Dr Catherine Mooney

Lecturer/Assistant Professor

 email:  catherine.mooney@ucd.ie
 Phone: +353 1 716 2917
 Room: A1.10
 Computer Science Building
 Belfield 
 Dublin 4

 Full Profile

Data Mining and Machine Learning

Introduction to Software Engineering

 

Machine Learning, Computational Biology, Bioinformatics

Peer Reviewed Journal Publications

[1] T. Hassan, C. Santi, C. Mooney, N.G. McElvaney, C.M. Greene. Alpha-1 antitrypsin augmentation therapy decreases miR-199a-5p, miR-598 and miR-320a expression in monocytes via inhibition of NFkB. Scientific Reports, 7:13803, 2017.
[2] R. Raoof, E.M. Jimenez-Mateos, S. Bauer, B. Tackenberg, F. Rosenow, J. Lang, M. Dogan, H. Hamer, T. Huchtemann, P. Kortvelyessy, M. Farrell, D.F. O’Brien, D. Henshall, C. Mooney. Cerebrospinal fluid microRNAs are potential biomarkers of temporal lobe epilepsy and status epilepticus. Scientific Reports, 7:3328, 2017.
[3] C.M. Mooney, E.M. Jimenez-Mateos, T. Engel, C. Mooney, M. Diviney, M. Venø, J. Kjems, M. Farrell, D.F. O’Brien, N. Delanty, et al. RNA sequencing of synaptic and cytoplasmic Upf1-bound transcripts supports contribution of nonsense-mediated decay to epileptogenesis. Scientific Reports, 7:41517, 2017.
[4] P. Bielefeld, C. Mooney, D. Henshall, C. Fitzsimons. miRNA-Mediated Regulation of Adult Hippocampal Neurogenesis. Brain Plasticity, 1-17, 2016.
[5] C. Mooney, B. Becker, R. Raoof, and D.C. Henshall. EpimiRBase: a comprehensive database of microRNA-epilepsy associations. Bioinformatics, 32(9):1436-1438, 2016.
[6] B. Becker, G. Glanville, R. Iwashima, C. McDonnell, K. Goslin, C. Mooney. Effective compiler error message enhancement for novice programming students. Computer Science Education, 1-28, 2016.
[7] K. Hennigan, P.J. Conroy, M.T. Walsh, M. Amin, R. O’Kennedy, P. Ramasamy, G. Gleich, Z. Siddiqui, S. Glynn, O. McCabe, C. Mooney, B. Harvey, R. Costello, J. McBryan. Eosinophil peroxidase activates cells by HER2 receptor engagement and β1-integrin clustering with downstream MAPK cell signaling. Clinical Immunology, 171:1-11, 2016.
[8] C. Mooney, R. Raoof, H. El-Naggar, A. Sanz-Rodriguez, E.M. Jimenez-Mateos, and D.C. Henshall. High Throughput qPCR Expression Profiling of Circulating MicroRNAs Reveals Minimal Sex-and Sample Timing-Related Variation in Plasma of Healthy Volunteers. PloS ONE, 10(12):e0145316, 2015.
[9] E.M. Jimenez-Mateos, M. Arribas-Blazquez, A. Sanz-Rodriguez, C. Concannon, L.A. Olivos-Ore, C.R. Reschke, C.M. Mooney, C. Mooney, E. Lugara, J. Morgan, et al. microRNA targeting of the P2X7 purinoceptor opposes a contralateral epileptogenic focus in the hippocampus. Scientific Reports, 5, 2015.
[10] A. Bianchin, A. Bell, A.J. Chubb, N. Doolan, D. Leneghan, I. Stavropoulos, D.C. Shields, and C. Mooney. Design and Evaluation of Antimalarial Peptides Derived from Prediction of Short Linear Motifs in Proteins Related to Erythrocyte Invasion. PloS ONE, 10(6):e0127383, 2015.
[11] C. Sheedy, C. Mooney, E. Jimenez-Mateos, A. Sanz-Rodriguez, E. Langa, C. Mooney, and T. Engel. De-repression of myelin-regulating gene expression after status epilepticus in mice lacking the C/EBP homologous protein CHOP. International Journal of Physiology, Pathophysiology and Pharmacology, 6(4):185, 2014.
[12] A.B. Nongonierma, C. Mooney, D.C. Shields, and R.J. FitzGerald. In silico approaches to predict the potential of milk protein-derived peptides as dipeptidyl peptidase IV (DPP-IV) inhibitors. Peptides, 57:43–51, 2014.
[13] M. Kruer, M. Salih, H. Azzedine, C. Mooney, S. Elmalik, M. Kabiraj, A. Khan, and F. Alkuraya. C19orf12 mutation leads to a pallido-pyramidal syndrome. Gene, 537(2):352–356, 2014.
[14] M. Kruer, T. Jepperson, S. Dutta, R. Steiner, L. Sanford, M. Merkens, B. Russman, P. Blasco, G. Fan, J. Pollock, S. Stanfield, R. Woltjer, C. Mooney, D. Kretzschmar, C. Paisán-Ruiz, and H. Houlden. Mutations in gamma adducin are associated with inherited cerebral palsy. Annals of Neurology, 74(6):805–814, 2013.
[15] W. Khan, G. Pollastri, F. Duffy, D.C. Shields, and C. Mooney. PepBindPred: Potential utility of docking to identify protein-peptide binding regions. PLoS ONE, 8(9):e72838, 2013.
[16] C. Mooney, D.C. Shields, and G. Pollastri. SCL-Epred: A generalised de novo eukaryotic protein subcellular localisation predictor. Amino Acids, pages 1–9, 2013.
[17] T. Holton, G. Pollastri, D.C. Shields, and C. Mooney. CPPpred: Cell penetrating peptide prediction. Bioinformatics, 29(23):3094–3096, 2013.
[18] C. Mooney, N.J. Haslam, T. Holton, G. Pollastri, and D.C. Shields. PeptideLocator: Prediction of bioactive peptides in protein sequences. Bioinformatics, 29(9):1120–1126, 2013.
[19] A. Nongonierma, C. Mooney, D.C. Shields, and R.J. FitzGerald. Inhibition of dipeptidyl peptidase IV and xanthine oxidase by amino acids and dipeptides. Food Chemistry, 141(1):644–653, 2013.
[20] R. Pushker, C. Mooney, N. Davey, J-M. Jacqué, and D.C. Shields. Marked variability in the extent of protein disorder within and between viral families. PLoS ONE, 8(4):e60724, 2013.
[21] R. Norris, F. Casey, R.J. FitzGerald, D.C. Shields, and C. Mooney. Predictive modelling of angiotensin converting enzyme inhibitory dipeptides. Food Chemistry, 133(4):1349–354, 2012.
[22] C. Mooney, N.J. Haslam, G. Pollastri, and 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.
[23] C. Mooney, G. Pollastri, D.C. Shields, and N.J. Haslam. Prediction of short linear protein binding regions. Journal of Molecular Biology, 415(1):193–204, 2011.
[24] C. Mooney, Y.H. Wang, and G. Pollastri. SCLpred: protein subcellular localization prediction by N-to-1 neural networks. Bioinformatics, 27(20):2812–2819, 2011.
[25] I. Walsh, D. Baù, A.J.M. Martin, C. Mooney, A. Vullo, and G. Pollastri. Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks. BMC Structural Biology, 9(1):5, 2009.
[26] I. Walsh, A.J.M. Martin, C. Mooney, E. Rubagotti, A. Vullo, and G. Pollastri. Ab initio and homology based prediction of protein domains by recursive neural networks. BMC Bioinformatics, 10(1):195, 2009.
[27] C. Mooney and G. Pollastri. Beyond the Twilight Zone: Automated prediction of structural properties of proteins by recursive neural networks and remote homology information. Proteins: Structure, Function, and Bioinformatics, 77(1):181–190, 2009.
[28] G. Pollastri, A.J.M. Martin, C. Mooney, and A. Vullo. Accurate prediction of protein secondary structure and solvent accessibility by consensus combiners of sequence and structure information. BMC Bioinformatics, 8(1):201, 2007.
[29] D. Baù, A.J.M. Martin, C. Mooney, A. Vullo, I. Walsh, and G. Pollastri. Distill: A suite of web servers for the prediction of one-, two-and three-dimensional structural features of proteins. BMC Bioinformatics, 7(1):402, 2006.
[30] C. Mooney, A. Vullo, and G. Pollastri. Protein structural motif prediction in multi-dimensional φ-ψ space leads to improved secondary structure prediction. Journal of Computational Biology, 13(8):1489–1502, 2006.

