Summary
Mauricio Barahona obtained a PhD in Theoretical Physics (Dynamical Systems) from the Massachusetts Institute of Technology (MIT) under the supervision of Steve Strogatz in the Department of Mathematics. His thesis co-advisors were Mehran Kardar (Physics) and Terry Orlando (EECS). His thesis dealt with the spatio-temporal dynamics of networks of Josephson junctions - superconducting electronic devices that can be described as coupled nonlinear oscillators. Concurrently with his PhD work, he developed methods for nonlinear data analysis based on dynamical embeddings and time series analysis.
He then obtained Fellowships to conduct postdoctoral research, first at Stanford University and then at the California Institute of Technology. At Stanford, he worked with Mac Beasley on properties of oscillator synchronization with applications to pattern detection. At Caltech, he worked with John Doyle in the Department of Control and Dynamical Systems on rigorous bounds of model reduction techniques for dynamical systems. He also developed his research on the links between dynamics and graph-theoretical properties aimed at the analysis of network dynamics.
He joined the newly formed Department of Bioengineering at Imperial as a Lecturer in 2001 and became a Reader in Biomathematics in 2004. In 2011, he moved to the Department of Mathematics as Chair of Biomathematics. Since 2016, he is Director of the EPSRC Centre for Mathematics of Precision Healthcare.
Selected Publications
Journal Articles
Sapienza R, Barahona M, Saxena D, et al., 2022, Sensitivity and spectral control of network lasers, Nature Communications, Vol:13, ISSN:2041-1723, Pages:1-7
Strömich L, Wu N, Barahona M, et al., 2022, Allosteric Hotspots in the Main Protease of SARS-CoV-2., J Mol Biol, Vol:434
Wu N, Yaliraki SN, Barahona M, 2022, Prediction of Protein Allosteric Signalling Pathways and Functional Residues Through Paths of Optimised Propensity, Journal of Molecular Biology, Vol:434, ISSN:0022-2836, Pages:167749-167749
Myall A, Price J, Peach R, et al., 2022, Predicting hospital-onset COVID-19 infections using dynamic networks of patient contact: an international retrospective cohort study, The Lancet Digital Health, Vol:4, ISSN:2589-7500, Pages:e573-e583
Rodrigues D, Kreif N, Lawrence-Jones A, et al., 2022, Reflection on modern methods: constructing directed acyclic graphs (DAGs) with domain experts for health services research, International Journal of Epidemiology, Vol:51, ISSN:0300-5771
Peach R, Arnaudon A, Barahona M, 2022, Relative, local and global dimension in complex networks., Nat Commun, Vol:13
Rodrigues D, Kreif N, Saravanakumar K, et al., 2022, Formalising triage in general practice towards a more equitable, safe, and efficient allocation of resources, British Medical Journal, Vol:377, ISSN:0959-535X
Qian Y, Expert P, Rieu T, et al., 2022, Quantifying the alignment of graph and features in deep learning, IEEE Transactions on Neural Networks, Vol:33, ISSN:1045-9227, Pages:1663-1672
Freischem LJ, Barahona M, Oyarzún DA, 2022, Prediction of gene essentiality using machine learning and genome-scale metabolic models
Laumann F, von Kuegelgen J, Kanashiro Uehara TH, et al., 2022, Quantitative assessment of complex interlinkages, key objectives and nexuses amongst the Sustainable Development Goals and climate change, The Lancet Planetary Health, Vol:6, ISSN:2542-5196
Beaney T, Clarke J, Woodcock T, et al., 2021, Patterns of healthcare utilisation in children and young people: a retrospective cohort study using routinely collected healthcare data in Northwest London, Bmj Open, Vol:11, ISSN:2044-6055, Pages:1-14
