Finite Models of Splicing and Their Complexity

Durante las dos últimas décadas ha surgido una colaboración estrecha entre informáticos, bioquímicos y biólogos moleculares, que ha dado lugar a la investigación en un área conocida como la computación biomolecular. El trabajo en esta tesis pertenece a este área, y estudia un modelo de cómputo llamado sistema de empalme (splicing system). El empalme es el modelo formal del corte y de la recombinación de las moléculas de ADN bajo la influencia de las enzimas de la restricción.Esta tesis presenta el trabajo original en el campo de los sistemas de empalme, que, como ya indica el título, se puede dividir en dos partes. La primera parte introduce y estudia nuevos modelos finitos de empalme. La segunda investiga aspectos de complejidad (tanto computacional como descripcional) de los sistema de empalme. La principal contribución de la primera parte es que pone en duda la asunción general que una definición finita, más realista de sistemas de empalme es necesariamente débil desde un punto de vista computacional. Estudiamos varios modelos alternativos y demostramos que en muchos casos tienen más poder computacional. La segunda parte de la tesis explora otro territorio. El modelo de empalme se ha estudiado mucho respecto a su poder computacional, pero las consideraciones de complejidad no se han tratado apenas. Introducimos una noción de la complejidad temporal y espacial para los sistemas de empalme. Estas definiciones son utilizadas para definir y para caracterizar las clases de complejidad para los sistemas de empalme. Entre otros resultados, presentamos unas caracterizaciones exactas de las clases de empalme en términos de clases de máquina de Turing conocidas. Después, usando una nueva variante de sistemas de empalme, que acepta lenguajes en lugar de generarlos, demostramos que los sistemas de empalme se pueden usar para resolver problemas. Por último, definimos medidas de complejidad descriptional para los sistemas de empalme. Demostramos que en este respecto los sistemas de empalme finitos tienen buenas propiedades comparadosOver the last two decades, a tight collaboration has emerged between computer scientists, biochemists and molecular biologists, which has spurred research into an area known as DNAComputing (also biomolecular computing). The work in this thesis belongs to this field, and studies a computational model called splicing system. Splicing is the formal model of the cutting and recombination of DNA molecules under the influence of restriction enzymes.This thesis presents original work in the field of splicing systems, which, as the title already indicates, can be roughly divided into two parts: 'Finite models of splicing' on the onehand and 'their complexity' on the other. The main contribution of the first part is that it challenges the general assumption that a finite, more realistic definition of splicing is necessarily weal from a computational point of view. We propose and study various alternative models and show that in most cases they have more computational power, often reaching computational completeness. The second part explores other territory. Splicing research has been mainly focused on computational power, but complexity considerations have hardly been addressed. Here we introduce notions of time and space complexity for splicing systems. These definitions are used to characterize splicing complexity classes in terms of well known Turing machine classes. Then, using a new accepting variant of splicing systems, we show that they can also be used as problem solvers. Finally, we study descriptional complexity. We define measures of descriptional complexity for splicing systems and show that for representing regular languages they have good properties with respect to finite automata, especially in the accepting variant

Developing Tools for Networks of Processors

A great deal of research eort is currently being made in the realm of so called natural computing. Natural computing mainly focuses on the denition, formal description, analysis, simulation and programming of new models of computation (usually with the same expressive power as Turing Machines) inspired by Nature, which makes them particularly suitable for the simulation of complex systems.Some of the best known natural computers are Lindenmayer systems (Lsystems, a kind of grammar with parallel derivation), cellular automata, DNA computing, genetic and evolutionary algorithms, multi agent systems, arti- cial neural networks, P-systems (computation inspired by membranes) and NEPs (or networks of evolutionary processors). This chapter is devoted to this last model

