2020

  • BANDIERA L, CABEZA D GOMEZ, BALSA-CANTO E, MENOLASCINA F. 2019. Bayesian model selection in synthetic biology: factor levels and observation functions. IFAC-PapersOnLine 52(26): 24-31.. DOI: 10.1016/j.ifacol.2019.12.231.
  • YORDANOV P, STELLING J, OTERO-MURAS I, VALENCIA A. 2020. BioSwitch: A tool for the detection of bistability and multi-steady state behaviour in signalling and gene regulatory networks. Bioinformatics, 36(5), Pp. 1640-1641.. DOI: 10.1093/bioinformatics/btz746.
  • VILAS C, ALONSO AA, BALSA-CANTO E, LÓPEZ-QUIROGA E, TRELEA IC. 2020. Model-based real time operation of the freeze-drying process. Processes, 8(3), Art. Nº. 325.. DOI: 10.1016/j.dsr.2020.103259.
  • BALSA-CANTO E, ALONSO-DEL-REAL J, QUEROL A. 2020. Temperature Shapes Ecological Dynamics in Mixed Culture Fermentations Driven by Two Species of the Saccharomyces Genus. Frontiers In Bioengineering And Biotechnology, 8, Art. Nº. 915.. DOI: 10.3389/fbioe.2020.00915.
  • TSIPA A, PITT JA, BANGA JR, MANTALARIS A. 2020. A dual-parameter identification approach for data-based predictive modeling of hybrid gene regulatory network-growth kinetics in Pseudomonas putida mt-2. Bioprocess and Biosystems Engineering. DOI: 10.1007/s00449-020-02360-2.
  • BALSA-CANTO E, LÓPEZ-NÚÑEZ A, VÁZQUEZ C. 2020. A two-dimensional multi-species model for different Listeria monocytogenes biofilm structures and its numerical simulation. Applied Mathematics and Computation, 384, art. no. 125383. DOI: 10.1016/j.amc.2020.125383.
  • REYES BC, OTERO-MURAS I, SHUEN MT, TARTAKOVSKY AM, PETYUK VA. 2020. CRNT4SBML: a Python package for the detection of bistability in biochemical reaction networks. Bioinformatics (Oxford, England), 36(12), pp. 3922-3924. DOI: 10.1093/bioinformatics/btaa241.
  • MASSONIS G, VILLAVERDE AF. 2020. Finding and breaking lie symmetries: Implications for structural identifiability and observability in biological modelling. Symmetry, 12(3), art. no. 469. DOI: 10.3390/sym12030469.
  • DA-ROCHA J-M, SEMPERE J, PRELLEZO R, TABOADA-ANTELO L. 2020. Input controls and overcapitalization: a general equilibrium analysis of the Spanish Mediterranean Sea fisheries. Fisheries Research, 228, art. no. 105559. DOI: 10.1016/j.fishres.2020.105559.
  • BALSA-CANTO E, ALONSO-DEL-REAL J, QUEROL A. 2020. Mixed growth curve data do not suffice to fully characterize the dynamics of mixed cultures. Proceedings of the National Academy of Sciences of the United States of America, 117(2), pp. 811-813. DOI: 10.1073/pnas.1916774117.
  • VILAS C, MAURICIO-IGLESIAS M, GARCÍA MR. 2020. Model-based design of smart active packaging systems with antimicrobial activity. Food Packaging and Shelf Life, 24, art. no. 100446. DOI: 10.1016/j.fpsl.2019.100446.
  • TSIPA ARGYRO, ALAN PITT JAKE, BANGA JULIO R, MANTALARIS ATHANASIOS. 2020 . A dual-parameter identification approach for data-based predictive modeling of hybrid gene regulatory network-growth kinetics in Pseudomonas putida mt-2 . Bioprocess And Biosystems Engineering, 43, pages1671–1688. DOI: 10.1007/s00449-020-02360-2.