Liu Z, Peach R, Lawrance E, et al., 2021, Listening to mental health crisis needs at scale: using Natural Language Processing to understand and evaluate a mental health crisis text messaging service, Frontiers in Digital Health, Vol:3, ISSN:2673-253X, Pages:1-14
Ming DK, Myall AC, Hernandez B, et al., 2021, Informing antimicrobial management in the context of COVID-19: understanding the longitudinal dynamics of C-reactive protein and procalcitonin, Bmc Infectious Diseases, Vol:21
Mersmann S, Stromich L, Song F, et al., 2021, ProteinLens: a web-based application for the analysis of allosteric signalling on atomistic graphs of biomolecules, Nucleic Acids Research, Vol:49, ISSN:0305-1048, Pages:W551-W558
Chrysostomou S, Roy R, Prischi F, et al., 2021, Repurposed floxacins targeting RSK4 prevent chemoresistance and metastasis in lung and bladder cancer., Science Translational Medicine, Vol:13, ISSN:1946-6234
Myall AC, Peach RL, Weiße AY, et al., 2021, Network memory in the movement of hospital patients carrying drug-resistant bacteria, Applied Network Science, Vol:6, ISSN:2364-8228
Saavedra-Garcia P, Roman-Trufero M, Al-Sadah HA, et al., 2021, Systems level profiling of chemotherapy-induced stress resolution in cancer cells reveals druggable trade-offs, Proceedings of the National Academy of Sciences of the United States of America, Vol:118, ISSN:0027-8424
Peach RL, Arnaudon A, Schmidt JA, et al., 2021, HCGA: Highly comparative graph analysis for network phenotyping, Patterns, Vol:2, ISSN:2666-3899, Pages:100227-100227
Qian Y, Expert P, Panzarasa P, et al., 2021, Geometric graphs from data to aid classification tasks with Graph Convolutional Networks, Patterns, Vol:2, ISSN:2666-3899, Pages:100237-100237
Maes A, Barahona M, Clopath C, 2021, Learning compositional sequences with multiple time scales through a hierarchical network of spiking neurons, PLOS Computational Biology, Vol:17, ISSN:1553-734X
Kuntz Nussio J, Thomas P, Stan G, et al., 2021, Approximations of countably-infinite linear programs over bounded measure spaces, SIAM Journal on Optimization, Vol:31, ISSN:1052-6234, Pages:604-625
Peach R, Greenbury S, Johnston I, et al., 2021, Understanding learner behaviour in online courses with Bayesian modelling and time series characterisation, Scientific Reports, Vol:11, ISSN:2045-2322
Schreglmann SR, Wang D, Peach RL, et al., 2021, Non-invasive suppression of essential tremor via phase-locked disruption of its temporal coherence, Nature Communications, Vol:12
Price JR, Mookerjee S, Dyakova E, et al., 2021, Development and delivery of a real-time hospital-onset COVID-19 surveillance system using network analysis, Clinical Infectious Diseases, Vol:72, ISSN:1058-4838, Pages:82-89
Kuntz J, Thomas P, Stan G-B, et al., 2021, Stationary Distributions of Continuous-Time Markov Chains: A Review of Theory and Truncation-Based Approximations, SIAM Review, Vol:63, ISSN:0036-1445, Pages:3-64
Clarke J, Murray A, Markar S, et al., 2020, A new geographic model of care to manage the post-COVID-19 elective surgery aftershock in England: a retrospective observational study, Bmj Open, Vol:10, ISSN:2044-6055, Pages:1-9
Clarke J, Beaney T, Majeed A, et al., 2020, Identifying naturally occurring communities of primary care providers in the English National Health Service in London, Bmj Open, Vol:10, ISSN:2044-6055, Pages:1-7
Arnaudon A, Peach R, Barahona M, 2020, Scale-dependent measure of network centrality from diffusion dynamics, Physical Review Research, Vol:2, ISSN:2643-1564
