List of Publications for D. J. Higham
(in reverse chronological order within each category)
Books
B6
Numerical Methods for Ordinary Differential Equations, D. F. Griffiths and D. J. Higham, Springer, 2010.
B5
Network Science: Complexity in Nature and Technology, Edited by E. Estrada, M. Fox, D. J. Higham and G.-L. Oppo, Springer, 2010.
B4
MATLAB Guide, D.J. Higham and N.J. Higham, Society for Industrial and Applied Mathematics, 3rd edition, 2017.
B3
An Introduction to Financial Option Valuation: Mathematics, Stochastics and Computation, D.J. Higham, Cambridge University Press, 2004.
B2
Numerical Analysis 1997: Proceedings of the 17th Biennial Conference on Numerical Analysis, Edited by D.F. Griffiths, D.J. Higham and G.A. Watson, Pitman Research Notes in Mathematics, Longman Scientific and Technical, 1998.
B1
Learning LATEX, D.F. Griffiths and D.J. Higham, Society for Industrial and Applied Mathematics, 2nd edition, 2016.


Refereed Journal Papers
(In reverse chronological order of acceptance)
Most of these can be downloaded via
http://personal.strath.ac.uk/d.j.higham/Plist/PX.pdf
where X is the relevant number.
P137
On the exponential generating function for non-backtracking walks, F. Arrigo, P. Grindrod, D. J. Higham and V. Noferini, Linear Algebra and its Applications, to appear.
P136
Computational complexity analysis for Monte Carlo approximations of classically scaled population processes, D. F. Anderson, D. J. Higham and Y. Sun, Multiscale Modeling and Simulation (SIAM), to appear.
P135
High modularity creates scaling laws, P. Grindrod and D. J. Higham, Scientific Reports, 8, 2018, 9737.
P134
The deformed graph Laplacian and its applications to network centrality analysis, P. Grindrod, D. J. Higham and V. Noferini, SIAM Journal on Matrix Analysis and Applications, 39, 2018, 310–341.
P133
Centrality analysis for modified lattices, M. Paton, K. Akartunali and D. J. Higham, SIAM Journal on Matrix Analysis and Applications, 38, 2017, 1055--1073.
P132
Nonbacktracking walk centrality for directed networks, F. Arrigo, P. Grindrod, D. J. Higham and V. Noferini, Journal of Complex Networks, 6, 2018, 54--78.
P131
Sparse matrix computations for dynamic network centrality, F. Arrigo and D. J. Higham, Applied Network Science, 2, 2017, 1--19.
P130
An overview of city analytics, D. J. Higham, M. Batty, L. M. A. Bettencourt, D. Vukadinovic Greetham and P. Grindrod, Royal Society Open Science, 4, 2017, 161063.
P129
Block matrix formulations for evolving networks, C. Fenu and D. J. Higham, SIAM Journal on Matrix Analysis and Applications, 38, 2017, 343--360.
P128
Multilevel Monte Carlo for stochastic differential equations with small noise, D. F. Anderson, D. J. Higham and Y. Sun, SIAM Journal on Numerical Analysis, 54, 2016, 505--529.
P127
Inverse network sampling to explore on-line brand allegiance, P. Grindrod, D. J. Higham, P. Laflin, A. Otley, J. A. Ward, European Journal of Applied Mathematics (Special Issue on Networks), 27, 2016, 958--970.
P126
Asymmetry through time dependency, A. V. Mantzaris and D. J. Higham, European Physics Journal B (Special issue on Temporal Networks), 89, 2016.
P125
Matching exponential-based and resolvent-based centrality measures, M. Aprahamian, D. J. Higham and N. J. Higham, Journal of Complex Networks, 4, 2015, 157--176.
P124
An introduction to multilevel Monte Carlo for option valuation, D. J. Higham, International Journal of Computer Mathematics (Special Issue on Computational Methods in Finance), 92, 2015, 2347--2360.
P123
Complexity of multilevel Monte Carlo tau-leaping, D. F. Anderson, D. J. Higham and Y. Sun, SIAM Journal on Numerical Analysis, 52, 2015, 3106--3127.
P122
Betweenness in time dependent networks, A. Alsayed and D. J. Higham, Chaos, Solitons and Fractals, Volume 72, 2015, 35--48.