2019

 

  • GOMEZ CABEZA D BANDIERA L BALSA-CANTO E MENOLASCINA F. 2019. Information content analysis reveals desirable aspects of in vivo experiments of a synthetic circuit. 2019 IEEE Conference on Computational Intelligence in Bioinformatics and Computational Biology, CIBCB 2019, art. no. 8791449. DOI: 10.1109/CIBCB.2019.8791449.
  • VILLAVERDE AF, RAIMÚNDEZ E, HASENAUER J, BANGA JR. 2019. A Comparison of Methods for Quantifying Prediction Uncertainty in Systems Biology. IFAC-PapersOnLine, 52(26), pp. 45-51. DOI: 10.1016/j.ifacol.2019.12.234.
  • BANDIERA L, GOMEZ CABEZA D, BALSA-CANTO E, MENOLASCINA F. 2019. Bayesian model selection in synthetic biology: Factor levels and observation functions. IFAC-PapersOnLine, 52(26), pp. 24-31. DOI: 10.1016/j.ifacol.2019.12.231.
  • PÁJARO M OTERO-MURAS I VÁZQUEZ C ALONSO AA. 2019. Transient hysteresis and inherent stochasticity in gene regulatory networks. Nature communications, 10(1), p. 4581. DOI: 10.1038/s41467-019-12344-w.
  • VILLAVERDE AF, TSIANTIS N, BANGA JR. 2019. Full observability and estimation of unknown inputs states and parameters of nonlinear biological models. Journal of the Royal Society Interface 16(156): 20190043. DOI: 10.1098/rsif.2019.0043.
  • CAÑIZO JA, CARRILLO JA, PÁJARO M. 2019. Exponential equilibration of genetic circuits using entropy methods. Journal of Mathematical Biology, 78(1-2):373-411 DOI:10.1007/s00285-018-1277-z.
  • BANGA J,R, MENOLASCINA F. 2019. Computational methods enabling next-generation bioprocesses. Processes, 7(4): 214. DOI: 10.3390/pr7040214.
  • VILLAVERDE A,F, COSENTINO C, GÁBOR A, Szederkényi G. 2019. Computational Methods for Identification and Modelling of Complex Biological Systems. Complexity, 2019, art. no. 4951650. DOI: 10.1155/2019/4951650.
  • VILLAVERDE AF. 2019. Observability and Structural Identifiability of Nonlinear Biological Systems. Complexity, 2019, art. no. 8497093. DOI: 10.1155/2019/8497093.
  • PITT JA; BANGA JR. 2019. Parameter estimation in models of biological oscillators: an automated regularised estimation approach. BMC bioinformatics, 20(1):82. DOI: 10.1186/s12859-019-2630-y.
  • VILLAVERDE, AF; FRÖHLICH, F; WEINDL, D; HASENAUER, J; BANGA, JR. 2019. Benchmarking optimization methods for parameter estimation in large kinetic models. Bioinformatics (Oxford, England), 35(5): 830-838.. DOI: 10.1093/bioinformatics/bty736.
  • BANDIERA, L; KOTHAMACHU, V; BALSA-CANTO, E; SWAIN, PS; MENOLASCINA, F. 2019. Optimally designed vs intuition-driven inputs: The study case of promoter activity modelling. Proceedings of the IEEE Conference on Decision and Control, 2018-December, art. no. 8618920, pp. 1880-1885. DOI: 10.1109/CDC.2018.8618920.
  • OTERO-MURAS, I; BANGA, JR. 2019. Distilling robust design principles of biocircuits using mixed integer dynamic optimization. Processes, 7(2): 92. DOI: 10.3390/pr7020092.

