Dynamics for Protein Secondary Structure Prediction' In: R. Sun and L. Giles (eds). Sequence Learning: Paradigms, Algorithms, and Applications. [Details]

Peer Reviewed Journals:

  • C. Mooney, Y. Wang, G.Pollastri (2011) 'SCLpred: Protein Subcellular Localization Prediction by N-to-1 Neural Networks'. Bioinformatics, . Available Online [DOI] [Details]
  • I. Walsh, A.J.Martin, T. Di Domenico, A. Vullo , G.Pollastri, S.Tosatto (2011) 'CSpritz: accurate prediction of protein disorder segments with annotation for homology, secondary structure and linear motifs'. Nucleic Acids Research, 39 (W):190-186. Available Online [Details]
  • Alberto J.M.Martin, Claudio Mirabello, Gianluca Pollastri (2011) 'Neural Network Pairwise Interaction Fields for Protein Model Quality Assessment and Ab Initio Protein Folding'. Current Protein and Peptide Science, 12 (6):549-562. [Details]
  • P.Kukic, D.Farrell, U.Bjarnadottir, C.Søndergaard, G.Pollastri, J.E.Nielsen (2010) 'Improving the analysis of NMR spectra tracking pH-induced conformational changes: Removing artefacts of the electric field on the NMR chemical shift'. Proteins, . [Details]
  • C.Søndergaard, A.Garrett, T.Carstensen, G.Pollastri, J.E.Nielsen (2009) 'Structural artefacts in protein-ligand X-ray structures: implications for the development of docking scoring functions'. Journal of Medicinal Chemistry, . [Details]
  • Ian Walsh, Alberto JM Martin, Catherine Mooney, Enrico Rubagotti, Alessandro Vullo, Gianluca Pollastri (2009) 'Ab initio and homology based prediction of protein domains by recursive neural networks'. BMC Bioinformatics, 10 . [Details]
  • C.Mooney and G.Pollastri (2009) 'Beyond the Twilight Zone: Automated prediction of structural properties of proteins by recursive neural networks and remote homology information'. Proteins, 77 (1):181-190. [Details]
  • I.Walsh, D.Baú, A.J.M.Martin, C. Mooney, A.Vullo, G.Pollastri (2009) 'Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks'. BMC Structural Biology, 9 . [Details]
  • Q.Le, G.Pollastri, P.Koehl (2009) 'Structural Alphabets for Protein Structure Classification: a Comparison Study'. Journal of Molecular Biology, 387 (2):431-450. [Details]
  • Martin AJ, Bau D, Vullo A, Walsh I, Pollastri G (2008) 'Long-range information and physicality constraints improve predicted protein contact maps'. Journal of bioinformatics and computational biology, 5 (NA):1001-1020. [Details]
  • C.R.Søndergaard, J.P.McIntosh, G.Pollastri, J.E.Nielsen (2008) 'Determination of electrostatic interaction energies and protonation state populations in enzyme active sites'. Journal of Molecular Biology, 376 (1):269-287. Available Online [Details]
  • G.Pollastri, A. J. M. Martin, C. Mooney, A. Vullo (2007) 'Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information'. BMC Bioinformatics, 8 . Available Online [Details]
  • Bau, D; Martin, AJM; Mooney, C; Vullo, A; Walsh, I; Pollastri, G; (2006) 'Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins'. BMC Bioinformatics, 7 (NA). [Details]
  • Vullo, A; Walsh, I; Pollastri, G; (2006) 'A two-stage approach for improved prediction of residue contact maps'. BMC Bioinformatics, 7 (NA). [Details]