P121
A dynamical systems view of network centrality, P. Grindrod and D. J. Higham, Proceedings of the Royal Society, Series A, 2014, 20130835.
P120
Subanaesthetic ketamine treatment promotes abnormal interactions between neural subsystems and alters the properties of functional brain networks, N. Dawson, M. McDonald, D. J. Higham, B. Morris and J. Pratt, Neuropsychopharmacology, 39 2014, 1786--1798.
P119
Discovering and validating influence in a dynamic online social network, P. Laflin, A. V. Mantzaris, P. Grindrod, F. Ainley, A. Otley and D. J. Higham, Social Network Analysis and Mining, 3, 2013, 1311--1323.
P118
Convergence, non-negativity and stability of a new Milstein scheme with applications to finance, D. J. Higham, X. Mao and L. Szpruch, Discrete and Continuous Dynamical Systems B, 2013, 2083--2100.
P117
Mathematical modelling of polyamine metabolism in bloodstream-form Trypanosoma brucei: An application to drug target identification, X. Gu, D. Reid, D. J. Higham and D. Gilbert, PLoS ONE, 8, 2013, e53734.
P116
Dynamic network centrality summarizes learning in the human brain, A. V. Mantzaris, D. S. Bassett, N. F. Wymbs, E. Estrada, M. A. Porter, P. J. Mucha, S. T. Grafton and D. J. Higham, Journal of Complex Networks, 1, 2013, 83--92.
P115
Mean exit times and the multi-level Monte Carlo method, D. J. Higham, X. Mao, M. Roj, Q. Song and G. Yin, Journal of Uncertainty Quantification (SIAM/ASA), 1, 2013, 2--18.
P114
Simultaneous non-negative matrix factorization for multiple large scale gene expression datasets in toxicology, C. M. Lee, M. A. V. Mudaliar, D. R. Haggart, C. R. Wolf, G. Miele, J. K. Vass, D. J. Higham and D. Crowther, PLoS ONE, 7, 2013, e48238.
P113
Sustained NMDA receptor hypofunction induces compromised neural systems integration and schizophrenia-like alterations in functional brain networks, N. Dawson, X. Xiao, D. J. Higham, B. Morris, J. Pratt, Cerebral Cortex, 2014, 452--464.
P112
A model for dynamic communicators A. Mantzaris and D. J. Higham, European Journal of Applied Mathematics, 23, 2012, 659--668.
P111
Bistability through triadic closure, P. Grindrod, D. J. Higham and M. C. Parsons, Internet Mathematics, 8, 2012, 402--423.
P110
Spectral algorithms for heterogeneous biological networks, M. McDonald, D. J. Higham and J. K. Vass, Briefings in Functional Genomics, 11, 2012, 457--468.
P109
A matrix iteration for dynamic network summaries, P. Grindrod and D. J. Higham, SIAM Review, 55, 2013, 118--128.
P108
Multi-level Monte Carlo for continuous time Markov chains, with applications in biochemical kinetics, D. F. Anderson and D. J. Higham, Multiscale Modeling and Simulation (SIAM), 10, 2012, 146-179.
P107
Googling the Brain: Discovering hierarchical and asymmetric network structures, with applications in neuroscience, J. J. Crofts and D. J. Higham, Internet Mathematics (Special Issue on Biological Networks), 7, 2011, 233-254.
P106
Exploring metabolic pathway disruption in the subchronic phencyclidine model of schizophrenia with the Generalized Singular Value Decomposition, X. Xiao, N. Dawson, L. MacIntyre, B. J. Morris, J. A. Pratt, D. G. Watson and D. J. Higham, BMC Systems Biology, 2011, 5:72.
P105
Discretization provides a conceptually simple tool to build expression networks, J. K. Vass, D. J. Higham, M. A. V. Mudaliar, X. Mao, D. J. Crowther, PLoS ONE 6(4), 2011, e18634.
P104
Communicability across evolving networks, P. Grindrod, D. J. Higham, M. C. Parsons and E. Estrada, Physical Review E, 83 2011, 046120.