2018

  • ALONSO AA; OTERO-MURAS I; PÁJARO M. 2018. Routes to Multiple Equilibria for Mass-Action Kinetic Systems. Complexity, 2018, art. no. 3912627.. DOI: 10.1155/2018/3912627.
  • OTERO-MURAS I, BANGA JR. 2018. Optimization-based prediction of fold bifurcations in nonlinear ODE models. IFAC-PapersOnLine,51(15):485-490. DOI: 10.1016/j.ifacol.2018.09.192.
  • BANDIERA L; HOU Z; KOTHAMACHU VB; BALSA-CANTO E SWAIN PS; MENOLASCINA F. 2018. On-line optimal input design increases the efficiency and accuracy of the modelling of an inducible synthetic promoter. Processes, 6(9), art. no. 148.. DOI: 10.3390/pr6090148.
  • PÁJARO M; OTERO-MURAS I; VÁZQUEZ C; ALONSO AA. 2018. Efficient simulation of stochastic gene regulatory networks⁎. IFAC-PapersOnLine, 51(19), pp. 84-85.. DOI: 10.1016/j.ifacol.2018.09.033.
  • MÉNDEZ-GONZÁLEZ JM; OTERO-MURAS I. 2018. Multistability in a prion replication interconnected cell reaction
  • VILLAVERDE AF; EVANS ND; CHAPPELL MJ; BANGA JR. 2018. Sufficiently Exciting Inputs for Structurally Identifiable Systems Biology Models. IFAC-PapersOnLine, 51(19), pp. 16-19.. DOI: 10.1016/j.ifacol.2018.09.015.
  • OTERO-MURAS I; BANGA JR. 2018. Mixed Integer Multiobjective Optimization Approaches for Systems and Synthetic Biology. IFAC-PapersOnLine, 51(19), pp. 58-61.. DOI: 10.1016/j.ifacol.2018.09.015.
  • PITT JA; GOMOESCU L; PANTELIDES CC; CHACHUAT B; BANGA JR. 2018. Critical Assessment of Parameter Estimation Methods in Models of Biological Oscillators⁎. IFAC-PapersOnLine, 51(19), pp. 72-75.. DOI: 10.1016/j.ifacol.2018.09.040.
  • TSIANTIS N; BALSA-CANTO E; BANGA JR. 2018. Optimality and identification of dynamic models in systems biology: An inverse optimal control framework. Bioinformatics, 34(14), pp. 2433-2440.. DOI: 10.1093/bioinformatics/bty139.
  • LE TTY; GARCÍA MR; NACHEV M;  GRABNER D; BALSA-CANTO E; HENDRIKS AJ; SURES B. 2018. Development of a PBPK Model for Silver Accumulation in Chub Infected with Acanthocephalan Parasites. Environmental Science and Technology, 52(21), pp. 12514-12525.. DOI: 10.1021/acs.est.8b04022.
  • ALONSO AA, BERMEJO R, PÁJARO M, VÁZQUEZ C. Numerical analysis of a method for a partial integro-differential equation model in regulatory gene networks. Mathematical Models and Methods in Applied Sciences, 28(10): 2069-2095 .DOI: 10.1142/S0218202518500495.
  • PROCOPIO A, DE ROSA S, GARCIA MR, COVELLO C, MEROLA A, SABATINO J, DE LUCA A, INDOLFI C AMATO F, COSENTINO C. Experimental Modeling and Identification of Cardiac Biomarkers Release in Acute Myocardial Infarction. IEEE Transactions on Control Systems Technology. . DOI: 10.1109/TCST.2018.2849068.
  • LIGON TS, FRÖHLICH F, CHIŞ OT, BANGA JR BALSA-CANTO E, HASENAUER J. 2018. GenSSI 2.0: Multi-experiment structural identifiability analysis of SBML models. Bioinformatics, 34(8),1421-1423. DOI: 10.1093/bioinformatics/btx735.
  • GARCÍA MR, VÁZQUEZ JA, TEIXEIRA IG, ALONSO AA. 2018.Corrigendum: Stochastic Individual-Based Modeling of Bacterial Growth and Division Using Flow Cytometry.  Frontiers in Microbiology, 9(MAR), art. no. 633. DOI: 10.3389/fmicb.2017.02626.
  • CASAS L, SAENZ-AGUDELO P, IRIGOIEN X. 2018. High-Throughput Sequencing and Linkage Mapping of a Clownfish Genome Provide. Scientific Reports, 8(1) art. no. 4073. DOI: 10.1038/s41598-018-22282-0.
  • HENRIQUES D, ALONSO-DEL-REAL  J, QUEROL A, BALSA-CANTO E. 2018. Saccharomyces cerevisiae and S. kudriavzevii synthetic wine fermentation performance dissected by predictive modeling. Frontiers in Microbiology, 9(FEB), art. no. 88. DOI:10.3389/fmicb.2018.00088. 
  • PÁJARO M, OTERO-MURAS I, VÁZQUEZ C, ALONSO AA. 2018. SELANSI: A toolbox for simulation of stochastic gene regulatory networks. Bioinformatics, 34(5): 893-895. DOI:10.1093/bioinformatics/btx645. 
  • GARCÍA MR, VÁZQUEZ JA, TEIXEIRA IG, ALONSO AA .2018. Stochastic individual-based modeling of bacterial growth and division using flow cytometry. Frontiers in Microbiology 8(JAN) art no 2626. DOI: 10.3389/fmicb.2017.02626.
  • VILAS C, ALONSO A.A, HERRERA J.R, BERNÁRDEZ M, GARCÍA M.R. 2018. A mathematical model to predict early quality attributes in hake during storage at low temperature. Journal of Food Engineering, 22: 11-19. DOI: 10.1016/j.jfoodeng.2017.11.005.

