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Modeling and simulation of biological systems

  •       supplementary material

[38] [PDF] A. Gargantilla Becerra, R. Lahoz-Beltra. 2020. A Microbial Screening in Silico Method for the Fitness Step Evaluation in Evolutionary Algorithms. Applied Sciences 2020, 10(11), 3936.

[37] [PDF] A. Gomez-Mompean, R. Lahoz-Beltra. 2020. An Evolutionary Computing Model for the Study of Within-Host Evolution. Computation 8, 5. doi: 10.3390/computation8010005

[36] [PDF] M. Maloy, F. Maloy, R. Lahoz-Beltra, J.C. Nuño, A. Bru. 2019.
An extended Moran process that captures the struggle for fitness. Mathematical Biosciences 308: 81-104.

[35] [PDF] J.
Navarro, M. Fernández Rosell, A. Castellanos, R. del Moral, R. Lahoz-Beltra, P.C. Marijuan. 2019. Plausibility of a neural network classifier-based neuroprosthesis for depression detection via laughter records. Frontiers in Neuroscience 13:267  DOI=10.3389/fnins.2019.00267  

[34] [PDF] R. Lahoz-Beltra. 2018.
The 'crisis of noosphere' as a limiting factor to achieve the point of technological singularity. Interdisciplinary Description of Complex Systems16(1): 92-109.

[33] [PDF].
A. Castellanos, R. Lahoz–Beltra. 2018. Optimization of gene expression with a genetic algorithm. International Journal Information Models and Analyses 7(2): 103-113.

[32] [PDF]
R. Salas Machado, A. Castellanos, R. Lahoz-Beltra. 2017. Eye evolution simulation with a genetic algorithm based on the hypothesis of Nilsson and Pelger. International Journal Information Theories and Applications 24(3): 221-228.

[31] [PDF]
S. Guil López, P. Cuesta Alvaro, S. Cano Alsua, R. Salas Machado, J. Castellanos, R. Lahoz-Beltra. 2016. Towards a Dawkins' genetic algorithm: Transforming an interactive evolutionary algorithm into a genetic algorithm. International Journal of Information Technologies & Knowledge 10(3): 234-249.

[30] [PDF]
R. Salas Machado, J. Castellanos, R. Lahoz-Beltra. 2016. Evolutionary synthesis of QCA circuits: A critique of evolutionary search methods based on the Hamming oracle. International Journal Information Technologies & Knowledge 10(3): 203-215.

[29] [PDF] R.
Lahoz-Beltra. 2016. Quantum Genetic Algorithms for Computer Scientists. Computers 5, 24. doi: 10.3390/computers5040024

[28] [PDF] M. Alfonseca, A. Ortega, M. de la Cruz, S. R. Hameroff, R. Lahoz-Beltra. 2015. A model of quantum-von Neumann hybrid cellular automata: principles and simulation of quantum coherent superposition and decoherence in cytoskeletal microtubules. Quantum Information & Computation 15 (1/2): 22-36.

[27] [PDF] D. Thai Dam,
R. Lahoz-Beltra. 2014. MICRORAM: A simulation model of a colony of bacteria evolving inside an artificial world. Journal of Information Theories & Applications 21(4): 328-338.

[26] [PDF] R. Lahoz-Beltra, J. Navarro, P.C. Marijuan. 2014. Bacterial computing: a form of natural computing and its applications. Frontiers in Microbiology 5. Article 101.  

[25] [PDF] C. Recio Rincon, P. Cordero, J. Castellanos, R. Lahoz-Beltra. 2014. A new method for the binary encoding and hardware implementation of metabolic pathways. International Journal of Information Theories & Applications 21(1): 21-30.

[24] [PDF] P. Cordero, R. Lahoz-Beltra, J. Castellanos. 2013. Prion crystallization model and its application to recognition pattern. Internacional Journal of Information Theories & Applications 20(3): 210-217.

] [PDF] C. Perales Graván, J. de Vicente Buendia, J. Castellanos, R. Lahoz-Beltra. 2013. Modeling, Simulation and Application of Bacterial Transduction in Genetic Algorithms. Internacional Journal of Information Technologies & Knowledge 7(1): 11-22. [supplementary material]

] [PDF] R. Lahoz-Beltra. 2012. Cellular computing: towards an artificial cell. Journal of Information Theories & Applications 19(4): 313-318.