Gosztolai A, Barahona M, 2020, Cellular memory enhances bacterial chemotactic navigation in rugged environments, Communications Physics, Vol:3, ISSN:2399-3650
Peach RL, Arnaudon A, Barahona M, 2020, SEMI-SUPERVISED CLASSIFICATION ON GRAPHS USING EXPLICIT DIFFUSION DYNAMICS, Foundations of Data Science, Vol:2, Pages:19-33
Greenbury S, Barahona M, Johnston I, 2020, HyperTraPS: Inferring probabilistic patterns of trait acquisition in evolutionary and disease progression pathways, Cell Systems, Vol:10, ISSN:2405-4712, Pages:39-51
Liu Z, Barahona M, 2020, Graph-based data clustering via multiscale community detection, Applied Network Science, Vol:5, ISSN:2364-8228, Pages:1-20
Tonn MK, Thomas P, Barahona M, et al., 2020, Computation of Single-Cell Metabolite Distributions Using Mixture Models., Front Cell Dev Biol, Vol:8, ISSN:2296-634X
Hodges M, Yaliraki SN, Barahona M, 2019, Edge-based formulation of elastic network models, Physical Review Research, Pages:033211-033211
Peach R, Yaliraki S, Lefevre D, et al., 2019, Data-driven unsupervised clustering of online learner behaviour , Npj Science of Learning, Vol:4, ISSN:2056-7936
Kuntz Nussio J, Thomas P, Stan GB, et al., 2019, Bounding the stationary distributions of the chemical master equation via mathematical programming, Journal of Chemical Physics, Vol:151, ISSN:0021-9606
Maes A, Barahona M, Clopath C, 2019, Learning spatiotemporal signals using a recurrent spiking network that discretizes time, Plos Computational Biology, Vol:16, Pages:e1007606-e1007606
Schaub MT, Delvenne JC, Lambiotte R, et al., 2019, Multiscale dynamical embeddings of complex networks, Physical Review E, Vol:99, ISSN:1539-3755, Pages:062308-1-062308-18
Kuntz J, Thomas P, Stan G-B, et al., 2019, The exit time finite state projection scheme: bounding exit distributions and occupation measures of continuous-time Markov chains, SIAM Journal on Scientific Computing, Vol:41, ISSN:1064-8275, Pages:A748-A769
Tonn M, Thomas P, Barahona M, et al., 2019, Stochastic modelling reveals mechanisms of metabolic heterogeneity, Communications Biology, Vol:2, ISSN:2399-3642
Altuncu MT, Mayer E, Yaliraki SN, et al., 2019, From free text to clusters of content in health records: An unsupervised graph partitioning approach, Applied Network Science, Vol:4, ISSN:2364-8228
Gosztolai A, Carrillo JA, Barahona M, 2019, Collective search with finite perception: Transient dynamics and search efficiency, Frontiers in Physics, Vol:6, ISSN:2296-424X
Clarke JM, Warren LR, Arora S, et al., 2018, Guiding interoperable electronic health records through patient-sharing networks., Npj Digital Medicine, Vol:1, ISSN:2398-6352, Pages:65-65
Beguerisse M, Bosque G, Oyarzun DA, et al., 2018, Flux-dependent graphs for metabolic networks, Npj Systems Biology and Applications, Vol:4, ISSN:2056-7189
Hodges M, Barahona M, Yaliraki SN, 2018, Allostery and cooperativity in multimeric proteins: bond-to-bond propensities in ATCase, Scientific Reports, Vol:8, ISSN:2045-2322
Tomazou M, Barahona M, Polizzi K, et al., 2018, Computational re-design of synthetic genetic oscillators for independent amplitude and frequency modulation, Cell Systems, Vol:6, ISSN:2405-4712, Pages:508-520.e5
Liu Z, Barahona M, 2017, Geometric multiscale community detection: Markov stability and vector partitioning, Journal of Complex Networks, Vol:6, ISSN:2051-1329, Pages:157-172
Kiselev V, Kirschner K, Schaub MT, et al., 2017, SC3: consensus clustering of single-cell RNA-seq data, Nature Methods, Vol:14, ISSN:1548-7105, Pages:483-486