Accepting splicing systems with permitting and forbidding words

Abstract: In this paper we propose a generalization of the accepting splicingsystems introduced in Mitrana et al. (Theor Comput Sci 411:2414?2422,2010). More precisely, the input word is accepted as soon as a permittingword is obtained provided that no forbidding word has been obtained sofar, otherwise it is rejected. Note that in the new variant of acceptingsplicing system the input word is rejected if either no permitting word isever generated (like in Mitrana et al. in Theor Comput Sci 411:2414?2422,2010) or a forbidding word has been generated and no permitting wordhad been generated before. We investigate the computational power ofthe new variants of accepting splicing systems and the interrelationshipsamong them. We show that the new condition strictly increases thecomputational power of accepting splicing systems. Although there areregular languages that cannot be accepted by any of the splicing systemsconsidered here, the new variants can accept non-regular and even non-context-free languages, a situation that is not very common in the case of(extended) finite splicing systems without additional restrictions. We alsoshow that the smallest class of languages out of the four classes definedby accepting splicing systems is strictly included in the class of context-free languages. Solutions to a few decidability problems are immediatelyderived from the proof of this result

Evaluating space measures in P systems

P systems with active membranes are a variant of P systems where membranes can be created by division of existing membranes, thus creating an exponential amount of resources in a polynomial number of steps. Time and space complexity classes for active membrane systems have been introduced, to characterize classes of problems that can be solved by different membrane systems making use of different resources. In particular, space complexity classes introduced initially considered a hypothetical real implementation by means of biochemical materials, assuming that every single object or membrane requires some constant physical space (corresponding to unary notation). A different approach considered implementation of P systems in silico, allowing to store the multiplicity of each object in each membrane using binary numbers. In both cases, the elements contributing to the definition of the space required by a system (namely, the total number of membranes, the total number of objects, the types of different membranes, and the types of different objects) was considered as a whole. In this paper, we consider a different definition for space complexity classes in the framework of P systems, where each of the previous elements is considered independently. We review the principal results related to the solution of different computationally hard problems presented in the literature, highlighting the requirement of every single resource in each solution. A discussion concerning possible alternative solutions requiring different resources is presented

Modelo de computación conexionista inspirado en las redes de procesadores evolutivos y su aprendizaje