P103
Hybrid simulation of autoregulation within transcription and translation, D. J. Higham, S. Intep, X. Mao and L. Szpruch, BIT Numerical Mathematics, 51, 2011, 177-196.
P102
Models for evolving networks: with applications in telecommunication and online activities, P. Grindrod and D. J. Higham, The Institute of Mathematics and Its Applications (IMA) Journal of Management Mathematics, 23, 2012, 1-16.
P101
Discovering bipartite substructure in directed networks, A. J. Taylor, J. K. Vass and D. J. Higham, London Mathematical Society J. Comput. and Math., 14, 2011, 72-86.
P100
Stochastic ordinary differential equations in applied and computational mathematics, D. J. Higham, The Institute of Mathematics and Its Applications (IMA) Journal of Applied Mathematics, special issue: "2020 visions of applied mathematics", 76, 2011, 449-474.
P99
Network analysis detects changes in the contralesional hemisphere following stroke, J. J. Crofts, D. J. Higham, R. Bosnell, S. Jbabdi, P. M. Matthews, T. E. J. Behrens; H. Johansen-Berg, NeuroImage, 54, 2011, 161-169.
P98
Mapping directed networks, J. J. Crofts, E. Estrada, D. J. Higham and A. Taylor, Electronic Transactions on Numerical Analysis, 37, 2010, 337-350.
P97
Numerical simulation of a strongly nonlinear Ait-Sahalia type interest rate model, L. Szpruch, X. Mao, D. J. Higham and J. Pan, BIT Numerical Mathematics, 51, 2011, 405-425.
P96
Non-negative matrix factorisation for network reordering, C. Lee, D. J. Higham, D. Crowther and J. K. Vass, Monografias de la Real Academia de Ciencias de Zaragoza, (special issue honouring Manuel Calvo on his 65th birthday), 33, 2010, 39-53.
P95
Network properties revealed through matrix functions, E. Estrada and D. J. Higham, SIAM Review, 52, 2010, 696-714.
P94
Comparing hitting time behaviour of Markov jump processes and their diffusion approximations, L. Szpruch and D. J. Higham, Multiscale Modeling and Simulation (SIAM), 8, 2010, 605-621.
P93
Periodic reordering, P. Grindrod, D. J. Higham and G. Kalna, The Institute of Mathematics and Its Applications (IMA) Journal of Numerical Analysis, 30, 2010, 195-207.
P92
Evolving graphs: Dynamical models, inverse problems and propagation, P. Grindrod and D. J. Higham, Proceedings of the Royal Society, Series A, 466, 2010, 753-770.
P91
Zero, one and two-switch models of gene regulation, S. Intep and D. J. Higham, Discrete and Continuous Dynamical Systems, Series B, 14 (special issue in honour of Peter Kloeden), 2010, 495-513.
P90
Geometric de-noising of protein-protein interaction networks, O. Kuchaiev, M. Rasajski, D. J. Higham and N. Przulj, PLoS Computational Biology, 5, 2009, e1000454.
P89
Switching and diffusion models for gene regulation networks, S. Intep, D. J. Higham and X. Mao, Multiscale Modeling and Simulation (SIAM), 8, 2009, 30-45.
P88
First and second moment reversion for a discretised square root process with jumps, G. D. Chalmers and D. J. Higham, J. Difference Equations and Applications, 16 (special issue in honour of Peter Kloeden), 2010, 143-156.
P87
A weighted communicability measure applied to complex brain networks, J. J. Crofts and D. J. Higham, J. Royal Socety Interface, 33, 2009, 411-414.
P86
Communicability betweenness in complex networks, E. Estrada, D. J. Higham and N. Hatano, Physica A. 388, 2009, 764-774.
P85
Analysing multi-level Monte Carlo for options with non-globally Lipschitz payoff, M. Giles, D. J. Higham and X. Mao, Finance and Stochastics. 13, 2009, 403-413.
P84
Communicability and multipartite structures in complex networks at negative absolute temperatures, E. Estrada, D. J. Higham and N. Hatano, Physical Review E, 78, 2008, 026102 (7 pages).
P83
CONTEST: A Controllable Test Matrix Toolbox for MATLAB, A. Taylor and D. J. Higham, ACM Trans. Math. Software., 35, 2009, 26:1-26:17.