] [PDF] R. Lahoz-Beltra, C. Perales Graván. 2010. A survey of nonparametric tests for the statistical analysis of evolutionary computation experiments. Internacional Journal of Information Theories and Applications 17(1): 49-61. [supplementary material]

] [PDF] J.C. Nuño, J. de Vicente, J. Olarrea, P. López, R. Lahoz-Beltra. 2010. Evolutionary daisyworld models: A new approach to studying complex adaptive systems. Ecological Informatics 5: 231-240.

] [PDF] R. Lahoz-Beltra, G. Ochoa, U. Aickelin. 2009. Cheating for Problem Solving: A genetic algorithm with social interactions.  Genetic and Evolutionary Computation Conference (GECCO-09), ACM: 811-817.

] [PDF] N. Selem Mojica, J. Navarro, P.C. Marijuan, R. Lahoz-Beltra. 2009. Cellular “bauplans”: Evolving unicellular forms by means of Julia sets and Pickover biomorphs. BioSystems 98: 19-30. [supplementary material]

] [PDF] C. Perales Graván, R. Lahoz-Beltra. 2008.  An AM radio receiver designed with a genetic algorithm based on a bacterial conjugation operator. IEEE Transactions on Evolutionary Computation 12(2): 129-142.

] [PDF] C. Perales Graván, R. Lahoz-Beltra. 2004. Evolving morphogenetic fields in the zebra skin pattern based on Turing morphogen hypothesis.  International Journal of Applied Mathematics and Computer Science 14(3): 351-361.

] [PDF] V. Di Paola, P.C. Marijuán, R. Lahoz-Beltra. 2004.  Learning and evolution in bacterial taxis: an operational amplifier circuit modeling the dynamics of the prokaryotic 'two component system' protein network. BioSystems  74:  29-49.

[14]  [PDF]
R. Lahoz-Beltra. 2001. Evolving hardware as model of enzyme evolution. BioSystems  61: 15-25.

[13]  [PDF]
R. Lahoz-Beltra. 1998. Molecular automata modeling in structural biology. Advances in Structural Biology 5: 85-101.

[12]  [PDF]
R. Lahoz-Beltra. 1997. Molecular automata assembly: principles and simulation of bacterium membrane construction.
BioSystems  44: 209-229.

[11] [PDF] R. Lahoz-Beltra, S. Hameroff, J.E. Dayhoff. 1996. Synaptic weights based on molecular mechanisms in Aplysia neuron synapses. Neurocomputing 11: 179-202.

[10] [PDF] R. Lahoz-Beltra, S.Hameroff, J.E. Dayhoff. 1995. From biological to artificial neural networks: developing artificial neural networks with biological algorithms, in: Le neuromimétisme: Epistémologie, neurobiologie, informatique (Eds. H. Paugam-Moisiy, J.P. Royet, D. Abdelkader Zighed).:  187-196. Editions Hermès   (ISBN 2-86601-487-1).

[9]  [PDF] J.E. Dayhoff, S. Hameroff, R. Lahoz-Beltra, C.E. Swenberg. 1994.  Cytoskeletal involvement in neural learning: a review.  European Biophysics Journal  23: 79-93.

[8] [PDF]
R. Lahoz-Beltra, S. Hameroff, J.E. Dayhoff. 1993. Cytoskeletal logic: a model for molecular computation via Boolean operations in microtubules and microtubule-associated proteins. BioSystems 29: 1-23.

[7]  [PDF]
S. Hameroff, J.E. Dayhoff, R. Lahoz-Beltra, S. Rasmussen, E.M. Insinna, D. Koruga. 1993. Chapter 10. Nanoneurology and the cytoskeleton: Quantum signaling and protein conformational dynamics as cognitive substrate, in: Rethinking Neural Networks: Quantum Fields and Biological Data (Eds. K.H. Pribram y Sir J. Eccles):  317-376. Lawrence Erlbaum Associates, Hillsdale, New Jersey (EE UU).    

[6] [PDF]
J.E. Dayhoff, S. Hameroff, C.E. Swenberg, R. Lahoz-Beltra. 1993. Chapter 12. The neuronal cytoskeleton: A complex system that subserves neural learning,  in: Rethinking Neural Networks: Quantum Fields and Biological Data (Eds. K.H. Pribram y Sir J. Eccles):  389-442.  Lawrence Erlbaum Associates,  Hillsdale, New Jersey (EE UU).    