La informática teórica es una disciplina básica ya que la mayoría de los avances en informática se sustentan en un sólido resultado de esa materia. En los últimos a~nos debido tanto al incremento de la potencia de los ordenadores, como a la cercanía del límite físico en la miniaturización de los componentes electrónicos, resurge el interés por modelos formales de computación alternativos a la arquitectura clásica de von Neumann. Muchos de estos modelos se inspiran en la forma en la que la naturaleza resuelve eficientemente problemas muy complejos. La mayoría son computacionalmente completos e intrínsecamente paralelos. Por este motivo se les está llegando a considerar como nuevos paradigmas de computación (computación natural). Se dispone, por tanto, de un abanico de arquitecturas abstractas tan potentes como los computadores convencionales y, a veces, más eficientes: alguna de ellas mejora el rendimiento, al menos temporal, de problemas NPcompletos proporcionando costes no exponenciales. La representación formal de las redes de procesadores evolutivos requiere de construcciones, tanto independientes, como dependientes del contexto, dicho de otro modo, en general una representación formal completa de un NEP implica restricciones, tanto sintácticas, como semánticas, es decir, que muchas representaciones aparentemente (sintácticamente) correctas de casos particulares de estos dispositivos no tendrían sentido porque podrían no cumplir otras restricciones semánticas. La aplicación de evolución gramatical semántica a los NEPs pasa por la elección de un subconjunto de ellos entre los que buscar los que solucionen un problema concreto. En este trabajo se ha realizado un estudio sobre un modelo inspirado en la biología celular denominado redes de procesadores evolutivos [55, 53], esto es, redes cuyos nodos son procesadores muy simples capaces de realizar únicamente un tipo de mutación puntual (inserción, borrado o sustitución de un símbolo). Estos nodos están asociados con un filtro que está definido por alguna condición de contexto aleatorio o de pertenencia. Las redes están formadas a lo sumo de seis nodos y, teniendo los filtros definidos por una pertenencia a lenguajes regulares, son capaces de generar todos los lenguajes enumerables recursivos independientemente del grafo subyacente. Este resultado no es sorprendente ya que semejantes resultados han sido documentados en la literatura. Si se consideran redes con nodos y filtros definidos por contextos aleatorios {que parecen estar más cerca a las implementaciones biológicas{ entonces se pueden generar lenguajes más complejos como los lenguajes no independientes del contexto. Sin embargo, estos mecanismos tan simples son capaces de resolver problemas complejos en tiempo polinomial. Se ha presentado una solución lineal para un problema NP-completo, el problema de los 3-colores. Como primer aporte significativo se ha propuesto una nueva dinámica de las redes de procesadores evolutivos con un comportamiento no determinista y masivamente paralelo [55], y por tanto todo el trabajo de investigación en el área de la redes de procesadores se puede trasladar a las redes masivamente paralelas. Por ejemplo, las redes masivamente paralelas se pueden modificar de acuerdo a determinadas reglas para mover los filtros hacia las conexiones. Cada conexión se ve como un canal bidireccional de manera que los filtros de entrada y salida coinciden. A pesar de esto, estas redes son computacionalmente completas. Se pueden también implementar otro tipo de reglas para extender este modelo computacional. Se reemplazan las mutaciones puntuales asociadas a cada nodo por la operación de splicing. Este nuevo tipo de procesador se denomina procesador splicing. Este modelo computacional de Red de procesadores con splicing ANSP es semejante en cierto modo a los sistemas distribuidos en tubos de ensayo basados en splicing. Además, se ha definido un nuevo modelo [56] {Redes de procesadores evolutivos con filtros en las conexiones{ , en el cual los procesadores tan solo tienen reglas y los filtros se han trasladado a las conexiones. Dicho modelo es equivalente, bajo determinadas circunstancias, a las redes de procesadores evolutivos clásicas. Sin dichas restricciones el modelo propuesto es un superconjunto de los NEPs clásicos. La principal ventaja de mover los filtros a las conexiones radica en la simplicidad de la modelización. Otras aportaciones de este trabajo ha sido el dise~no de un simulador en Java [54, 52] para las redes de procesadores evolutivos propuestas en esta Tesis. Sobre el término "procesador evolutivo" empleado en esta Tesis, el proceso computacional descrito aquí no es exactamente un proceso evolutivo en el sentido Darwiniano. Pero las operaciones de reescritura que se han considerado pueden interpretarse como mutaciones y los procesos de filtrado se podrían ver como procesos de selección. Además, este trabajo no abarca la posible implementación biológica de estas redes, a pesar de ser de gran importancia. A lo largo de esta tesis se ha tomado como definición de la medida de complejidad para los ANSP, una que denotaremos como tama~no (considerando tama~no como el número de nodos del grafo subyacente). Se ha mostrado que cualquier lenguaje enumerable recursivo L puede ser aceptado por un ANSP en el cual el número de procesadores está linealmente acotado por la cardinalidad del alfabeto de la cinta de una máquina de Turing que reconoce dicho lenguaje L. Siguiendo el concepto de ANSP universales introducido por Manea [65], se ha demostrado que un ANSP con una estructura de grafo fija puede aceptar cualquier lenguaje enumerable recursivo. Un ANSP se puede considerar como un ente capaz de resolver problemas, además de tener otra propiedad relevante desde el punto de vista práctico: Se puede definir un ANSP universal como una subred, donde solo una cantidad limitada de parámetros es dependiente del lenguaje. La anterior característica se puede interpretar como un método para resolver cualquier problema NP en tiempo polinomial empleando un ANSP de tama~no constante, concretamente treinta y uno. Esto significa que la solución de cualquier problema NP es uniforme en el sentido de que la red, exceptuando la subred universal, se puede ver como un programa; adaptándolo a la instancia del problema a resolver, se escogerín los filtros y las reglas que no pertenecen a la subred universal. Un problema interesante desde nuestro punto de vista es el que hace referencia a como elegir el tama~no optimo de esta red.