2017

  • BLATTMANN P, HENRIQUES D, ZIMMERMANN M,  FROMMELT F, SAUER U,  SAEZ-RODRIGUEZ J, AEBERSOLD R. 2017. Systems Pharmacology Dissection of Cholesterol Regulation Reveals Determinants of Large Pharmacodynamic Variability between Cell Lines. Cell Systems, 5(6):604-619.e7. DOI:10.1016/j.cels.2017.11.002.
  • LOPES C, ANTELO LT, FRANCO-URÍA A, ALONSO AA, PÉREZ-MARTÍN R. 2017. Chitin production from crustacean biomass: Sustainability assessment of chemical and enzymatic processes. Journal of Cleaner Production, 172: 4140-4151. DOI: 10.1016/j.jclepro.2017.01.082.
  • VILLAVERDE AF, BANGA JR. 2017. Dynamical compensation and structural identifiability of biological models: Analysis, implications, and reconciliation. PLoS Computational Biology, 13(11), art. no. e1005878. DOI: 10.1371/journal.pcbi.1005878.
  • VILLAVERDE AF, BANGA JR. 2017. Structural properties of dynamic systems biology models: Identifiability reachability and initial conditions. Processes 5(2) art. no. 29. DOI: 10.3390/pr5020029.
  • BALSA-CANTO E, VILAS C, LÓPEZ-NÚÑEZ A, MOSQUERA-FERNÁNDEZ M, BRIANDET R, CABO ML, VÁZQUEZ C. 2017. Modeling reveals the role of aging and glucose uptake impairment in L1A1 Listeria monocytogenes biofilm life cycle. Frontiers in Microbiology , 8(1): 2118. DOI:10.3389/fmicb.2017.02118.
  • ALONSO AA, OTERO-MURAS I. 2017. Wegscheider’s condition and passivity of open chemical reaction systems. IFAC-PapersOnLine 50(1):564-569 DOI: 10.1016/j.ifacol.2017.08.075.
  • DA-ROCHA JM, PRELLEZO R, SEMPERE J, TABOADA ANTELO L. 2017. A dynamic economic equilibrium model for the economic assessment of the fishery stock-rebuilding policies Marine Policy 81:185-195. DOI: 10.1016/j.marpol.2017.03.029.
  • VILAS C, ALONSO AA, HERRERA J.R, GARCÍA-BLANCO A, GARCÍA M.R. 2017. A model for the biochemical degradation of inosine monophosphate in hake (Merluccius merluccius) Journal of Food Engineering 200:95-101 DOI: 10.1016/j.jfoodeng.2016.12.016
  • OTERO-MURAS I, YORDANOV P, STELLING J. 2017. Chemical Reaction Network Theory elucidates sources of multistability in interferon signaling PLoS Computational Biology 13(4) DOI: 10.1371/journal.pcbi.1005454.
  • HENRIQUES D, VILLAVERDE AF, ROCHA M, SAEZ-RODRÍGUEZ J, BANGA J.R. 2017. Data-driven reverse engineering of signaling pathways using ensembles of dynamic models PLoS Computational Biology 13(2) DOI: 10.1371/journal.pcbi.1005379.
  • BALSA-CANTO E, LÓPEZ-NÚÑEZ A, VÁZQUEZ C. 2017. Numerical methods for a nonlinear reaction-diffusion system modelling a batch culture of biofilm Applied Mathematical Modelling 18:164-179 DOI:  10.1016/j.apm.2016.08.020.
  • PENAS DR, GONZÁLEZ P, EGEA JA, DOALLO R, BANGA, JR. 2017. Parameter estimation in large-scale systems biology models: A parallel and self-adaptive cooperative strategy BMC Bioinformatics 18(1) DOI: 10.1186/s12859-016-1452-4.
  • ATTILA GÁBOR, ALEJANDRO F VILLAVERDE, JULIO R BANGA. 2017 Parameter identifiability analysis and visualization in large-scale kinetic models of Biosystems BMC Systems Biology 11 DOI: 10.1186/s12918-017-0428-y.
  • GARCÍA M.R, CABO M.L, HERRERA, JR, RAMILO-FERNÁNDEZ, G, ALONSO, A.A, BALSA-CANTO, E. 2017. Smart sensor to predict retail fresh fish quality under ice storage Journal of Food Engineering 8:87-97 DOI: 10.1016/j.jfoodeng.2016.11.006.
  • PENAS, D.R, HENRIQUES, D, GONZÁLEZ, P, DOALLO, R, SAEZ-RODRÍGUEZ, J, BANGA, JR. 2017. A parallel metaheuristic for large mixed-integer dynamic optimization problems, with applications in computational biology PLoS ONE 12(8) DOI: 10.1371/journal.pone.0182186.
  • OTERO-MURAS, I, BANGA, JR. 2017. Automated Design Framework for Synthetic Biology Exploiting Pareto Optimality ACS Synthetic Biology 6(7):1180-1193 DOI: 10.1021/acssynbio.6b00306.
  • GARCÍA, MR, ALONSO, A.A, BALSA-CANTO, E. 2017. A normalisation strategy to optimally design experiments in computational biology. Advances in Intelligent Systems and Computing 616:136-136 DOI: 10.1007/978-3-319-60816-7_16
  • TEIJEIRO D, PARDO XC, PENAS D.R, GONZÁLEZ P, BANGA JR, DOALLO, R. 2017. Evaluation of parallel differential evolution implementations on MapReduce and spark Lecture Notes in Computer Science 10104:397-408 DOI: 10.1007/978-3-319-58943-5_32.