P82
Asymptotic stability of a jump-diffusion equation and its numerical approximation, G. D. Chalmers and D. J. Higham, SIAM Journal on Scientific Computing, 31, 2008, 1141-1155.
P81
Chemical master equation and Langevin regimes for a gene transcription model, R. Khanin and D. J. Higham, Theoretical Computer Science. 408, 2008, 31-40.
P80
Fitting a geometric graph to a protein-protein interaction network, D. J. Higham, M. Rasajski and N. Przulj, Bioinformatics, 2008; doi: 10.1093/bioinformatics/btn079.
P79
Chemical master versus chemical Langevin for first-order reaction networks, D. J. Higham and R. Khanin, The Open Applied Mathematics Journal, 2, 2008, 59-79.
P78
DNA meets the SVD, P. Grindrod, D. J. Higham, G. Kalna, A. Spence, Z. Stoyanov and J. K. Vass, The Institute of Mathematics and Its Applications (IMA) Mathematics Today, 44, 2008, 80-85.
P77
A clustering coefficient for weighted networks, with application to gene expression data, G. Kalna and D. J. Higham, AI Communications (The European Journal on Artificial Intelligence) special issue on Network Analysis in Natural Sciences and Engineering, 20, 2007, 263-271.
P76
Preserving exponential mean-square stability in the simulation of hybrid stochastic differential equations, D. J. Higham, X. Mao and C. Yuan, Numerische Mathematik, 108, 2007, 295-325.
P75
Convergence and stability analysis for implicit simulations of stochastic differential equations with random jump magnitudes, G. D. Chalmers and D. J. Higham, Discrete and Continuous Dynamical Systems B, 9, 2008, 47-64.
P74
Modeling and simulating chemical reactions D. J. Higham, SIAM Review, Education Section, 50, 2008, 347-368.
P73
Comment on "Numerical methods for stochastic differential equations", K. Burrage, P. Burrage, D. J. Higham, P. E. Kloeden and E. Platen, Physical Review E, 74, 2006, 068701.
P72
Multidimensional partitioning and bi-partitioning: analysis and application to gene expression datasets, G. Kalna, J. K. Vass and D. J. Higham, International Journal of Computer Mathematics, 85, 2008, 475-485.
P71
Spectral analysis of two-signed microarray expression data, D. J. Higham, G. Kalna and J. K. Vass, IMA Mathematical Medicine and Biology, 24, 2007, 131-148.
P70
Almost sure and moment exponential stability in the numerical simulation of stochastic differential equations, D. J. Higham, X. Mao and C. Yuan, SIAM J. Numer. Anal., 45, 2007, 592-609.
P69
A matrix perturbation view of the small world phenomenon, D. J. Higham, SIAM Review, 49, 2007, 91-108, (chosen as a SIGEST article, based on [P49]).
P68
Connectivity-based parcellation of human cortex using diffusion MRI: establishing reproducibility, validity and observer-independence in BA 44/45 and SMA/pre-SMA, J. C. Klein, T. E. J. Behrens, M. D. Robson, C. E. Mackay, D. J. Higham, H. Johansen-Berg, NeuroImage, 34, 2007, 204-211.
P67
Modelling protein-protein interaction networks via a stickiness index, N. Przulj and D. J. Higham, J. Royal Society Interface, 3, 2006, 711-716.
P66
Divergent routes to oral cancer, K. D. Hunter, J. K. Thurlow, J. Fleming, P. J. H. Drake, J. K. Vass, G. Kalna, D. J. Higham, P. Herzyk, D. G. MacDonald, E. K. Parkinson, P. R. Harrison, Cancer Research, 66, 2006, 7405-7413.
P65
A lock-and-key model for protein-protein interactions, J. L. Morrison, R. Breitling, D. J. Higham and D. R. Gilbert, Bioinformatics, 22, 2006, 2012-2019.
P64
Nonnormality and stochastic differential equations, D. J. Higham and X. Mao, BIT Numerical Mathematics. 46, 525-532, 2006.
P63
Strong convergence rates for backward Euler on a class of nonlinear jump-diffusion problems, D. J. Higham and P. E. Kloeden, J. Computational and Applied Math. 205, 2007, 949-956.
