Artigos com autorizações de acesso público - Gianluca PollastriSaiba mais
4 artigos não disponíveis publicamente
Structural artifacts in protein− ligand X-ray structures: implications for the development of docking scoring functions
CR Søndergaard, AE Garrett, T Carstensen, G Pollastri, JE Nielsen
Journal of medicinal chemistry 52 (18), 5673-5684, 2009
Autorizações: Science Foundation Ireland
Improving the analysis of NMR spectra tracking pH‐induced conformational changes: Removing artefacts of the electric field on the NMR chemical shift
P Kukić, D Farrell, CR Søndergaard, U Bjarnadottir, J Bradley, G Pollastri, ...
Proteins: Structure, Function, and Bioinformatics 78 (4), 971-984, 2010
Autorizações: Science Foundation Ireland
G-quadruplex Structure Prediction and integration in the GenData2020 data model
G Tradigo, F Cristiano, S Alcaro, S Greco, G Pollastri, P Veltri, M Prosperi
Proceedings of the 7th ACM International Conference on Bioinformatics …, 2016
Autorizações: Government of Italy
Deeper Profiles and Cascaded Recurrent and Convolutional Neural Networks for
M Torrisi, M Kaleel, G Pollastri
Scientific Reports, 9 (1):, Article, 2019
Autorizações: Irish Research Council
39 artigos disponíveis publicamente
Deep architectures and deep learning in chemoinformatics: the prediction of aqueous solubility for drug-like molecules
A Lusci, G Pollastri, P Baldi
Journal of chemical information and modeling 53 (7), 1563-1575, 2013
Autorizações: US National Institutes of Health, Science Foundation Ireland
Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity
C Mooney, NJ Haslam, G Pollastri, DC Shields
Public Library of Science 7 (10), e45012, 2012
Autorizações: Science Foundation Ireland
DOME: Recommendations for supervised machine learning validation in biology
I Walsh, D Fishman, D Garcia-Gasulla, T Titma, G Pollastri, J Harrow, ...
Nature Methods, 1-6, 2021
Autorizações: A*Star, Singapore, European Commission, Government of Italy
CPPpred: prediction of cell penetrating peptides
TA Holton, G Pollastri, DC Shields, C Mooney
Bioinformatics 29 (23), 3094-3096, 2013
Autorizações: Science Foundation Ireland
Porter, PaleAle 4.0: high-accuracy prediction of protein secondary structure and relative solvent accessibility
C Mirabello, G Pollastri
Bioinformatics 29 (16), 2056-2058, 2013
Autorizações: Science Foundation Ireland
Prediction of short linear protein binding regions
C Mooney, G Pollastri, DC Shields, NJ Haslam
Journal of molecular biology 415 (1), 193-204, 2012
Autorizações: Science Foundation Ireland
Correct machine learning on protein sequences: a peer-reviewing perspective
I Walsh, G Pollastri, SCE Tosatto
Briefings in bioinformatics 17 (5), 831-840, 2016
Autorizações: Science Foundation Ireland, Government of Italy
Deeper profiles and cascaded recurrent and convolutional neural networks for state-of-the-art protein secondary structure prediction
M Torrisi, M Kaleel, G Pollastri
Scientific reports 9 (1), 12374, 2019
Autorizações: Irish Research Council
PeptideLocator: prediction of bioactive peptides in protein sequences
C Mooney, NJ Haslam, TA Holton, G Pollastri, DC Shields
Bioinformatics 29 (9), 1120-1126, 2013
Autorizações: Science Foundation Ireland
SCLpred: protein subcellular localization prediction by N-to-1 neural networks
C Mooney, YH Wang, G Pollastri
Bioinformatics 27 (20), 2812-2819, 2011
Autorizações: Science Foundation Ireland
Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks
I Walsh, D Baù, AJM Martin, C Mooney, A Vullo, G Pollastri
BMC structural biology 9, 1-20, 2009
Autorizações: Science Foundation Ireland
Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks
P Kukic, C Mirabello, G Tradigo, I Walsh, P Veltri, G Pollastri
BMC bioinformatics 15, 1-15, 2014
Autorizações: Irish Research Council
Porter 5: state-of-the-art ab initio prediction of protein secondary structure in 3 and 8 classes
M Torrisi, M Kaleel, G Pollastri
BioRxiv, 289033, 2018
Autorizações: Irish Research Council
Accurate prediction of protein enzymatic class by N-to-1 Neural Networks
V Volpato, A Adelfio, G Pollastri
BMC bioinformatics 14 (Suppl 1), S11, 2013
Autorizações: Science Foundation Ireland
Structural alphabets for protein structure classification: a comparison study
Q Le, G Pollastri, P Koehl
Journal of molecular biology 387 (2), 431-450, 2009
Autorizações: US National Institutes of Health, Science Foundation Ireland
Predicting binding within disordered protein regions to structurally characterised peptide-binding domains
W Khan, F Duffy, G Pollastri, DC Shields, C Mooney
PLoS One 8 (9), e72838, 2013
Autorizações: Science Foundation Ireland
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