2016

    • BALSA-CANTO E, ALONSO A.A, ARIAS-MÉNDEZ A, GARCÍA M.R, LÓPEZ-NÚÑEZ A, MOSQUERA-FERNÁNDEZ M, VÁZQUEZ C, VILAS C. 2016. Modeling and optimization techniques with applications in food processes, bio-processes and bio-systems. SEMA SIMAI Springer Series, 9 :187-216. DOI: 10.1007/978-3-319-32146-2_4.

 

    • ALONSO  AA,  SZEDERKÉNYI  G2016Uniqueness of feasible equilibria for mass action law (MAL) kinetic systems. Journal of Process Control , 48 pp. 41 – 71 .

 

    • BALSA-CANTO  E,  HENRIQUES  D,  GÁBOR  A,  BANGA  J.R.2016AMIGO2, a toolbox for dynamic modeling, optimization and control in systems biologyBioinformatics ,32 ( 21 ) pp. 3357 – 3359

 

    • OTERO-MURAS  I,  HENRIQUES  D,  BANGA  JR.2016SYNBADm: A tool for optimization-based automated design of synthetic gene circuitsBioinformatics , 32 ( 21 ) pp. 3360 – 3362 .

 

    • ANTELO LT, ORDÓÑEZ-DEL PAZO T, LOPES C, FRANCO-URÍA A, PÉREZ-MARTÍN RI, ALONSO AA . 2016. Pollutant levels in discarded fish species by Spanish trawlers operating in the Great Sole Bank and the Atlantic coast of the Iberian Peninsula. Marine Pollution Bulletin,  108: 303-310 . DOI: 10.1016/j.marpolbul.. 2016..04.040

 

    • MOSQUERA-FERNÁNDEZ M, SANCHEZ-VIZUETE P, BRIANDET R, CABO ML, BALSA-CANTO E . 2016. Quantitative image analysis to characterize the dynamics of Listeria monocytogenes biofilms. International Journal of Food Microbiology, 236: 130-137 . DOI: 10.1016/j.ijfoodmicro.. 2016..07.015

 

    • OTERO-MURAS I, BANGA JR . 2016. Exploring Design Principles of Gene Regulatory Networks via Pareto Optimality. IFAC-PapersOnLine, 49(7): 809-814 . DOI: 10.1016/j.ifacol.. 2016..07.289

 

