Papers by Alfonso Rodríguez-Patón
Briefings in Bioinformatics
A biological network is complex. A group of critical nodes determines the quality and state of su... more A biological network is complex. A group of critical nodes determines the quality and state of such a network. Increasing studies have shown that diseases and biological networks are closely and mutually related and that certain diseases are often caused by errors occurring in certain nodes in biological networks. Thus, studying biological networks and identifying critical nodes can help determine the key targets in treating diseases. The problem is how to find the critical nodes in a network efficiently and with low cost. Existing experimental methods in identifying critical nodes generally require much time, manpower and money. Accordingly, many scientists are attempting to solve this problem by researching efficient and low-cost computing methods. To facilitate calculations, biological networks are often modeled as several common networks. In this review, we classify biological networks according to the network types used by several kinds of common computational methods and intro...
BMC Medical Genomics
Background: Accurately predicting pathogenic human genes has been challenging in recent research.... more Background: Accurately predicting pathogenic human genes has been challenging in recent research. Considering extensive gene-disease data verified by biological experiments, we can apply computational methods to perform accurate predictions with reduced time and expenses. Methods: We propose a probability-based collaborative filtering model (PCFM) to predict pathogenic human genes. Several kinds of data sets, containing data of humans and data of other nonhuman species, are integrated in our model. Firstly, on the basis of a typical latent factorization model, we propose model I with an average heterogeneous regularization. Secondly, we develop modified model II with personal heterogeneous regularization to enhance the accuracy of aforementioned models. In this model, vector space similarity or Pearson correlation coefficient metrics and data on related species are also used. Results: We compared the results of PCFM with the results of four state-of-arts approaches. The results show that PCFM performs better than other advanced approaches. Conclusions: PCFM model can be leveraged for predictions of disease genes, especially for new human genes or diseases with no known relationships.
Ecology and Evolution
Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and ... more Computational ecology is an emerging interdisciplinary discipline founded mainly on modeling and simulation methods for studying ecological systems. Among the existing modeling formalisms, the individual-based modeling is particularly well suited for capturing the complex temporal and spatial dynamics as well as the nonlinearities arising in ecosystems, communities or populations due to individual variability. In addition, being a bottom up approach, it is useful for providing new insights on the local mechanisms which are generating some observed global dynamics. Of course no conclusions about model results could be taken seriously if they are based on a single model execution and they are not analyzed carefully. Therefore, a sound methodology should always be used for underpinning the interpretation of model results. The sensitivity analysis is a methodology for quantitatively assessing the effect of input uncertainty in the simulation output which should be incorporated compulsorily to every work based on in silico experimental setup. In this paper we present R/Repast a GNU R package for running and analyzing Repast Simphony models accompanied by two worked examples on how to perform global sensitivity analysis and how to interpret the results.
Fundamenta Informaticae, 2000
ABSTRACT
Self-consciousness implies not only self or group recognition, but also real knowledge of one's o... more Self-consciousness implies not only self or group recognition, but also real knowledge of one's own identity. Self-consciousness is only possible if an individual is intelligent enough to formulate an abstract self-representation. Moreover, it necessarily entails the capability of referencing and using this selfrepresentation in connection with other cognitive features, such as inference, and the anticipation of the consequences of both one's own and other individuals' acts. In this paper, a cognitive architecture for selfconsciousness is proposed. This cognitive architecture includes several modules: abstraction, self-representation, other individuals' representation, decision and action modules. It includes a learning process of self-representation by direct (self-experience based) and observational learning (based on the observation of other individuals). For model implementation a new approach is taken using Modular Artificial Neural Networks (MANN). For model testing, a virtual environment has been implemented. This virtual environment can be described as a holonic system or holarchy, meaning that it is composed of autonomous entities that behave both as a whole and as part of a greater whole. The system is composed of a certain number of holons interacting. These holons are equipped with cognitive features, such as sensory perception, and a simplified model of personality and self-representation. We explain holons' cognitive architecture that enables dynamic selfrepresentation. We analyse the effect of holon interaction, focusing on the evolution of the holon's abstract self-representation. Finally, the results are explained and analysed and conclusions drawn.
Conclusiones y futuras investigaciones 7 Conclusiones 8 L?neas futuras de investigaci?n Bibliogra... more Conclusiones y futuras investigaciones 7 Conclusiones 8 L?neas futuras de investigaci?n Bibliograf?a ?ndice de Figuras 2.1 Estructura de las bases purinas A y G y pirimidinas T, C y U.. .. .. .. .. .. 2.2 Estructura de laD -ribosa y de laD -2-desoxirribosa.. .. .. .. .. .. .. 2.3 Estructura de una hebra simple o monocatenaria de ADN cuya secuencia se lee en sentido 5 0 3 0 y es GTAC.