Schaub MT, Billeh YN, Anastassiou CA, et al., 2017, Emergence of Slow-Switching Assemblies in Structured Neuronal Networks (vol 11, e1004196, 2015), PLOS Computational Biology, Vol:13, ISSN:1553-734X
Dattani J, Barahona M, 2017, Stochastic models of gene transcription with upstream drives: Exact solution and sample path characterisation, Journal of the Royal Society Interface, Vol:14, ISSN:1742-5689
Beguerisse-Diaz M, McLennan AK, Garduño-Hernández G, et al., 2017, The 'who' and 'what' of #diabetes on Twitter, Digital Health, Vol:3, ISSN:2055-2076, Pages:1-29
Schaub MT, O'Clery N, Billeh YN, et al., 2016, Graph partitions and cluster synchronization in networks of oscillators, Chaos, Vol:26, ISSN:1054-1500
Beguerisse Diaz M, Desikan R, Barahona M, 2016, Linear models of activation cascades: analytical solutions and coarse-graining of delayed signal transduction, Journal of the Royal Society Interface, Vol:13, ISSN:1742-5689
Amor BRC, Schaub MT, Yaliraki S, et al., 2016, Prediction of allosteric sites and mediating interactions through bond-to-bond propensities, Nature Communications, Vol:7, ISSN:2041-1723, Pages:1-13
Bacik KA, Schaub MT, Beguerisse-Diaz M, et al., 2016, Flow-Based Network Analysis of the Caenorhabditis elegans Connectome, PLOS Computational Biology, Vol:12, ISSN:1553-734X
Kuntz J, Ottobre M, Stan G-B, et al., 2016, BOUNDING STATIONARY AVERAGES OF POLYNOMIAL DIFFUSIONS VIA SEMIDEFINITE PROGRAMMING, SIAM Journal on Scientific Computing, Vol:38, ISSN:1064-8275, Pages:A3891-A3920
Sim A, Yaliraki SN, Barahona M, et al., 2015, Great cities look small., Journal of the Royal Society Interface, Vol:12, ISSN:1742-5689
Noseda M, Harada M, McSweeney S, et al., 2015, PDGFRα demarcates the cardiogenic clonogenic Sca1(+) stem/progenitor cell in adult murine myocardium, Nature Communications, Vol:6, ISSN:2041-1723
Wang B, Barahona M, Buck M, 2015, Amplification of small molecule-inducible gene expression via tuning of intracellular receptor densities, Nucleic Acids Research, Vol:43, ISSN:0305-1048, Pages:1955-1964
Branch T, Girvan P, Barahona M, et al., 2015, Introduction of a Fluorescent Probe to Amyloid-beta to Reveal Kinetic Insights into Its Interactions with Copper(II), Angewandte Chemie - International Edition, Vol:54, ISSN:1433-7851, Pages:1227-1230
Beguerisse-Díaz M, Garduño-Hernández G, Vangelov B, et al., 2014, Interest communities and flow roles in directed networks: the Twitter network of the UK riots, J. R. Soc. Interface 6 December 2014, Vol:11
Georgiou PS, Barahona M, Yaliraki SN, et al., 2014, On memristor ideality and reciprocity, Microelectronics Journal, Vol:45, ISSN:0026-2692, Pages:1363-1371
Billeh YN, Schaub MT, Anastassiou CA, et al., 2014, Revealing cell assemblies at multiple levels of granularity, Journal of Neuroscience Methods, Vol:236, ISSN:0165-0270, Pages:92-106
Wang B, Barahona M, Buck M, 2014, Engineering modular and tunable genetic amplifiers for scaling transcriptional signals in cascaded gene networks, Nucleic Acids Research
Lambiotte R, Delvenne JC, Barahona M, 2014, Random walks, Markov processes and the multiscale modular organization of complex networks, Ieee Transactions on Network Science and Engineering, Vol:1, Pages:76-90
Amor B, Yaliraki SN, Woscholski R, et al., 2014, Uncovering allosteric pathways in caspase-1 using Markov transient analysis and multiscale community detection, Molecular Biosystems, Vol:10, ISSN:1742-206X, Pages:2247-2258
Wang B, Barahona M, Buck M, 2012, A modular cell-based biosensor using engineered genetic logic circuits to detect and integrate multiple environmental signals, Biosensors & Bioelectronics, Vol:40, ISSN:0956-5663, Pages:368-376