P62
Greedy pathlengths and small world graphs, D. J. Higham, Linear Algebra and Its Applications, 416, 2006, 745-758.
P61
Spectral clustering and its use in bioinformatics, D. J. Higham, G. Kalna, and M. Kibble, J. Computational and Applied Math., 204, 2007, 25-37.
P60
Convergence and stability of implicit methods for jump-diffusion systems, D. J. Higham and P. E. Kloeden, International Journal of Numerical Analysis & Modeling, 3, 2006, 125-140.
P59
GeneRank: Using search engine technology for the analysis of microarray experiments, J. L. Morrison, R. Breitling, D. J. Higham and D. R. Gilbert, BMC Bioinformatics 2005, 6:233. (Flagged as Highly accessed.)
P58
Numerical methods for nonlinear stochastic differential equations with jumps, D. J. Higham and P. E. Kloeden, Numerische Mathematik, 101, 2005, 101-119.
P57
Convergence of Monte Carlo simulations involving the mean-reverting square root process, D. J. Higham and X. Mao, Journal of Computational Finance. 8, 2005, 35-61.
P56
Google PageRank as mean playing time for pinball on the reverse web, D. J. Higham, Applied Mathematics Letters, 18, 2005, 1359-1362.
P55
Spectral reordering of a range-dependent weighted random graph, D. J. Higham, The Institute of Mathematics and Its Applications (IMA) Journal of Numerical Analysis. 25, 2005, 443-457.
P54
Black-Scholes for scientific computing students, D. J. Higham, Computing in Science and Engineering (Education Section), 6, 2004, 72-79.
P53
Changes in connectivity profiles define functionally-distinct regions in human medial frontal cortex, H. Johansen-Berg, T. E. J. Behrens, M. D. Robson, I. Drobnjak, M. F. S. Rushworth, J. M. Brady, S. M. Smith, D. J. Higham and P. M. Matthews, Proceedings of the National Academy of Sciences (PNAS), vol. 101 (no. 26), 2004, 13335-13340.
P52
Numerical simulation of a linear stochastic oscillator with additive noise, A. H. Strømmen Melbø and D. J. Higham, Applied Numerical Mathematics, 51, 2004, 89-99.
P51
The sleekest link algorithm, D. J. Higham and A. Taylor, The Institute of Mathematics and Its Applications (IMA) Mathematics Today, 39, 2003, 192-197.
P50
Exponential mean square stability of numerical solutions to stochastic differential equations, D. J. Higham, X. Mao and A. M. Stuart, London Mathematical Society J. Comput. and Math., 6, 2003, 297-313.
P49
A matrix perturbation view of the small world phenomenon, D. J. Higham, SIAM Journal on Matrix Analysis and Applications, 25, 2003, 429-444.
P48
Unravelling small world networks, D. J. Higham, J. Computational and Applied Math., 158, 2003, 61-74.
P47
On the boundedness of asymptotic stability regions for the stochastic theta method, A. Bryden and D. J. Higham. BIT Numerical Mathematics, 43, 2003, 1-7.
P46
Nine ways to implement the binomial method for option valuation in MATLAB, D. J. Higham. SIAM Review, Education Section, 44, 2002, 661-677.
P45
Ergodicity for SDEs and approximations: Locally Lipschitz vector fields and degenerate noise, J. Mattingly, A. M. Stuart and D. J. Higham. Stochastic Processes and their Appl., 101, 2002, 185-232.
P44
Strong convergence of Euler-type methods for nonlinear stochastic differential equations, D. J. Higham, X. Mao and A. M. Stuart. SIAM J. Num Anal., 40, 2002, 1041-1063.
P43
Error analysis of QR algorithms for computing Lyapunov exponents, E. J. McDonald and D. J. Higham, Electronic Transactions on Numerical Analysis, 12, 2001, 234-251.
P42
An algorithmic introduction to numerical simulation of stochastic differential equations, by D. J. Higham, SIAM Review, Education Section, 43, 2001, 525-546.
P41
MacCormack's method for advection-reaction equations, by D. F. Griffiths and D. J. Higham, Journal of the Japan Society of Computational Fluid Dynamics, 9, 2000.