Negative and positive transcriptional feedback loops are present in natural and synthetic genetic... more Negative and positive transcriptional feedback loops are present in natural and synthetic genetic oscillators. A single gene with negative transcriptional feedback needs a time delay and sufficiently strong nonlinearity in the transmission of the feedback signal in order to produce biochemical rhythms. A single gene with only positive transcriptional feedback does not produce oscillations. Here, we demonstrate that this single-gene network in conjunction with a simple negative interaction can also easily produce rhythms. We examine a model comprised of two well-differentiated parts. The first is a positive feedback created by a protein that binds to the promoter of its own gene and activates the transcription. The second is a negative interaction in which a repressor molecule prevents this protein from binding to its promoter. A stochastic study shows that the system is robust to noise. A deterministic study identifies that the dynamics of the oscillator are mainly driven by two types of biomolecules: the protein, and the complex formed by the repressor and this protein. The main conclusion of this paper is that a simple and usual negative interaction, such as degradation, sequestration or inhibition, acting on the positive transcriptional feedback of a single gene is a sufficient condition to produce reliable oscillations. One gene is enough and the positive transcriptional feedback signal does not need to activate a second repressor gene. This means that at the genetic level an explicit negative feedback loop is not necessary. The model needs neither cooperative binding reactions nor the formation of protein multimers. Therefore, our findings could help to clarify the design principles of cellular clocks and constitute a new efficient tool for engineering synthetic genetic oscillators.
Spiking neural P systems are computing devices recently introduced as a bridge between spiking ne... more Spiking neural P systems are computing devices recently introduced as a bridge between spiking neural nets and membrane computing. Thanks to the rapid research in this field there exists already a series of both theoretical and application studies. In this paper we focus on normal forms of these systems while preserving their computational power. We study combinations of existing normal forms, showing that certain groups of them can be combined without loss of computational power, thus answering partially open problems stated in . We also extend some of the already known normal forms for spiking neural P systems considering determinism and strong acceptance condition. Normal forms can speed-up development and simplify future proofs in this area.
Fundamenta Informaticae
Department of Artificial Intelligence, Faculty of Computer Science, Polytechnical University of M... more Department of Artificial Intelligence, Faculty of Computer Science, Polytechnical University of Madrid Campus de Montegancedo, Boadilla del Monte 28660, Madrid, Spain E-mail: ¡£¢¥¤¦¡£ §© ¦ ¥ ¤£!" $ #&% ... Andrés Silva Department of Languages and Software Engineering, ...
Advances in Intelligent Systems and Computing, 2015
ABSTRACT Bacterial conjugation is a cell-cell communication by which neighbor cells transmit circ... more ABSTRACT Bacterial conjugation is a cell-cell communication by which neighbor cells transmit circular DNA strands called plasmids. The transmission of these plasmids has been traditionally modeled using differential equations. Recently agent-based systems with spatial resolution have emerged as a promising tool that we use in this work to assess three different schemes for modeling the bacterial conjugation. The three schemes differ basically in which point of cell cycle the conjugation is most prone to happen. One alternative is to allow a conjugative event occurs as soon a suitable recipient is found, the second alternative is to make conjugation equally like to happen throughout the cell cycle and finally, the third one technique to assume that conjugation is more likely to occur in a specific point late in the cell cycle.
Lecture Notes in Computer Science, 2015
ABSTRACT BactoSim is an agent-based platform for simulating the conjugation in spatially structur... more ABSTRACT BactoSim is an agent-based platform for simulating the conjugation in spatially structured bacterial populations, which are the conditions typically found on naturally occurring colonies such as biofilms or in agar-based laboratory cultures. The model provides a set of key indicators which can be visualized in real time as the simulation evolves and saved as for further analysis.
Lecture Notes in Computer Science, 2009
... In our opinion, the use of proteins, antisense RNAs, microR-NAs and small interfering RNAs in... more ... In our opinion, the use of proteins, antisense RNAs, microR-NAs and small interfering RNAs in combination with RNA molecules with catalityc functions, such as ribozymes or riboswitches, may simplify and enhance the new synthetic biological devices. Acknowledgments. ...
Lecture Notes in Computer Science, 2003
This paper describes the design of a linear time DNA algorithm for the Hamiltonian Path Problem (... more This paper describes the design of a linear time DNA algorithm for the Hamiltonian Path Problem (HPP) suited for parallel implementation using a microfluidic system. This bioalgorithm was inspired by the algorithm contained in [16] within the tissue P systems model. The algorithm is not based on the usual brute force generate/test technique, but builds the space solution gradually. The
Theoretical Computer Science, 2003
... 781–800. [10] E. Csuhaj-Varju, J. Dassow, J. Kelemen and Gh. Păun, Grammar Systems. A Grammat... more ... 781–800. [10] E. Csuhaj-Varju, J. Dassow, J. Kelemen and Gh. Păun, Grammar Systems. A Grammatical Approach to Distribution and Cooperation, Gordon and Breach, London (1994). [11] E. Csuhaj-Varju, C. Martin-Vide and V. Mitrana, Multiset automata, CS Calude, Gh. ...
Department of Artificial Intelligence, Faculty of Computer Science, Polytechnical University of M... more Department of Artificial Intelligence, Faculty of Computer Science, Polytechnical University of Madrid Campus de Montegancedo, Boadilla del Monte 28660, Madrid, Spain E-mail: ¡£¢¥¤¦¡£ §© ¦ ¥ ¤£!" $ #&% ... Andrés Silva Department of Languages and Software Engineering, ...
Fundamenta …, 2005
The operations of symport and antiport, directly inspired from biology, are already known to be r... more The operations of symport and antiport, directly inspired from biology, are already known to be rather powerful when used in the framework of P systems. In this paper we confirm this observation with a quite surprising result: P systems with symport/antiport rules using only three objects can simulate any counter machine, while systems with only two objects can simulate any blind counter machine. In the first case, the universality (of generating sets of numbers) is obtained also for a small number of membranes, four.
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Papers by Alfonso Rodríguez-Patón