| Wisdom of crowds for robust gene network inference (As part of the DREAM5 consortium) D Marbach, JC Costello, R Küffner, NM Vega, RJ Prill, DM Camacho, ... Nature Methods, 2012 | 2033 | 2012 |
| Techniques for clustering gene expression data G Kerr, HJ Ruskin, M Crane, P Doolan Computers in biology and medicine 38 (3), 283-293, 2008 | 342 | 2008 |
| Random matrix theory for portfolio optimization: a stability approach S Sharifi, M Crane, A Shamaie, H Ruskin Physica A: Statistical Mechanics and its Applications 335 (3-4), 629-643, 2004 | 141 | 2004 |
| Time and scale Hurst exponent analysis for financial markets JAO Matos, SMA Gama, HJ Ruskin, A Al Sharkasi, M Crane Physica A: Statistical Mechanics and its Applications 387 (15), 3910-3915, 2008 | 139 | 2008 |
| RNA-Seq vs dual-and single-channel microarray data: sensitivity analysis for differential expression and clustering A Sîrbu, G Kerr, M Crane, HJ Ruskin PloS one 7 (12), e50986, 2012 | 134 | 2012 |
| Cross-correlation dynamics in financial time series T Conlon, HJ Ruskin, M Crane Physica A: Statistical Mechanics and its Applications 388 (5), 705-714, 2009 | 115 | 2009 |
| Random matrix theory and fund of funds portfolio optimisation T Conlon, HJ Ruskin, M Crane Physica A: Statistical Mechanics and its applications 382 (2), 565-576, 2007 | 102 | 2007 |
| Comparison of evolutionary algorithms in gene regulatory network model inference A Sîrbu, HJ Ruskin, M Crane BMC bioinformatics 11 (1), 59, 2010 | 99 | 2010 |
| Learning behaviours data in programming education: Community analysis and outcome prediction with cleaned data TT Mai, M Bezbradica, M Crane Future Generation Computer Systems 127, 42-55, 2022 | 89 | 2022 |
| Random matrix theory filters in portfolio optimisation: A stability and risk assessment J Daly, M Crane, HJ Ruskin Physica A: Statistical Mechanics and its Applications 387 (16-17), 4248-4260, 2008 | 70 | 2008 |
| Wavelet multiscale analysis for hedge funds: Scaling and strategies T Conlon, M Crane, HJ Ruskin Physica A: Statistical Mechanics and its Applications 387 (21), 5197-5204, 2008 | 67 | 2008 |
| Interrelationships among international stock market indices: Europe, Asia and the Americas A Sharkasi, HJ Ruskin, M Crane International Journal of Theoretical and Applied Finance 8 (05), 603-622, 2005 | 59 | 2005 |
| The reaction of stock markets to crashes and events: A comparison study between emerging and mature markets using wavelet transforms A Sharkasi, M Crane, HJ Ruskin, JA Matos Physica A: Statistical Mechanics and its Applications 368 (2), 511-521, 2006 | 54 | 2006 |
| Cross-Correlation Dynamics and Community Structures of Cryptocurrencies H Chaudhari, M Crane Journal of Computational Science 44 (July), 101130, 2020 | 52 | 2020 |
| Probabilistic models for drug dissolution. Part 1. Review of Monte Carlo and stochastic cellular automata approaches A Barat, HJ Ruskin, M Crane Simulation Modelling Practice and Theory 14 (7), 843-856, 2006 | 52 | 2006 |
| The cryptocurrency market in transition before and after COVID-19: An opportunity for investors? APN Nguyen, TT Mai, M Bezbradica, M Crane Entropy 24 (9), 1317, 2022 | 41 | 2022 |
| Employee turnover prediction using machine learning L Alaskar, M Crane, M Alduailij International conference on computing, 301-316, 2019 | 39 | 2019 |
| Probabilistic methods for drug dissolution. Part 2. Modelling a soluble binary drug delivery system dissolving in vitro A Barat, HJ Ruskin, M Crane Simulation modelling practice and theory 14 (7), 857-873, 2006 | 39 | 2006 |
| Quantitative multi-agent models for simulating protein release from PLGA bioerodible nano-and microspheres A Barat, M Crane, HJ Ruskin Journal of Pharmaceutical and Biomedical Analysis 48 (2), 361-368, 2008 | 38 | 2008 |
| Comparison of microarray preprocessing methods K Shakya, HJ Ruskin, G Kerr, M Crane, J Becker Advances in computational biology, 139-147, 2010 | 35 | 2010 |
Alina SîrbuComputer Science Department, University of Pisa, ItalyVerified email at unipi.it