---ABSTRACT---This thesis deals with the recent research works in the area of Natural Computing {bio-inspired models{, more precisely Networks of Evolutionary Processors first developed by Victor Mitrana and they are based on P Systems whose father is Georghe Paun. In these models, they are a set of processors connected in an underlying undirected graph, such processors have an object multiset (strings) and a set of rules, named evolution rules, that transform objects inside processors[55, 53],. These objects can be sent/received using graph connections provided they accomplish constraints defined at input and output filters processors have. This symbolic model, non deterministic one (processors are not synchronized) and massive parallel one[55] (all rules can be applied in one computational step) has some important properties regarding solution of NP-problems in lineal time and of course, lineal resources. There are a great number of variants such as hybrid networks, splicing processors, etc. that provide the model a computational power equivalent to Turing machines. The origin of networks of evolutionary processors (NEP for short) is a basic architecture for parallel and distributed symbolic processing, related to the Connection Machine as well as the Logic Flow paradigm, which consists of several processors, each of them being placed in a node of a virtual complete graph, which are able to handle data associated with the respective node. All the nodes send simultaneously their data and the receiving nodes handle also simultaneously all the arriving messages, according to some strategies. In a series of papers one considers that each node may be viewed as a cell having genetic information encoded in DNA sequences which may evolve by local evolutionary events, that is point mutations. Each node is specialized just for one of these evolutionary operations. Furthermore, the data in each node is organized in the form of multisets of words (each word appears in an arbitrarily large number of copies), and all the copies are processed in parallel such that all the possible events that can take place do actually take place. Obviously, the computational process just described is not exactly an evolutionary process in the Darwinian sense. But the rewriting operations we have considered might be interpreted as mutations and the filtering process might be viewed as a selection process. Recombination is missing but it was asserted that evolutionary and functional relationships between genes can be captured by taking only local mutations into consideration. It is clear that filters associated with each node allow a strong control of the computation. Indeed, every node has an input and output filter; two nodes can exchange data if it passes the output filter of the sender and the input filter of the receiver. Moreover, if some data is sent out by some node and not able to enter any node, then it is lost. In this paper we simplify the ANSP model considered in by moving the filters from the nodes to the edges. Each edge is viewed as a two-way channel such that the input and output filters coincide. Clearly, the possibility of controlling the computation in such networks seems to be diminished. For instance, there is no possibility to loose data during the communication steps. In spite of this and of the fact that splicing is not a powerful operation (remember that splicing systems generates only regular languages) we prove here that these devices are computationally complete. As a consequence, we propose characterizations of two complexity classes, namely NP and PSPACE, in terms of accepting networks of restricted splicing processors with filtered connections. We proposed a uniform linear time solution to SAT based on ANSPFCs with linearly bounded resources. This solution should be understood correctly: we do not solve SAT in linear time and space. Since any word and auxiliary word appears in an arbitrarily large number of copies, one can generate in linear time, by parallelism and communication, an exponential number of words each of them having an exponential number of copies. However, this does not seem to be a major drawback since by PCR (Polymerase Chain Reaction) one can generate an exponential number of identical DNA molecules in a linear number of reactions. It is worth mentioning that the ANSPFC constructed above remains unchanged for any instance with the same number of variables. Therefore, the solution is uniform in the sense that the network, excepting the input and output nodes, may be viewed as a program according to the number of variables, we choose the filters, the splicing words and the rules, then we assign all possible values to the variables, and compute the formula.We proved that ANSP are computationally complete. Do the ANSPFC remain still computationally complete? If this is not the case, what other problems can be eficiently solved by these ANSPFCs? Moreover, the complexity class NP is exactly the class of all languages decided by ANSP in polynomial time. Can NP be characterized in a similar way with ANSPFCs