    • PÁJARO M, ALONSO AA . 2016. On the applicability of deterministic approximations to model genetic circuits. IFAC-PapersOnLine 49(7):206-211  . DOI: 10.1016/j.ifacol.. 2016..07.251

 

    • VILLAVERDE AF, BECKER K, BANGA JR . 2016. PREMER: Parallel reverse engineering of biological networks with information theory Lecture Notes in Computer Science (including subseries. Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics),  9859( LNCS): 323-329 . DOI: 10.1007/978-3-319-45177-0_21

 

    • VILLAVERDE A F, BONGARD  S, MAUCH K, BALSA-CANTO E, BANGA J R. 2016. Metabolic engineering with multi-objective optimization of kinetic models.  Journal of biotechnology 222: 1-8 (2016). DOI: 10.1016/j.jbiotec.. 2016..01.005

 

  • VILLAVERDE, A.F., BARREIRO, A., PAPACHRISTODOULOU. 2016. Structural Identifiability Analysis via Extended Observability and Decomposition  IFAC-PapersOnLine 49(26):171-177 DOI: 10.1016/j.ifacol.2016.12.121

 

2015

    • ANTELO LT, HIJAS-LISTE GM DE, FRANCO-URÍA A, ALONSO AA, PÉREZ-MARTÍN RI. 2015. Optimisation of processing routes for a marine biorefinery. Journal of Cleaner Production, 104: 489-501.

 

    • HIJAS-LISTE GM DE, BALSA-CANTO E, EWALD J, BARTL M, LI P, BANGA JR, KALETA C. 2015. Optimal programs of pathway control: dissecting the influence of pathway topology and feedback inhibition on pathway regulation. BMC Bioinformatics, 16: 163.

 

    • LOPES C, ANTELO LT, FRANCO-URÍA A, ALONSO AA, PÉREZ-MARTÍN RI. 2015. Valorisation of fish by-products against waste management treatments: Comparison of environmental impacts. Waste Management, 46: 103-112.

 

    • GARCÍA MR, VILAS C, HERRERA JR, BERNÁRDEZ M, BALSA-CANTO E, ALONSO AA. 2015. Quality and shelf-life prediction for retail fresh hake (Merluccius merluccius). International Journal of Food Microbiology, 208: 65-74.

 

    • VILLAVERDE AF, HENRIQUES D, SMALLBONE K, BONGARD S, SCHMID J, CICIN-SAIN D, CROMBACH A, SAEZ-RODRIGUEZ J, MAUCH K, BALSA-CANTO E, MENDES P, JAEGER J AND BANGA JR. 2015. BioPreDyn-bench: benchmark problems for kinetic modelling in systems biology. BMC Systems Biology, 9(1): 8.

 

    • VILLAVERDE AF, BONGARD S, MAUCH K, MÜLLER D, BALSA-CANTO E, SCHMID J, BANGA JR. 2015. A consensus approach for estimating the predictive accuracy of dynamic models in biology. Computer Methods and Programs in Biomedicine, 119: 17-28.

 

    • FOLCH-FORTUNY A, VILLAVERDE AF, FERRER A, BANGA JR. 2015. Enabling network inference methods to handle missing data and outliers. BMC Bioinformatics, 16: 283.

 

    • GABOR A, BANGA JR. 2015. Robust and efficient parameter estimation in dynamic models of biological systems. BMC Systems Biology, 9: 74

 

    • GABOR A, HANGOS KM, BANGA JR, SZEDERKENYI G. 2015. Reaction Network Realizations of Rational Biochemical Systems and Their Structural Properties. Journal of Mathematical Chemistry, 53: 1657-1686.

 

    • PÁJARO M, ALONSO AA, VÁZQUEZ C. 2015. Shaping protein distributions in stochastic self-regulated gene expression networks. Physical Review E, 92: 032712.

 

    • PENAS DR, BANGA JR, GONZÁLEZ P, DOALLO R. 2015. Enhanced parallel Differential Evolution algorithm for problems in computational systems biology. Applied Soft Computing, 33: 86-99.

 

    • HENRIQUES D, ROCHA M, SAEZ-RODRIGUEZ J, BANGA JR. 2015. Reverse engineering of logic-based differential equation models using a mixed-integer dynamic optimization approach. Bioinformatics, 31(18): 2999-3007.

