The dynamics of biological systems is driven by interactions between many elements at a given level of biological organisation (e.g. molecular, cellular, organism), but also by the couplings that exist between said levels (e.g. from molecules to cells to populations). Such couplings are highly non-linear and make the analysis of complex biological systems extremely challenging . The remit of the Mathematical and Computational Biology is the development of new theory, models, techniques, and tools that are relevant to biologists and clinicians. For this purpose we use a plethora of mathematical techniques including stochastic multiscale models, dynamical systems theory, singular perturbation analysis, bifurcation analysis, morphometrics, dimensional reduction tools and efficient simulation methods, as well as statistics, machine learning or optimization. We tackle issues such as understanding how genetic variation leads to variation in the characteristics of organisms, the so-called genotype-phenotype map, the arising of such map in embryonic development, its influence in the direction of phenotypic evolution. We also formulate new models of virus evolution and therapies that account for intrinsic heterogeneity and noise, we study the design of new strategies to avoid drug resistance induced by cancer-cell heterogeneity and analyze the mechanisms of ageing. Our research is collaborative in nature and we make an effort to keep close collaborations with both biologists and medical practitioners.
RESEARCH LINES
Cancer Modeling | Tomás Alarcón
Most phenomena studied by the Natural Sciences, from Material Sciences to Astrophysics, are multi-scale processes, i.e. they involve the coupling of multiple different processes characterised by widely-ranging time and length scales, with the macroscopic behaviour emerging from the complex interactions between them. Whilst considerable progress has been done in dealing with such problems in the Physical Sciences, the success achieved so far in the Biological Sciences is rather more limited. This is partly due to the fact that the individual components of biological systems (e.g. cells) are much more complex than their counterparts in physical systems and, therefore, new methods and models are needed to analyse multi-scale processes in Biology. Such is the remit of the Computational & Mathematical Biology group at CRM: To propose new models relevant to experimental biologists and clinicians and develop the analytical and computational tools necessary for their analysis. We pay special attention to problems with clinical relevance, in particular those related to cancer.
The research activity of our group is developed along the following lines:
- Multiscale modelling of tumour growth and tumour-induced angiogenesis
- Evolutionary dynamics of populations with complex structure, in particular cell populations with hierarchical structure and genotype-phenotype map
- Mathematical modelling of the cell-cycle
- Stochastic modelling of receptor tyrosine kinases
- Tumour dormancy
Nonlinear Dynamics and Evolution (NoDE) | Josep Sardanyés
Our laboratory is interested in understanding biological nonlinear phenomena. Our research is focused on Biomedicine (including cancer and viruses), in systems and synthetic Biology as well as in theoretical ecology. To do so we use the qualitative theory of dynamical systems and computer simulations (stochastic dynamics and spatially-extended systems).
We are especially interested in characterizing both asymptotic and transient dynamics of these systems and their sensitivity to parameter changes. That is, understand which bifurcations govern transitions in biological systems.
GROUP LEADERS
Personal Website
Tomás Alarcon
ICREA – CRM
talarcon@crm.cat
I obtained my PhD in Theoretical Physics from the University of Barcelona in 2000. After that I spent many wonderful years working as a postdoc at the University of Oxford, UK (2001-2003), University College London, UK (2003-2006), and Imperial College London, UK (2006-2009). I briefly held a senior researcher and group leader position at BCAM, Bilbao, Spain (2009-2010), after which I moved the Centre Recerca Matematica where I lead the Cancer Modelling Group. I have also held visiting fellowships at the Universidad Complutense de Madrid, IIMAS (UNAM, Mexico DF), OCCAM (University of Oxford, UK), the Mathematical Institute (University of Oxford, UK), and the Mathematical Biosciences Institute (Columbus, Ohio, USA). In October 2015, I was appointed to an ICREA Research Professorship at the Centre de Recerca Matematica.
Personal Website
Josep Sardanyés
CRM
jsardanyes@crm.cat
I completed a BSc in Biology at University of Barcelona (2002) and went on to earn a Master and a PhD in Biomedicine (2009) at the Complex Systems Lab (CSL, Universitat Pompeu Fabra). During my PhD thesis I worked on dynamical systems and complexity in Biology. Upon obtaining my PhD degree, I moved to Valencia where I took up a postdoc position at the Institute of Molecular and Cellular Plant Biology (Consejo Superior de Investigaciones Científicas-UPV). In 2011 I moved to The David J. Gladstone Institutes for a second postdoc (University of California San Francisco, USA), where I focused on the evolutionary dynamics of RNA virus. Then, I moved again to the CSL where I completed a third postdoc (2012-2016) working on cancer evolution, theoretical ecology and systems and synthetic biology. In 2017 I became a researcher at the CRM.