P40
Mean-square and asymptotic stability of numerical methods for stochastic ordinary differential equations, D. J. Higham, SIAM J. Num Anal, 38, 2000, 753-769.
P39
Theta method dynamics, G. J. Barclay, D. F. Griffiths and D. J. Higham, London Mathematical Society J. Comput. and Math., 3, 2000, 27-43.
P38
A-stability and stochastic mean-square stability, D. J. Higham, BIT, 40, 2000, 404-409.
P37
Runge-Kutta solutions of a hyperbolic conservation law with source term, M. A. Aves, D. F. Griffiths and D. J. Higham, SIAM Journal on Scientific Computing, 22, 2000, 20-38.
P36
The effect of quadrature on the dynamics of a discretised nonlinear integro-differential equation, M. A. Aves, P. J. Davies and D. J. Higham, Applied Numerical Mathematics, 32, 2000, 1-20.
P35
Phase space error control for dynamical systems, D. J. Higham, A. R. Humphries and R. J. Wain, SIAM Journal on Scientific Computing, 21, 2000, 2275-2294.
P34
Trust region algorithms and timestep selection, D. J. Higham, SIAM Journal on Numerical Analysis, 37, 1999, 194-210.
P33
Qualitative properties of modified equations, O. Gonzalez, A. M. Stuart and D. J. Higham, IMA Journal of Numerical Analysis, 19, 1999, 169-190.
P32
Structured backward error and condition of generalized eigenvalue problems, D. J. Higham and N. J.Higham, SIAM Journal on Matrix Analysis and Applications, 20, 1998, 493-512.
P31
Analysis of the dynamics of local error control via a piecewise continuous residual, D. J. Higham and A. M. Stuart, BIT, 38, 1998, 44-57.
P30
Regular Runge-Kutta pairs, by D. J. Higham, Applied Numerical Mathematics, 25, 1997, 229-241.
P29
Time-stepping and preserving orthonormality, D. J. Higham, BIT, 37, 1997, 24-36.
P28
Does error control suppress spuriosity?, M. A. Aves, D. F. Griffiths and D. J. Higham, SIAM Journal on Numerical Analysis, 34, 1997, 756-778.
P27
Stepsize selection for tolerance proportionality in explicit Runge-Kutta codes, M. C. Calvo, D. J. Higham, J. M. Montijano and L. Rández, Advances in Computational Mathematics, 7, 1997, 361-382.
P26
Dynamics of constant and variable stepsize methods for a nonlinear population model with delay, D. J. Higham and T. Sardar, Applied Numerical Mathematics, 24, 1997, 425-438.
P25
Runge-Kutta type methods for orthogonal integration, D. J. Higham, Applied Numerical Mathematics, 22, 1996, 217-223.
P24
Non-normality effects in a discretised, nonlinear, reaction-convection-diffusion equation, D. J. Higham and B. Owren, Journal of Computational Physics, 124, 1996, 309-323.
P23
Global error estimation with adaptive explicit Runge-Kutta methods, M. C. Calvo, D. J. Higham, J. M. Montijano and L. Rández, IMA Journal of Numerical Analysis, 16, 1996, 47-63.
P22
Existence and stability of fixed points for a discretised nonlinear reaction-diffusion equation with delay, D. J. Higham and T. Sardar, Applied Numerical Mathematics, 18, 1995, 155-173.
P21
Equilibrium states of adaptive algorithms for delay differential equations, D. J. Higham and I.Th. Famelis, Journal of Computational and Applied Mathematics, 58, 1995, 151-169.
P20
Condition numbers and their condition numbers, D. J. Higham, Linear Algebra and Its Applications, 214, 1995, 193-214.
P19
Runge-Kutta stability on a Floquet problem, D. J. Higham, BIT, 34, 1994, 88-98.
P18
Error control for initial value problems with discontinuities and delays, D. J.Higham, Applied Numerical Mathematics, 12, 1993, 315-330.
P17
Stiffness of ODEs, D. J. Higham and L. N. Trefethen, BIT, 33, 1993, 285-303.
P16
The tolerance proportionality of adaptive ODE solvers, D. J. Higham, Journal of Computational and Applied Mathematics, 45, 1993, 227-236.