[5] [PDF]
J.E. Dayhoff, S. Hameroff, C. Swenberg, R. Lahoz-Beltra. 1992. Biological plausibility of back-error propagation in microtubules. Technical Report of Institute for Systems Research, University of Maryland, College Park, MD 10742. SRC TR 92-17: 1-79.

[4] [PDF]
S. Hameroff, J.E. Dayhoff, R. Lahoz-Beltra, A. Samsonovich, S. Rasmussen. 1992. Conformational automata in the cytoskeleton: models for molecular computation. IEEE Computer (Special Issue on Molecular Computing) 25(11): 30-39.    

[3] [PDF]
H. Hotani, R. Lahoz-Beltra, B. Combs, S. Hameroff, S. Rasmussen. 1992. Microtubule dynamics, liposomes and artificial cells: in vitro observation and cellular automata simulation of microtubule assemby/disassembly and membrane morphogenesis. Nanobiology  1: 61-74.

[2] [PDF]
J. Alonso, R. Lahoz-Beltra, A. Bailador, M. Levy, J.R. Díaz-Ruiz. 1992. An expert system to classify plant viruses. Binary Computing in Microbiology 4: 195-199.

[1] [PDF]  
(My first paper) R. Lahoz-Beltra. 1986. What is Life? Life as a Bioinformation System. Fifth ISSOL meeting and Eight International Conference on the Origins of Life. Berkeley, CA (EE UU). Origins of Life 16 (3/4): 324-325.  

Collaborations in statistical data analysis and numerical models in life sciences

[15c] [PDF] J. Navarro, R. del Moral, P. Cuesta Alvaro, R. Lahoz-Beltra, P. C. Marijuan. 2016. The entropy of laughter: Discriminative power of laughter's entropy in the diagnosis of depression. Entropy 18(1), 36: 1-12.

[14c] [PDF] J. M. Gabriel y Galan, C. Prada, C. Martinez Calvo, R. Lahoz-Beltra. 2015. A Gompertz regression model for fern spores germination. Anales del Jardin Botanico de Madrid 72(1): 1-8.

[13c] [PDF] A. Sanchez-Alberca, R. Lahoz-Beltra, J. Castellanos. 2014. Towards a semantic catalog of similarity measures. Internation Journal of Information Content and Processing 1(2): 124-135.

[12c] [PDF] R. del Moral, J. Navarro, R. Lahoz-Beltra, M.G. Bedia, F. J. Serón, P. C. Marijuan. 2014. Cognitive and emotional contents of laughter: Framing a new neurocomputational approach. International Journal of Synthetic Emotions, 5(2): 33-55.

[11c] [PDF]  J. Navarro, R. del Moral, M.F. Alonso, P. Loste, J. Garcia-Campayo, R. Lahoz-Beltra, P.C. Marijuan. 2014. Validation of laughter for diagnosis and evaluation of depression. Journal of Affective Disorders 160: 43-49.

[10c]  [PDF] J. Gil, M. Gimeno, J. Laborda, J. Nuviala, R. Lahoz-Beltra. 2013. Birkhoff’s aesthetic ratio as a morphometric tool in the analysis of anatomical development of biological tree-like structures: Zoomorphology 132(1): 67-80.

[9c]  [PDF]  J.M. Gabriel y Galan, G. Migliario, R. Lahoz-Beltra. 2011. Effect of temperature and dark pretreatment on the germination of three species of Jamesonia (Pteridaceae, Polypodiopsida). Plant Species Biology 26: 254-258.

[8c]  [PDF] J.M. Gabriel y Galan, C. Prada, C. H. Rollen, R. Lahoz-Beltra, C. Martinez-Calvo. 2011. A biometrical study of stomata in Blechnum species (Blechnaceae) with some taxonomic and ecological implications for the ferns. Rev. Biol. Trop. (Int. J. Trop. Biol.) 59(1): 403-415.

[7c]  [PDF]  M.A. Caja, R. Marfil, D. Garcia, E. Remacha, S. Morad, H. Mansurbeg, A. Amorosi, C. Martinez-Calvo, R. Lahoz-Beltra. 2010. Provenance of siliciclastic and Irbid turbiditic arenitas of the Eocene Hecho Group, the Spanish Pyrenees: implications for tectonic evolution of a foreland basin. Basin Research 22: 157-180.