 

  • PENAS DR, GONZALEZ P, EGEA JA, BANGA JR, DOALLO R. 2015. Parallel Metaheuristics in Computational Biology: An Asynchronous Cooperative Enhanced Scatter Search Method. Procedia Computer Science, 51: 630-639

 

2014

    • ALONSO A, MOLINA I, THEODOROPOULOS K. 2014. Modeling bacteria population growth from stochastic single-cell dynamics.Applied and Environmental Microbiology, 80 (17), 5241-5253

 

    • ARIAS-MENDEZ A, VILAS C, ALONSO AA, BALSA-CANTO E. 2014. Time temperature integrators as predictive temperature sensors. Food Control, 44: 258-266.

 

    • DE HIJAS-LISTE GM, KLIPP E, BALSA-CANTO E, BANGA JR. 2014. Global dynamic optimization approach to predict activation in metabolic pathways. BMC Systems Biology,8:1.

 

    • EGEA JA, HENRIQUES D, COKELAER T, VILLAVERDE AF, MACNAMARA A, DANCIU D, BANGA JR, SAEZ-RODRIGUEZ J. 2014. MEIGO: an open-source software suite based on metaheuristics for global optimization in systems biology and bioinformatics. BMC Bioinformatics,15: 136.

 

    • HEERMANN R, ZIGANN K, GAYER S, RODRIGUEZ-FERNANDEZ M, BANGA JR, KREMLING A, JUNG K. 2014. Dynamics of an Interactive Network Composed of a Bacterial Two-Component System, a Transporter and K+ as Mediator. PLoS ONE, 9(2):e89671.

 

    • LÓPEZ-CAAMAL F, OYARZÚN DA, MIDDLETON RH, GARCÍA MR. 2014. Spatial quantification of cytosolic Ca2+ accumulation in nonexcitable cells: Ananalytical study. IEEE/ACM Transactions on Computational Biolgy and Bioinformatics, 11 (3): 592-603.

 

    • MOSQUERA-FERNÁNDEZ M, RODRÍGUEZ-LÓPEZ P, CABO ML, BALSA-CANTO E. 2014. Numerical spatio-temporal characterization of Listeria mono cytogenes biofilms.International Journal of Food Microbiology, 182, 26-36.

 

    • ORDÓÑEZ-DEL PAZO T, ANTELO LT, FRANCO-URÍA A, PÉREZ-MARTÍN RI, SOTELO CG, ALONSO AA. 2014. Fish discards management in selected Spanish and Portuguese métiers: Identification and potential valorisation. Trends in Food Science and Technology, 36 (1), 29-43.

 

    • OTERO MURAS I, BANGA JR. 2014. Multicriteria global optimization for biocircuit design. BMC Systems Biology,8:113.

 

    • OTERO MURAS I, YORDANOV P, STELLING J. 2014. A method for inverse bifurcation of biochemical switches: inferring parameters from dose response curves. BMC Systems Biology, 8:114.

 

    • RAIMÚNDEZ C, VILLAVERDE AF, BARREIRO A. 2014. Adaptive tracking in mobile robots with input-output linearization. Journal of Dynamic Systems, easurement, and Control, Transactions of the ASME,136: 054503-1.

 

    • VILLAVERDE AF, ROSS J, MORÁN F, BANGA JR. 2014. MIDER: network inference with Mutual Information Distance and Entropy Reduction. PLOS ONE, 9(5): e96732.

 

    • VILLAVERDE AF, BANGA JR. 2014. Reverse engineering and identification in systems biology: strategies, perspectives, and challenges.

 

  • Journal of the Royal Society Interface, 11: 20130505.

 

2013

    •  ALONSO AA, ARIAS-MÉNDEZ A, BALSA-CANTO E, GARCÍA MR, MOLINA JI, VILAS C, VILLAFÍN M. 2013. Real time optimization for quality control of batch thermal sterilization of  prepackaged foods. Food Control, 32 (2): 392-403.

 

    • ARIAS-MENDEZ A, WARNING A, DATTA AK, BALSA-CANTO E. 2013. Quality and safety driven optimal operation of deep-fat frying of potato chips. Journal of Food Engineering, 119 (1): 125–134.