  • Mooney, C; Vullo, A; Pollastri, G; (2006) 'Protein structural motif prediction in multidimensional phi-psi space leads to improved secondary structure prediction'. Journal of Computational Biology, 13 (8):1489-1502. [Details]
  • Vullo, A., Bortolami, O., Pollastri, G., Tosatto, S. (2006) 'Spritz: a server for the prediction of intrinsically disordered regions in protein sequences using kernel machines'. NUCLEIC ACIDS RESEARCH, . [Details]
  • Pollastri, G.,Vullo, A.,Frasconi, P.,Baldi, P. (2006) 'Modular DAG-RNN Architectures for assembling coarse protein structures'. Journal of Computational Biology, 13 (3):631-650. [Details]
  • Ceroni, A; Frasconi, P; Pollastri, G; (2005) 'Learning protein secondary structure from sequential and relational data'. Neural Networks, 18 (8):1029-1039. [Details]
  • Pollastri, G.,McLysaght, A. (2005) 'Porter: a new, accurate server for protein secondary structure prediction'. Bioinformatics, 21 (8):1719-1720. [Details]
  • Y.Guermeur, G.Pollastri, A.Eliseeff, D.Zelus, H. Paugam-Moisy, P.Baldi (2004) 'Combining Protein Secondary Structure Prediction Models With Ensemble Methods of Optimal Complexity'. Neurocomputing, 56C :305-327. [Details]
  • Y.Dou, P. Baisnee, G. Pollastri, Y. Pecout, J. Nowick, and P. Baldi (2004) 'ICBS: A Database of Protein-Protein Interactions Mediated by β-Sheet Formation'. Bioinformatics, in press . [Details]
  • G.Pollastri, P.Baldi, A.Vullo, P.Frasconi (2003) 'Prediction of Protein Topologies Using GIOHMMs and GRNNs'. Advances in Neural Information Processing Systems, 15 . [Details]
  • P.Baldi and G.Pollastri (2003) 'The Principled Design of Large-Scale Recursive Neural Network Architectures - DAG-RNNs and the Protein Structure Prediction Problem'. Journal of Machine Learning Research, 4 :575-602. [Details]
  • P.F. Baisnee, G. Pollastri, P.F. Baldi, J.S. Nowick. (2002) 'Identification of protein-protein interactions mediated by interchain beta-sheet formation'. Abstracts of Papers of the American Chemical Society, 224 . [Details]
  • G.Pollastri, P.Baldi, P.Fariselli, R.Casadio (2002) 'Prediction of Coordination Number and Relative Solvent Accessibility in Proteins'. Proteins, 47 :142-153. [Details]
  • G.Pollastri, D.Przybylski, B.Rost, P.Baldi (2002) 'Improving the Prediction of Protein Secondary Strucure in Three and Eight Classes Using Recurrent Neural Networks and Profiles'. Proteins, 47 :228-235. [Details]
  • P.Baldi, G.Pollastri (2002) 'Machine Learning Structural and Functional Proteomics'. IEEE Intelligent Sysyems, 17, 2 :28-35. [Details]
  • G.Pollastri and P.Baldi (2002) 'Prediction of Contact Maps by Recurrent Neural Network Architectures and Hidden Context Propagation from All Four Cardinal Corners'. Bioinformatics, 18 (Supplement 1):62-70. [Details]
  • G.Pollastri, P.Baldi, P.Fariselli, R.Casadio (2001) 'Improved Prediction of the Number of Residue Contacts in Proteins by Recurrent Neural Networks'. Bioinformatics, 17 (Supplement 1):234-242. [Details]
  • P.Baldi, S.Brunak, P.Frasconi, G.Soda., G.Pollastri (1999) 'Exploiting the Past and the Future in Protein Secondary Structure Prediction'. Bioinformatics, 15 :937-946. [Details]