Book Chapters

[1] E.M. Jimenez-Mateos, T. Engel, C. Mooney, and D.C. Henshall. MicroRNAs in Epileptogenesis and Epilepsy. In Christian Barbato and Francesca Ruberti, editors, Mapping of Nervous System Diseases via MicroRNAs, volume 6 of Frontiers in Neurotherapeutics Series, pages 153–182. CRC Press, 2016.
[2] C. Mooney, Y.H. Wang, and G. Pollastri. De novo protein subcellular localization prediction by N-to-1 neural networks. In Riccardo Rizzo and PauloJ.G. Lisboa, editors, Computational Intelligence Methods for Bioinformatics and Biostatistics, volume 6685 of Lecture Notes in Computer Science, pages 31–43. Springer Berlin Heidelberg, 2011.
[3] C. Mooney, N. Davey, A.J.M. Martin, I. Walsh, D.C. Shields, and G. Pollastri. In silico protein motif discovery and structural analysis. In Bing Yu and Marcus Hinchcliffe, editors, In Silico Tools for Gene Discovery, volume 760 of Methods in Molecular Biology, pages 341–353. Humana Press, 2011.
[4] A.J.M. Martin, C. Mooney, I. Walsh, and G. Pollastri. Contact map prediction by machine learning. In Introduction to Protein Structure Prediction, pages 137–163. John Wiley and Sons, Inc., 2010.