 

    • BECKER K, BALSA-CANTO E, CICIN-SAIN D, HOERMANN A, JANSSENS H, BANGA JR, JAEGER J. 2013. Reverse-Engineering Post-Transcriptional Regulation of Gap Genes in Drosophila melanogaster. PLoS Computational Biology, 9 (10): e1003281.

 

    • EGEA JA, HENRIQUES D, COKELAER T, VILLAVERDE AF, BANGA JR, SAEZ-RODRIGUEZ J. 2013. MEIGO: an open-source software suite based on metaheuristics for global optimization  in systems biology and bioinformatics. ArXiv, 1311.5735.

 

    • HANNEMANN-TAMÁS R, GÁBOR A, SZEDERKÉNYI G, HANGOS KM. 2013. Model complexity reduction of chemical reaction networks using mixed-integer quadratic programming. Computers and Mathematics with Applications, 65 (10): 1575-1595.

 

    • LOPES C, ANTELO LT, FRANCO-URÍA A, BOTANA C, ALONSO AA. 2013. Sustainability of port activities within the framework of the fisheries sector: Port of Vigo (NW Spain). Ecological  Indicators, 30: 45-51.

 

    • RIVAS D, VILAS C, VARAS F, ALONSO AA. 2013. Derivation of postharvest fruit behavior reduced order models for on-line monitoring and control of quality parameters during refrigeration. Journal of Food Process Engineering, 36 (4): 480-491.

 

    • ROCHA JM, GUTIÉRREZ MJ, ANTELO LT. 2013. Selectivity, Pulse Fishing and Endogenous Lifespan in Beverton-Holt Models. Environmental and Resource Economics, 54 (1) 139-154, doi: 10.1007/s10640-012-9.

 

    • RODRIGUEZ-FERNANDEZ M, REHBERG M, KREMLING A, BANGA JR. 2013. Simultaneous model discrimination and parameter estimation in dynamic models of cellular systems. BMC  Systems Biology, 7: 76.

 

    • TUZA ZA, SZEDERKENYI G, HANGOS KM, ALONSO  AA, BANGA JR. 2013. Computing all Sparse Kinetic Structures for a Lorenz System Using Optimization. Int. Journal of Bifurcation and Chaos, 23 (8): 1350141.

 

    • VILLAVERDE AF ROSS J, BANGA JR. 2013. Reverse engineering cellular networks with information theoretic methods. Cells, 2 (2): 306–329.

 

    • BALSA-CANTO E, BANGA J.R. 2013. Optimal dynamic experiments. En: Encyclopedia of Systems Biology. (W. Dubitzky, O. Wolkenhauer, K.-H. Cho, H. Yokota, eds.), pp. 1569-1572. Springer Science+Business Media.

 

    • DE HIJAS-LISTE GM, BALSA-CANTO E, BANGA JR, KALETA C. 2013. Optimal regulatory programs for the control of metabolic pathways: The case of feedback inhibition. En: 21st  Mediterranean Conference on Control and Automation, MED 2013- Conference Proceedings, pp. 237 – 242, (http:// dx.doi.org/10.1109/MED.2013.6608728).

 

    • BALSA-CANTO E, ALONSO AA, ANTELO LT, ARIAS-MENDEZ A, LÓPEZ-QUIROGA E, RIVAS D, VILAS C. 2013. Model identification and on-line optimal control of food processes. En:  Computational Methods for Coupled problems in Science and Engineering V. (S. Idelsohn, M. Papadrakakis and B. Schrefler, eds.), pp. 1395-1406, ISBN: 978-84-941407-6-1.

 

    • GÁBOR A, HANGOS KM, SZEDERKÉNYI G, BANGA JR. 2013. On the Verification and Correction of Large-Scale Kinetic Models in Systems Biology. En: Computational Methods in Systems  biology. Lecture Notes in Computer Science, 8130: 206-219.

 

    • GARCÍA M-SG, BALSA-CANTO E, ALONSO AA, BANGA JR. 2013. Dynamic Optimization of Nonlinear Bioreactors. En: Taming Heterogeneity and Complexity of Embedded Control, 307-327 (http://dx.doi.org/10.1002/9780470612217.ch18).

 

  • MACNAMARA A, HENRIQUES D, SAEZ-RODRIGUEZ J. 2013. Modeling Signaling Networks with Different Formalisms: A Preview. En: In Silico Systems Biology, pp. 89-105. Humana Press.

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