Membrane systems with limited parallelism

Membrane computing is an emerging research field that belongs to the more general area of molecular computing, which deals with computational models inspired from bio-molecular processes. Membrane computing aims at defining models, called membrane systems or P systems, which abstract the functioning and structure of the cell. A membrane system consists of a hierarchical arrangement of membranes delimiting regions, which represent various compartments of a cell, and with each region containing bio-chemical elements of various types and having associated evolution rules, which represent bio-chemical processes taking place inside the cell. This work is a continuation of the investigations aiming to bridge membrane computing (where in a compartmental cell-like structure the chemicals to evolve are placed in compartments defined by membranes) and brane calculi (where one considers again a compartmental cell-like structure with the chemicals/proteins placed on the membranes themselves). We use objects both in compartments and on membranes (the latter are called proteins), with the objects from membranes evolving under the control of the proteins. Several possibilities are considered (objects only moved across membranes or also changed during this operation, with the proteins only assisting the move/change or also changing themselves). Somewhat expected, computational universality is obtained for several combinations of such possibilities. We also present a method for solving the NP-complete SAT problem using P systems with proteins on membranes. The SAT problem is solved in O(nm) time, where n is the number of boolean variables and m is the number of clauses for an instance written in conjunctive normal form. Thus, we can say that the solution for each given instance is obtained in linear time. We succeeded in solving SAT by a uniform construction of a deterministic P system which uses rules involving objects in regions, proteins on membranes, and membrane division. Then, we investigate the computational power of P systems with proteins on membranes in some particular cases: when only one protein is placed on a membrane, when the systems have a minimal number of rules, when the computation evolves in accepting or computing mode, etc. This dissertation introduces also another new variant of membrane systems that uses context-free rewriting rules for the evolution of objects placed inside compartments of a cell, and symport rules for communication between membranes. The strings circulate across membranes depending on their membership to regular languages given by means of regular expressions. We prove that these rewriting-symport P systems generate all recursively enumerable languages. We investigate the computational power of these newly introduced P systems for three particular forms of the regular expressions that are used by the symport rules. A characterization of ET0L languages is obtained in this context

DNA Computing: Modelling in Formal Languages and Combinatorics on Words, and Complexity Estimation

DNA computing, an essential area of unconventional computing research, encodes problems using DNA molecules and solves them using biological processes. This thesis contributes to the theoretical research in DNA computing by modelling biological processes as computations and by studying formal language and combinatorics on words concepts motivated by DNA processes. It also contributes to the experimental research in DNA computing by a scaling comparison between DNA computing and other models of computation. First, for theoretical DNA computing research, we propose a new word operation inspired by a DNA wet lab protocol called cross-pairing polymerase chain reaction (XPCR). We define and study a word operation called word blending that models and generalizes an unexpected outcome of XPCR. The input words are uwx and ywv that share a non-empty overlap w, and the output is the word uwv. Closure properties of the Chomsky families of languages under this operation and its iterated version, the existence of a solution to equations involving this operation, and its state complexity are studied. To follow the XPCR experimental requirement closely, a new word operation called conjugate word blending is defined, where the subwords x and y are required to be identical. Closure properties of the Chomsky families of languages under this operation and the XPCR experiments that motivate and implement it are presented. Second, we generalize the sequence of Fibonacci words inspired by biological concepts on DNA. The sequence of Fibonacci words is an infinite sequence of words obtained from two initial letters f(1) = a and f(2)= b, by the recursive definition f(n+2) = f(n+1)*f(n), for all positive integers n, where * denotes word concatenation. After we propose a unified terminology for different types of Fibonacci words and corresponding results in the extensive literature on the topic, we define and explore involutive Fibonacci words motivated by ideas stemming from theoretical studies of DNA computing. The relationship between different involutive Fibonacci words and their borderedness and primitivity are studied. Third, we analyze the practicability of DNA computing experiments since DNA computing and other unconventional computing methods that solve computationally challenging problems often have the limitation that the space of potential solutions grows exponentially with their sizes. For such problems, DNA computing algorithms may achieve a linear time complexity with an exponential space complexity as a trade-off. Using the subset sum problem as the benchmark problem, we present a scaling comparison of the DNA computing (DNA-C) approach with the network biocomputing (NB-C) and the electronic computing (E-C) approaches, where the volume, computing time, and energy required, relative to the input size, are compared. Our analysis shows that E-C uses a tiny volume compared to that required by DNA-C and NB-C, at the cost of the E-C computing time being outperformed first by DNA-C and then by NB-C. In addition, NB-C appears to be more energy efficient than DNA-C for some input sets, and E-C is always an order of magnitude less energy efficient than DNA-C

In Memoriam, Solomon Marcus

This book commemorates Solomon Marcus’s fifth death anniversary with a selection of articles in mathematics, theoretical computer science, and physics written by authors who work in Marcus’s research fields, some of whom have been influenced by his results and/or have collaborated with him

Communication in membrana Systems with symbol Objects.