[6c]  [PDF] J. López Sánchez, A. Murciano, R. Lahoz-Beltra, J. Zamora, N.I. Giménez-Abián, J.F. López-Sáez, C. De La Torre, J.L. Cánovas. 2002. Modelling complex populations formed by proliferating, quiescent and quasi-quiescent cells: application to plant root meristems. Journal of Theoretical Biology 215: 201-213.

[5c] [PDF] C. Fernández-Montraveta, R. Lahoz-Beltra, J. Ortega. 1991.  Spatial distribution of Lycosa tarentula fasciiventris in a population from central Spain. The Journal of Arachnology  19: 73-79.   

[4c] [PDF]  R. Lahoz-Beltra, A. Pérez de Vargas, J. López Sánchez,  J.R. Díaz Ruiz. 1990.  New approach of spatial point pattern as a tool for distinguishing plant viruses.  Biometrie Praximetrie  30: 1-13.

[3c] [PDF]  R. Lahoz-Beltra, J. Ortega. 1989. Compass orientation of Lycosa tarentula fasciiventris nests in central Spain. Bulletin British Arachnological Society 8: 63-64.

[2c]  [PDF] R. Lahoz, F. Reyes, G. Gómez Alarcón, L. Cribeiro, R. Lahoz-Beltra. 1986. Behaviour of the cell walls of Aspergillus niger during the autolytic phase of growth. FEMS Microbiology Letters 36: 265-268.

[1c]  [PDF]  R. Lahoz, F. Reyes, M. Junquera, R. Lahoz-Beltra. 1986. Kinetics of the autolytic phase of growth in the fungus Aspergillus niger. Micopathologia  94: 75-78.

Books (in spanish)

[10b] [HTLM] R. Lahoz-Beltra. 2019. En las entrañas del big data. Una aproximación a la estadística. EMSE Publishing. Colección "Grandes Ideas de las Matemáticas" (ISBN 978-84-17811-471-1), pp. 1-144.

[9b] [HTLM]  R. Lahoz-Beltra. 2019. Hiperespacios. El mundo en cuatro o más dimensiones. EMSE Publishing. Colección "Grandes Ideas de las Matemáticas" (ISBN 978-84-17811-44-0), pp. 1-139.

[8b]  [HTML] R. Lahoz-Beltra. 2015.  
Turing. La computación: pensando en máquinas que piensan. National Geographic 28: 1-136.

[7b]  [HTML] R. Lahoz-Beltra. 2012. Turing. La computación: pensando en máquinas que piensan. RBA. Colección “Grandes Ideas de la Ciencia” (ISBN 978-84-473-7638-4), pp 1-144. Eds. Española, italiana, francesa.

[6b]  [HTML] R. Lahoz-Beltra. 2011. Las matemáticas de la vida. Modelos numéricos para la biología y la ecología. RBA. Colección “El Mundo es Matemático” (ISBN 978-84-473-69 70-6),  pp 1-159. Eds. Española, italiana, francesa, portuguesa y polaca.

[5b]  [HTML] R. Lahoz-Beltra. 2008  ¿Juega Darwin a los Dados? Nivola (ISBN 84-96566-42-0), pp 1-160.

[4b]  [HTML] C. Martínez-Calvo, E. Fernández Bermejo, M.T. Gónzalez Manteiga, R. Lahoz-Beltra , C. Perales Graván. 2005. Matemáticas Básicas para Biólogos, CD-ROM. Innovación Educativa,  Editorial Complutense (ISBN 84-7491-786-7), Madrid.

[3b]  [HTML] R. Lahoz-Beltra. 2005 (1 Ed.), 2009 (2 Ed.). Turing. Del Primer Ordenador a la Inteligencia Artificial. Nivola (ISBN 84-96566-01-3), pp 1-142.

[2b] [HTML] R. Lahoz-Beltra. 2004. Bioinformática. Simulación, Vida Artificial e Inteligencia Artificial. Editorial Díaz de Santos (ISBN 84-7978-645-0), pp 1-610.

[1b] [HTML]  R. Lahoz-Beltra, J. Ortega, C. Fernández-Montraveta. 1995. Métodos Estadísticos en Biología del Comportamiento. Editorial Complutense (ISBN  84-7491-512-0), pp 1-232.

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