Ielyaas Cloete
Daria Stepanova
Oriol Llopis
PUBLICATIONS
Publications from the last 5 years
Calsina, À & Cuadrado, S. & Vidiella, B. & Sardanyés. J. (2023). About ghost transients in spatial continuous media. Chaos, Solitons & Fractals, 166, 112915. doi: http://dx.doi.org/10.1016/j.chaos.2022.112915
Carrasco-Mantis, A. & Alarcón, T. & Sanz-Herrera, J.A. (2023). An in silico study on the influence of
extracellular matrix mechanics on vasculogenesis. Computer Methods and Programs in Biomedicine.
231, 107369. doi: https://doi.org/10.1016/j.cmpb.2023.107369
Lázaro, T. J. & Alarcón, T. & Garay, C.P. & Sardanyés, J. (2023). Semiclassical theory predicts stochastc
ghosts scaling. Proceedings of the Royal Society A. 479: 20220621. doi: http://doi.org/10.1098/rspa.2022.0621
Chakraborty, S. & Ivančić F. & You, Y-J. (2023). Role of surface tension effect at the deformed free surface
of chemotaxis coupling flow system: weakly nonlinear study. Physics of Fluids 35, 091908. doi: https://
doi.org/10.1063/5.0166650.
Cano-Fernández, H. & Tissot, T. & Brun-Usan, M. & Salazar-Ciudad, I. (2023). On the origins of
developmental robustness: modeling buffering mechanisms against cell-level noise. Development 15
December 2023; 150 (24): dev201911. doi: https://doi.org/10.1242/dev.201911
Stepanova, D. & Byrne, H. M. & Maini, P. K. & Alarcón, T. (2023). Computational modeling of angiogenesis:
The importance of cell rearrangements during vascular growth. WIREs Mechanisms of Disease, 16(2),
e1634. doi: https://doi.org/10.1002/wsbm.1634
D.Stepanova, H.M. Byrne, P.K. Maini, T. Alarcon. A multiscale model of complex endothelial cell dynamics in early angiogenesis. Posted in bioRxiv.
M.O. Bernabeu, J. Kory, J.A. Grogan, B. Markelc, A. Beardo-Ricol, M. d’Avezac, J. Kaeppler, N. Daly, J. Hetherington, T. Krueger, P.K. Maini, J.M. Pitt-Francis, R.J. Muschel, T. Alarcon, H.M. Byrne. Abnormal morphology biases haematocrit distribution in tumour vasculature and contributes to heterogeneity in tissue oxygenation. Posted in bioRxiv.
A.I. Rodriguez-Villarreal, L. Ortega-Tana, J. Cid, A. Hernendez-Machado, T. Alarcon, P. Miribel-Catala, J. Colomer-Farrarons. An integrated detection method for flow viscosity measurements in microdevices. IEEE Transactions on Biomedical Engineering. Accepted for publication (2020).
E. Cuyas, S. Verdura, B. Martin-Castillo, T. Alarcon, R. Lupu, J. Bosch-Barrera, J.A. Menendez. Tumor-cell-intrinsic immunometabolism and precision nutrition in cancer immunotherapy. 12, 1757 (2020). doi: 10.3390/cancers12071757
E. Cuyas, J. Gumizio, S. Verdura, J. Brunet, J. Bosch-Barrera, B. Martin-Castillo, T. Alarcon, J.A. Encinar, A. Martin, and J.A. Menendez. The LSD1 inhibitor iadademstat (ORY-1001) targets SOX2-driven breast cancer stem cells: A potential epigenetic therapy in luminal-B and HER2-positive breast cancer subtypes. Aging. 12, 4794-4814 (2020). doi: 10.18632/aging.102887
R.A. Barrio, T. Alarcon, A. Hernandez-Machado. The dynamics of shapes of vesicle membranes with time dependent spontaneous curvature. PLoS One. 15, e0227562 (2020). doi: 10.1371/journal.pone.0227562
J.A. Menendez, E. Cuyas, N. Folguera-Blasco, S. Verdura, B. Martin-Castillo, T. Alarcon. In silico clinical trials for anti-aging therapies. Aging. 11, 6591-6601 (2019). doi: 10.18632/aging.102180
A.V. Ponce-Bobadilla, T. Carraro, H.M. Byrne, P.K. Maini, T. Alarcon. Age-structure can account for delayed logistic proliferation of scratch assays. Bull. Math. Biol. 81, 2706-2724 (2019). Preprint version available from bioRxiv
Vidiella B, Valverde S, Fontich E, Sardanyés J, Transients in simple trophic chains with facilitation: the impact of habitat destruction. Theoretical Ecology (submitted)
Sardanyés J, Raich C, Alarcón T. Noise-induced stabilization of saddle-node ghosts. Physical Review E (submitted)
Solé R, Sardanyés J, Elena SF, Phase transitions in Virology. Virus Evolution (submitted)
Zaldo Q, Serra I, Alsedà Ll, Sardanyés J, Maneja R, Reviewing the reliability of Land Use and Land Cover Data in studies relating human health to the environment. Land Use Policy (submitted)
Vidiella B, Sardanyés J, Solé R, Synthetic soil crusts against green-desert transitions: a spatial model. Royal Society Open Science (submitted)