Esta tesis está dedicada a los sistemas de membranas con objetos-símbolo como marco teórico de los sistemas paralelos y distribuidos de procesamiento de multiconjuntos.Una computación de parada puede aceptar, generar o procesar un número, un vector o una palabra; por tanto el sistema define globalmente (a través de los resultados de todas sus computaciones) un conjunto de números, de vectores, de palabras (es decir, un lenguaje), o bien una función. En esta tesis estudiamos la capacidad de estos sistemas para resolver problemas particulares, así como su potencia computacional. Por ejemplo, las familias de lenguajes definidas por diversas clases de estos sistemas se comparan con las familias clásicas, esto es, lenguajes regulares, independientes del contexto, generados por sistemas 0L tabulados extendidos, generados por gramáticas matriciales sin chequeo de apariciones, recursivamente enumerables, etc. Se prestará especial atención a la comunicación de objetos entre regiones y a las distintas formas de cooperación entre ellos.Se pretende (Sección 3.4) realizar una formalización los sistemas de membranas y construir una herramienta tipo software para la variante que usa cooperación no distribuida, el navegador de configuraciones, es decir, un simulador, en el cual el usuario selecciona la siguiente configuración entre todas las posibles, estando permitido volver hacia atrás. Se considerarán diversos modelos distribuidos. En el modelo de evolución y comunicación (Capítulo 4) separamos las reglas tipo-reescritura y las reglas de transporte (llamadas symport y antiport). Los sistemas de bombeo de protones (proton pumping, Secciones 4.8, 4.9) constituyen una variante de los sistemas de evolución y comunicación con un modo restrictivo de cooperación. Un modelo especial de computación con membranas es el modelo puramente comunicativo, en el cual los objetos traspasan juntos una membrana. Estudiamos la potencia computacional de las sistemas de membranas con symport/antiport de 2 o 3 objetos (Capítulo 5) y la potencia computacional de las sistemas de membranas con alfabeto limitado (Capítulo 6).El determinismo (Secciones 4.7, 5.5, etc.) es una característica especial (restrictiva) de los sistemas computacionales. Se pondrá especial énfasis en analizar si esta restricción reduce o no la potencia computacional de los mismos. Los resultados obtenidos para sistemas de bombeo del protones están transferidos (Sección 7.3) a sistemas con catalizadores bistabiles. Unos ejemplos de aplicación concreta de los sistemas de membranas (Secciones 7.1, 7.2) son la resolución de problemas NP-completos en tiempo polinomial y la resolución de problemas de ordenación.This thesis deals with membrane systems with symbol objects as a theoretical framework of distributed parallel multiset processing systems.A halting computation can accept, generate or process a number, a vector or a word, so the system globally defines (by the results of all its computations) a set of numbers or a set of vectors or a set of words, (i.e., a language), or a function. The ability of these systems to solve particular problems is investigated, as well as their computational power, e.g., the language families defined by different classes of these systems are compared to the classical ones, i.e., regular, context-free, languages generated by extended tabled 0L systems, languages generated by matrix grammars without appearance checking, recursively enumerable languages, etc. Special attention is paid to communication of objects between the regions and to the ways of cooperation between the objects.An attempt to formalize the membrane systems is made (Section 3.4), and a software tool is constructed for the non-distributed cooperative variant, the configuration browser, i.e., a simulator, where the user chooses the next configuration among the possible ones and can go back. Different distributed models are considered. In the evolution-communication model (Chapter 4) rewriting-like rules are separated from transport rules. Proton pumping systems (Sections 4.8, 4.9) are a variant of the evolution-communication systems with a restricted way of cooperation. A special membrane computing model is a purely communicative one: the objects are moved together through a membrane. We study the computational power of membrane systems with symport/antiport of 2 or 3 objects (Chapter 5) and the computational power of membrane systems with a limited alphabet (Chapter 6).Determinism (Sections 4.7, 5.5, etc.) is a special property of computational systems; the question of whether this restriction reduces the computational power is addressed. The results on proton pumping systems can be carried over (Section 7.3) to the systems with bi-stable catalysts. Some particular examples of membrane systems applications are solving NP-complete problems in polynomial time, and solving the sorting problem

Journal of Telecommunications and Information Technology, 2008, nr 3

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