Conference Publications:

  • G.Tradigo, P.Veltri, G.Pollastri (2011) Machine Learning approaches for Contact Map prediction in the CASP9 experiment SEBD 2011 Maratea (Italy), , 26-JUN-11 - 29-JUN-11 [Details]
  • I.Walsh, A.Vullo, G.Pollastri (2009) An adaptive model for learning molecular endpoints . In: M.Biehl, B.Hammer, S.Hochreiter, S.C. Kremer and T.Villmann eds. Similarity-based learning on structures , Dagstuhl Seminars series Dagstuhl, Germany, , 15-FEB-09 - 20-FEB-09 Available Online [Details]
  • A.J.M.Martin, A.Vullo, G.Pollastri (2009) Neural Network Pairwise Interaction Fields for protein model quality assessment LION3 Trento, Italy, , 14-JAN-09 - 18-JAN-09 Available Online [Details]
  • J.Cheng, G.Pollastri (2008) A Neural Network Approach to Ordinal Regression IJCNN 2008 Hong Kong, , 01-JUN-08 - 06-JUN-08 [Details]
  • A. Vullo, A. Passerini, P. Frasconi, F. Costa, G. Pollastri (2008) On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways EVOBIO 2008 Available Online [Details]
  • C.Søndergaard, L.P.McIntosh, G.Pollastri, J.E.Nielsen (2007) 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, [Details]
  • P.F. Baisnee, G. Pollastri, P.F. Baldi, J.S. Nowick (2002) Identification of protein-protein interactions mediated by interchain beta-sheet formation 224th National Meeting of the American Chemical Society Boston, [Details]
  • P.Baldi, S.Brunak, P.Frasconi, G.Pollastri, and G.Soda (1999) Bidirectional Dynamics for Protein Secondary Structure Prediction International Joint Conference on Artificial Intelligence (IJCAI99) Stockholm, [Details]
  • P.Baldi, G.Pollastri, C.A.F. Andersen, and S. Brunak. (2000) Matching Protein beta-Sheet Partners by Feedforward and Recurrent Neural Networks Proceedings of the 2000 Conference on Intelligent Systems for Molecular Biology, (ISMB00), La Jolla, CA, AAAI Press, 2000 La Jolla, CA, [Details]

Articles

  • G.Pollastri (1999) Modelli Connessionistici non causali per l'analisi di sequenze e loro impiego nella classificazione delle proteine. Articles [Details]
  • G.Pollastri (1997) Risoluzione dei giochi dell'8 e del 15 con algoritmo IDA* e funzione euristica calcolata mediante MLP. Articles [Details]

Reports

  • C. Mooney, A. Vullo, G. Pollastri (2006) Protein Backbone Angle Prediction in Multidimensional phi-psi Space UCD CSI Technical Report 2006-1. Reports [Details]

Technical Publication

  • P. Baisnee, G. Pollastri, Y. Pecout, P. Baldi (2003) ICBS: A Database of Protein-Protein Interactions Mediated by β-Sheet Formation. Technical Publication [Details]

Research

Research Interests:

    • Bioinformatics,
    • Protein Structure Prediction,
    • Machine Learning,
    • Neural Networks

     There are two main related focuses to my research: one is the development of Machine Learning models for complex structured data; the other is the field of Bioinformatics, and Structural Genomics and Proteomics in particular. The two things are inextricably tied, since virtually all the applicative domains I tested my models on are in molecular biology.
    To get an idea of our ongoing projects, you may check our research blurb, the list of our free tools and servers, or our funding and publication pages.


Teaching

Teaching Interests:



Modules Co-ordinated:

  • COMP10010     Computer Science: Introduction to Programming I
  • COMP10140     Computer Science: Programming for Radiography I
  • COMP20120     Computer Science: Introduction to Bioinformatics
  • COMP30230     Computer Science: Connectionist Computing
  • COMP40400     Computer Science: Bioinformatics
  • COMP41390     Computer Science: Connectionist Computing

Recent Postgraduate Students:

    Davide Baú (Ph.D. 2008)

    Catherine Mooney (Ph.D. 2008)

    Ian Walsh (Ph.D. 2008)

    Chresten Søndergaard (Ph.D. 2009)

    Alberto J.Martin-Martin (Ph.D. 2009)

     


Current Postgraduate Students:

  • Predrag Kukic, Doctor of Philosophy (PhD)   -   Thesis Supervisor
  • Alessandro Lusci, Doctor of Philosophy (PhD)   -   Thesis Supervisor
  • Claudio Mirabello, Doctor of Philosophy (PhD)   -   Thesis Supervisor
  • Alessandro Adelfio, Doctor of Philosophy (PhD)   -   Thesis Supervisor
  • Viola Volpato, Doctor of Philosophy (PhD)   -   Thesis Supervisor