Penella C, Alarcón T, Sardanyés J, Spatio-temporal dynamics of cancer phenotypic quasispecies under targeted therapy. Proceedings of the 9th International Congress on Industrial and Applied Mathematics (ICIAM) (2020) Accepted
Nurtay A, Hennessy MG, Alsedà Ll, Elena SF, Sardanyés J, Host-virus evolutionary dynamics with specialist and generalist infection strategies: bifurcations, bistability and chaos. Chaos (2020) Accepted
Perona J, Fontich E, Sardanyés J, Dynamical effects of loss of cooperation in discrete-time hypercycles. Physica D: Nonlinear Phenomena 406: 132425 (2020)
Conde-Pueyo N, Vidiella B, Sardanyés J, Berdugo M, Maestre FT, de Lorenzo V, Solé R, Synthetic biology for terraformation: lessons from Mars, Earth, and the microbiome. Life 10(2): 14 (2020)
Alsedà Ll, Vidiella B, Solé R, Lázaro JT, Sardanyés J, Dynamics in a time-discrete food-chain model with strong pressure on preys. Communications in Nonlinear Science and Numerical Simulation 84, 105187 (2020)
Sardanyés J, Piñero J, Solé R, Habitat loss-induced tipping points in metapopulations with facilitation. Population Ecology 1-14 (2019)
Sardanyés J. Viruses: Agents of evolutionary invention. The Quarterly Review of Biology 94(1): 90-91 (2019)
Nurtay A, Hennessy MG, Sardanyés J, Alsedà Ll, Elena SF, Theoretical conditions for the coexistence of viral strains with differences in phenotypic traits: a bifurcation analysis. Royal Society Open Science 6: 181179 (2019)
Fornés J, Lázaro JT, Alarcón T, Elena SF, Sardanyés J, Viral replication modes in single-peak fitness landscapes: A dynamical systems analysis. Journal of Theoretical Biology 460: 170-183 (2019)
Daniel J. Toddie-Moore Martti P. Montanari Ngan Vi Tran Evgeniy M. Brik Hanna Antson Isaac Salazar-Ciudad Osamu Shimmi, Mechano-chemical feedback mediated competition for BMP signalling leads to pattern formation
Salazar-Ciudad, Isaac. Why call it developmental bias when it is just development?. Biology Direct, 2021, vol. 16, p. 1-13.
Milocco, L., & Salazar-Ciudad, I. (2022). Evolution of the G Matrix under Nonlinear Genotype-Phenotype Maps. The American Naturalist, 199(3), 420-435.
Hagolani, P. F., Zimm, R., Vroomans, R., & Salazar-Ciudad, I. (2021). On the evolution and development of morphological complexity: A view from gene regulatory networks. PLoS computational biology, 17(2), e1008570.
Coronado-Zamora, M., Salvador-Martínez, I., Castellano, D., Barbadilla, A., & Salazar-Ciudad, I. (2019). Adaptation and conservation throughout the Drosophila melanogaster life-cycle. Genome biology and evolution, 11(5), 1463-1482.
Hagolani, P. F., Zimm, R., Marin-Riera, M., & Salazar-Ciudad, I. (2019). Cell signaling stabilizes morphogenesis against noise. Development, 146(20), dev179309.
PROJECTS
PDC2022-133020-I00
Sistemas dinámicos y matemática computacional para la optimización de partículas interferentes terapéuticas como terapia antiviral
PIs: Josep Sardanyés / Tomás Alarcón
Funded by MICINN
PID2021-127896OB-I00
HENOCANDYN: Heterogeneity and noise as engines of cancer evolution: A multiscale dynamical systems approach
PIs: Tomás Alarcón / Josep Sardanyés
Funded by MICINN
PCI2022-132926
MPA4SUSTAINABILITY: Enhancing Marine Protected Areas’ role in restoring biodiversity while maintaining access to ecosystem services
PI: Josep Sardanyés
Funded by IFD, ANR, FCT, AEI, SEPA
2021-SGR-00874
Los puntales matemáticos de la biología integrativa de sistemas
PIs: Tomás Alarcón
Funded by MINECO
PID2021-122930NB-I00
Predicting the evolution of complex phenotypes by contrasting and combining quantitative genetics and mathematical models of development
PI: Isaac Salazar
Funded by Ministerio de Ciencia, Innovación y Universidades
CNS2022-135397
Testeando la predicibilidad de la evolución y del mapa genotipofenotipo
PI: Isaac Salazar
Funded by Ministerio de Ciencia, Innovación y Universidades
EXTERNAL COLLABORATORS
CSIC Associated Unit (DySCoVir) between the I2SysBio and CRM
The I2SysBio and the Centre de Recerca Matemàtica (Mathematical Research Center) launch the associated unit Dynamic Systems and Computational Virology (DysCoVir) — News — DysCoVir website