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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.
doi.org/10.3390/app10113936
[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.
[23] [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]
[22] [PDF] R.
Lahoz-Beltra. 2012. Cellular computing: towards an artificial cell.
Journal of Information Theories & Applications 19(4): 313-318.
[21] [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]
[20] [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.
[19] [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.
[18] [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]
[17] [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.
[16] [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.
[15] [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-
[14c] [PDF] J. M. Gabriel y Galan, C. Prada, C. Martinez Calvo, R. Lahoz-
[13c] [PDF] A. Sanchez-
[12c] [PDF] R. del Moral, J. Navarro, R. Lahoz-
[11c] [PDF] J. Navarro, R. del Moral, M.F. Alonso, P. Loste, J. Garcia-
[10c] [PDF] J. Gil, M. Gimeno, J. Laborda, J. Nuviala, R. Lahoz-
[9c] [PDF] J.M. Gabriel y Galan, G. Migliario, R. Lahoz-
[8c] [PDF] J.M. Gabriel y Galan, C. Prada, C. H. Rollen, R. Lahoz-
[7c] [PDF] M.A. Caja, R. Marfil, D. Garcia, E. Remacha, S. Morad, H. Mansurbeg, A. Amorosi, C. Martinez-
[6c] [PDF] J. López Sánchez, A. Murciano, R. Lahoz-
[5c] [PDF] C. Fernández-
[4c] [PDF] R. Lahoz-
[3c] [PDF] R. Lahoz-
[2c] [PDF] R. Lahoz, F. Reyes, G. Gómez Alarcón, L. Cribeiro, R. Lahoz-
[1c] [PDF] R. Lahoz, F. Reyes, M. Junquera, R. Lahoz-
Books (in spanish)
[10b] [HTLM] R. Lahoz-
[9b] [HTLM] R. Lahoz-
[8b] [HTML] R. Lahoz-
[7b] [HTML] R. Lahoz-
[6b] [HTML] R. Lahoz-
[5b] [HTML] R. Lahoz-
[4b] [HTML] C. Martínez-
[3b] [HTML] R. Lahoz-
[2b] [HTML] R. Lahoz-
[1b] [HTML] R. Lahoz-