Schaub MT, Delvenne J-C, Yaliraki SN, et al., 2012, Markov Dynamics as a Zooming Lens for Multiscale Community Detection: Non Clique-Like Communities and the Field-of-View Limit, PLOS One, Vol:7, ISSN:1932-6203
Georgiou PS, Barahona M, Yaliraki SN, et al., 2011, Device Properties of Bernoulli Memristors, Proceedings of the IEEE, Vol:100, ISSN:0018-9219, Pages:1-13
Delvenne J-C, Yaliraki SN, Barahona M, 2010, Stability of graph communities across time scales, Proceedings of the National Academy of Sciences of the United States of America, Vol:107, ISSN:0027-8424, Pages:{12755-12760}-{12755-12760}
Anastassiou CA, Montgomery SM, Barahona M, et al., 2010, The Effect of Spatially Inhomogeneous Extracellular Electric Fields on Neurons, Journal of Neuroscience, Vol:30, ISSN:0270-6474, Pages:{1925-1936}-{1925-1936}
Strelkowa N, Barahona M, 2010, Switchable genetic oscillator operating in quasi-stable mode, Journal of the Royal Society Interface, Vol:7, ISSN:1742-5689, Pages:{1071-1082}-{1071-1082}
Lambiotte R, Delvenne J-C, Barahona M, 2008, Laplacian Dynamics and Multiscale Modular Structure in Networks
Chang HH, Hemberg M, Barahona M, et al., 2008, Transcriptome-wide noise controls lineage choice in mammalian progenitor cells, Nature, Vol:453, ISSN:0028-0836, Pages:{544-U10}-{544-U10}
Barahona M, Pecora LM, 2002, Synchronization in small-world systems, Physical Review Letters, Vol:89, ISSN:0031-9007
Barahona M, Poon CS, 1996, Detection of nonlinear dynamics in short, noisy time series, Nature, Vol:381, ISSN:0028-0836, Pages:215-217
Chapters
Schaub MT, Delvenne J-C, Lambiotte R, et al., 2019, Structured networks and coarse-grained descriptions: a dynamical perspective, Advances in Network Clustering and Blockmodeling, Editor(s): Doreian, Batagelj, Ferligoj, John Wiley and Sons, Ltd, Pages:333-361, ISBN:9781119224709
Amor B, Vuik S, Callahan R, et al., 2016, Community detection and role identification in directed networks: understanding the Twitter network of the care.data debate, Dynamic Networks and Cyber-Security, Editor(s): Adams, Heard, World Scientific, Pages:111-136, ISBN:978-1-60558752-3
Delvenne J-C, Schaub MT, Yaliraki S, et al., 2013, The stability of a graph partition: A dynamics-based framework for community detection, Dynamics On and Of Complex Networks, Volume 2, Editor(s): Mukherjee, Choudhury, Peruani, Ganguly, Mitra, Springer, Pages:221-242, ISBN:978-1-4614-6728-1
Conference
Liu Z, Barahona M, 2021, Similarity measure for sparse time course data based on Gaussian processes, Uncertainty in Artificial Intelligence 2021, PMLR, Pages:1332-1341
Laumann F, von Kuegelgen J, Barahona M, 2021, Kernel two-sample and independence tests for non-stationary random processes, ITISE 2021 (7th International conference on Time Series and Forecasting), https://www.mdpi.com/2673-4591/5/1/31, Pages:1-13
Altuncu MT, Mayer E, Yaliraki SN, et al., From Text to Topics in Healthcare Records: An Unsupervised Graph Partitioning Methodology, 2018 KDD Conference Proceedings - MLMH: Machine Learning for Medicine and Healthcare
Jadbabaie A, Motee N, Barahona M, On the stability of the Kuramoto model of coupled nonlinear oscillators, Pages:{4296-4301}-{4296-4301}, ISSN:0743-1619
Patents
Poon, C.S., Barahona M, 1999, Method and apparatus for detecting nonlinearity and chaos in a dynamical system, US, US5938594 A
Poon, C.S., Barahona, M., Merrill, C.K., 1996, Method and apparatus for detecting nonlinearity in a dynamical system, US, United States Patent 5792062, World WO1997043722