Marco Colombo

Experimental area · proceed at your own risk!

Research papers

November 2016, revised September 2017 N. Pirastu, P.K. Joshi, A.S. Morrison, M.C. Cornelis, P.M. McKeigue, N. Keum, N. Franceschini, M. Colombo, A. Spiliopoulou, L. Franke, K.E. North, P. Kraft, P.S. De Vries, T. Esku, J.F. Wilson GWAS for male-pattern baldness identifies 71 susceptibility loci explaining 38% of the risk Nature Communications, 2017
November 2016, revised April 2017 J.D. Quell, W. Römisch-Margl, M. Colombo, J. Krumsiek, A.M. Evans, R. Mohney, V. Salomaa, U. de Faire, L.C. Groop, F. Agakov, H.C. Looker, P. McKeigue, H.M. Colhoun, G. Kastenmüller Automated pathway and reaction prediction facilitates in silico identification of unknown metabolites in human cohort studies Journal of Chromatography B, 2017
May 2016, revised March 2017 A. Spiliopoulou, M. Colombo, P. Orchard, F. Agakov, P. McKeigue GeneImp: fast imputation to large reference panels using genotype likelihoods from ultra-low coverage sequencing Genetics, 206 (1), 91-104, 2017
August 2014, revised April 2015 H.C. Looker, M. Colombo, S. Hess, M.J. Brosnan, B. Farran, R.N. Dalton, M.C. Wong, C. Turner, C.N. Palmer, E. Nogoceke, L. Groop, V. Salomaa, D.B. Dunger, F. Agakov, P.M. McKeigue and H.M. Colhoun, on behalf of the SUMMIT Investigators Biomarkers of rapid chronic kidney disease progression in type 2 diabetes Kidney International, 88, 888-896, 2015
November 2013, revised January 2015 H.C. Looker, M. Colombo, F. Agakov, T. Zeller, L. Groop, B. Thorand, C.N. Palmer, A. Hamsten, U. de Faire, E. Nogoceke, S.J. Livingstone, V. Salomaa, K. Leander, N. Barbarini, R. Bellazzi, N. van Zuydam, P.M. McKeigue and H.M. Colhoun, on behalf of the SUMMIT Investigators Protein biomarkers for the prediction of cardiovascular disease in type 2 diabetes Diabetologia, 58 (6), 1363-1371, 2015
March 2011, revised September 2011 P.M. McKeigue, M. Colombo, F. Agakov, I. Datta, A. Levin, D. Favro, R.R. Burke, C. Gray-Montgomery, M.C. Iannuzzi and B.A. Rybicki Extending admixture mapping to nuclear pedigrees: application to sarcoidosis Genetic Epidemiology, 37 (3), 256-266, 2013
February 2010, revised July 2010 B.A. Rybicki, A.M. Levin, P.M. McKeigue, I. Datta, C. Gray-McGuire, M. Colombo, D. Reich, R.R. Burke and M.C. Iannuzzi A genome-wide admixture scan for ancestry-linked genes predisposing to sarcoidosis in African-Americans Genes and Immunity, 12 (2), 67-77, 2011
June 2009, revised February 2012 M. Colombo and A. Grothey A decomposition-based crash-start method for stochastic programming Computational Optimization and Applications, 55 (2), 311-340, 2013
March 2009, revised September 2009 M. Colombo, A. Grothey, J. Hogg, K. Woodsend and J. Gondzio A structure-conveying modelling language for mathematical and stochastic programming Mathematical Programming Computation, 1 (4), 223-247, 2009
January 2009 A. Grothey, J. Hogg, K. Woodsend, M. Colombo and J. Gondzio A structure-conveying parallelisable modelling language for mathematical programming "Parallel Scientific Computing and Optimization", R. Ciegis, D. Henty, B. Kågström, J. Zilinskas (eds.), Springer Optimization and its Applications, 27, 147-158, 2009
August 2006, revised March 2009 M. Colombo, J. Gondzio and A. Grothey A warm-start approach for large-scale stochastic linear programs Mathematical Programming, 127 (2), 371-397, 2011
October 2005, revised November 2006 M. Colombo and J. Gondzio Further development of multiple centrality correctors for interior point methods Computational Optimization and Applications, 41 (3), 277-305, 2008

Technical reports and Dissertations

June 2009, revised December 2010 M. Colombo and A. Grothey A multi-step interior point warm-start approach for large-scale stochastic linear programming Technical Report ERGO 09-007
May 2007, revised October 2007 M. Colombo Advances in interior point methods for large-scale linear programming Thesis presented for the Degree of PhD in Optimization, School of Mathematics, University of Edinburgh Successfully defended on 6 September 2007, examiners Danny Ralph and Ken McKinnon
September 2003 M. Colombo A branch-and-cut approach to solve the Hamiltonian Cycle Problem Dissertation presented for the Degree of MSc in Operational Research, School of Mathematics, University of Edinburgh MSc in OR awarded with distinction
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