P15
Componentwise perturbation theory for linear systems with multiple right-hand sides, D. J. Higham and N. J. Higham, Linear Algebra and Its Applications, 174, 1992, 111-130.
P14
The structured sensitivity of Vandermonde-like systems, S. G. Bartels and D. J. Higham, Numerische Mathematik, 62, 1992, 17-33.
P13
Monotonic piecewise cubic interpolation, with applications to ODE plotting, D. J. Higham, Journal of Computational and Applied Mathematics, 39, 1992, 287-294.
P12
Backward error and condition of structured linear systems, D. J. Higham and N. J. Higham, SIAM Journal on Matrix Analysis and Applications, 13, 1992, 162-175.
P11
Parallel defect control, by W. H. Enright and D. J. Higham, BIT, 31, 1991, 647-663.
P10
Global error versus tolerance for explicit Runge-Kutta methods, D. J. Higham, IMA Journal of Numerical Analysis, 11, 1991, 457-480.
P9
Remark on Algorithm 669, D. J. Higham, ACM Transactions on Mathematical Software, 17, 1991, 424-426.
P8
Runge-Kutta defect control using Hermite-Birkhoff interpolation, D. J. Higham, SIAM Journal on Scientific and Statistical Computing, 12, 1991, 991-999.
P7
Highly continuous Runge-Kutta interpolants, D. J. Higham, ACM Transactions on Mathematical Software, 17, 1991, 368-386.
P6
Embedded Runge-Kutta formulae with stable equilibrium states, D. J. Higham and G. Hall, Journal of Computational and Applied Mathematics, 29, 1990, 25-33.
P5
Robust defect control with Runge-Kutta schemes, D. J. Higham, SIAM Journal on Numerical Analysis, 26, 1989, 1175-1183.
P4
Defect estimation in Adams PECE codes, D. J. Higham, SIAM Journal on Scientific and Statistical Computing, 10, 1989, 964-976.
P3
Large growth factors in Gaussian elimination with pivoting, N. J. Higham and D. J. Higham, SIAM Journal on Matrix Analysis and Applications, 10, 1989, 155-164.
P2
Analysis of the Enright-Kamel partitioning method for stiff ODEs, D. J. Higham, IMA Journal of Numerical Analysis, 9, 1989, 1-14.
P1
Analysis of stepsize selection schemes for Runge-Kutta codes, G. Hall and D. J. Higham, IMA Journal of Numerical Analysis, 8, 1988, 305-310.


Refereed Book Chapters
Bc6
Dynamic communicability measures predict macroscale features of epidemics on temporal connectivity networks, to appear in Temporal Networks, edited by P. Holme and J. Saramaki, Springer, 2013.
Bc5
Infering and calibrating triadic closure in a dynamic network features of epidemics on temporal connectivity networks, to appear in Temporal Networks, edited by P. Holme and J. Saramaki, Springer, 2013.
Bc4
Is it safe to go out yet? Statistical inference in a zombie outbreak model, in Mathematical Modelling of Zombies, edited by R. Smith?, University of Ottawa Press, 2014, pp. 129--148.
Bc3
Random Graph Models and Their Application to Protein-Protein Interaction Networks, by D. J. Higham and N. Przulj, Chapter 14, pages 290-308, Handbook of Statistical Systems Biology, edited by D. Balding, M. Girolami and M. Stumpf, Wiley. 2011.
Bc2
NESSIE: Network Example Source Supporting Innovative Experimentation, by A. Taylor and D. J. Higham, Chapter 5, pages 85-106, in Network Science: Complexity in Nature and Technology, Chapter 1, pages 1-11, edited by E. Estrada, M. Fox, D. J. Higham and G.-L. Oppo, Springer, 2010.
Bc1
MAPLE and MATLAB for Stochastic Differential Equations in Finance, D. J. Higham and P. E. Kloeden, in Programming Languages and Systems in Computational Economics and Finance, edited by Søren S. Neilsen, Kluwer, 2002, 233-270.


Refereed Conference Papers
C9
Dynamic targeting in an online social medium, P. Laflin, A. V. Mantzaris, P. Grindrod, F. Ainley, A. Otley and D. J. Higham, to appear in Social Informatics 2012, Lausanne.
C8
Demonstration of dynamic targeting in an online social medium, P. Laflin, A. V. Mantzaris, P. Grindrod, F. Ainley, A. Otley and D. J. Higham, real time demonstration and demo paper to appear in Social Informatics 2012, Lausanne.
C7
Computing mean first exit times for stochastic processes using multilevel Monte Carlo, D. J. Higham and M. Roj, Proceedings of the 2012 Winter Simulation Conference, edited by C. Laroque, J. Himmelspach, R. Pasupathy, O. Rose and A. M. Uhrmacher, 2012, Berlin.
C6
Analysis of the singular value decomposition as a tool for processing microarray expression data, D. J. Higham, G. Kalna and J. K. Vass, Proceedings of ALGORITMY 2005, Conference on Scientific Computing, Slovak University of Technology, 250-259, Slovakia, 2005.
C5
Reordering diffusion-based connectivity matrices to define anatomical networks of the human brain, T. E. J. Behrens, H. Johansen-Berg, S. M. Smith, I. Drobnjak, J. M. Brady, P. M. Matthews and D. J. Higham, Proceedings of the International Society for Magnetic Resonance in Medicine 12th Scientific Meeting, Kyoto, 2004.
C4
Connectivity based anatomical parcellation of cortical grey matter, H. Johansen-Berg, T. E. J. Behrens, I. Drobnjak, S. M. Smith, D. J. Higham and P. M. Matthews, Proceedings of the 10th International Conference for Functional Mapping of the Human Brain, Budapest, 2004.
C3
Runge-Kutta and MacCormack dynamics, D. F. Griffiths and D. J. Higham, Proceedings of the 8th International Symposium on Computational Fluid Dynamics (CD ROM format), Bremen, Sep. 1999.
C2
The reliability of standard local error control algorithms for initial value ordinary differential equations, D. J. Higham, Proceedings of the IFIP Conference on The Quality of Numerical Software, R.F. Boisvert, Ed. 1997, 315-325, Chapman & Hall.
C1
Runge-Kutta equilibrium theory for a mixed relative-absolute error measure, D. J. Higham and G. Hall, Proceedings of the 1989 IMA Conference on Computational ODEs, J.R. Cash and I. Gladwell, Eds 1992, 73-85, Oxford University Press.


Invited (Unrefereed) Contributions to Proceedings and Books
I6
Complex networks: An invitation, by E. Estrada, M. Fox, D. J. Higham and G.-L. Oppo, in Network Science: Complexity in Nature and Technology, Chapter 1, pages 1-11, edited by E. Estrada, M. Fox, D. J. Higham and G.-L. Oppo, Springer, 2010.
I5
Mathematical and computational modeling of post-transcriptional gene regulation by microRNAs, by R Khanin and D. J. Higham, in MicroRNA Profiling in Cancer: A Bioinformatics Perspective, Chapter 10, pages 197-216, edited by Yuriy Gusev, World Scientific, 2009.
I4
Multidimensional partitioning and bi-partitioning: analysis and application to gene expression datasets, D. J. Higham, G. Kalna and J. K. Vass, in Proceedings of the International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2006, Editors R. Criado, D. Estep, M. A. Pérez Garcia, J. Vigo-Aguiar, Madrid, pages 414-425, 2006. Extended version appeared in International Journal of Computer Mathematics: see [P72]
I3
Finite differences in a small world, D.J. Higham, in the Proceedings of the 20th Biennial Conference on Numerical Analysis, Dundee, D.F. Griffiths and G.A. Watson, Eds, University of Dundee Numerical Analysis Report NA/217, pages 81-84, 2003.
I2
Fixed points and spurious modes of a nonlinear infinite-step map, M. A. Aves, P. J. Davies and D. J. Higham, in Numerical Analysis: A.R. Mitchell 75th Birthday Volume, D.F. Griffiths and G.A. Watson, Eds 1996, 21-38, World Scientific.
I1
The dynamics of a discretised nonlinear delay differential equation, D. J. Higham, in the Proceedings of the 15th Biennial Conference on Numerical Analysis, Dundee, G.A. Watson and D.F. Griffiths, Eds 1993, Pitman Research Notes in Mathematics, Volume 303, pages 167-179, Longman Scientific and Technical.