Martín Diéguez

Differential evolution for protein structure prediction using the HP model

We used Differential Evolution (DE) for the problem of protein structure prediction. We employed the HP model to represent the folding conformations of a protein in a lattice. In this model the nature of amino acids is reduced considering only two types: hydrophobic residues (H) and polar residues (P), which is based on the recognition that hydrophobic interactions are a dominant force in protein folding. Given a primary sequence of amino acids, the problem is to search for the folding structure in the lattice that minimizes an energy potential. This energy reflects the fact that the hydrophobic amino acids have a propensity to form a hydrophobic core. The complexity of the problem has been shown to be NP-hard, with minimal progress achieved in this category of ab initio folding. We combined DE with methods to transform illegal protein conformations to feasible ones, showing the capabilities of the hybridized DE with respect to previous works.

STeLP: a tool for temporal answer set programming

In this paper we present STeLP, a solver for Answer Set Programming with temporal operators. Taking as an input a particular kind of logic program with modal operators (called Splitable Temporal Logic Program), STeLP obtains its set of temporal equilibrium models (a generalisation of stable models for this extended syntax). The obtained set of models is represented in terms of a deterministic Buchi automaton capturing the complete program behaviour. In small examples, this automaton can be graphically displayed in a direct and readable way. The input language provides a set of constructs which allow a simple definition of temporal logic programs, including a special syntax for action domains that can be exploited to simplify the graphical output. STeLP combines the use of a standard ASP solver with a linear temporal logic model checker in order to find all models of the input theory.

Temporal equilibrium logic: a survey

Abstract This paper contains a survey of the main definitions and results obtained to date related to Temporal Equilibrium Logic, a nonmonotonic hybrid approach that combines Equilibrium Logic (the best-known logical characterisation for the stable models semantics of logic programs) with Linear-Time Temporal Logic.

Cellular automata for modeling protein folding using the HP model

We used cellular automata (CA) for the modeling of the temporal folding of proteins. Unlike the focus of the vast research already done on the direct prediction of the final folded conformations, we will model the temporal and dynamic folding process. The CA model defines how the amino acids interact through time to obtain a folded conformation. We employed the TIP model to represent the protein conformations in a lattice, we extended the classical CA models using artificial neural networks for their implementation, and we used evolutionary computing to automatically obtain the models by means of Differential Evolution. Moreover, the modeling of the folding provides the final protein conformation.

Paving the Way for Temporal Grounding.

In this paper we consider the problem of introducing variables in temporal logic programs under the formalism of Temporal Equilibrium Logic (TEL), an extension of Answer Set Programming (ASP) for dealing with linear-time modal operators. We provide several fundamental contributions that pave the way for the implementation of a grounding process, that is, a method that allows replacing variables by ground instances in all the possible (or better, relevant) ways.

Temporal Here and There

Temporal Here and There (THT) constitutes the logical foundations of Temporal Equilibrium Logic. Nevertheless, it has never been studied in detail since results about axiomatisation and interdefinability of modal operators remained unknown. In this paper we provide a sound and complete axiomatic system for THT together with several results on interdefinability of modal operators.

An infinitary encoding of temporal equilibrium logic

This paper studies the relation between two recent extensions of propositional Equilibrium Logic, a well-known logical characterisation of Answer Set Programming. In particular, we show how Temporal Equilibrium Logic, which introduces modal operators as those typically handled in Linear-Time Temporal Logic (LTL), can be encoded into Infinitary Equilibrium Logic, a recent formalisation that allows the use of infinite conjunctions and disjunctions. We prove the correctness of this encoding and, as an application, we further use it to show that the semantics of the temporal logic programming formalism called TEMPLOG is subsumed by Temporal Equilibrium Logic.

Temporal Logic Modeling of Biological Systems

Metabolic networks, formed by a series of metabolic pathways, are made of intracellular and extracellular reactions that determine the biochemical properties of a cell, and by a set of interactions that guide and regulate the activity of these reactions. Cancer, for example, can sometimes appear in a cell as a result of some pathology in a metabolic pathway. Most of these pathways are formed by an intricate and complex network of chain reactions, and can be represented in a human readable form using graphs which describe the cell signaling pathways. In this paper, we define a logic, called Molecular Interaction Logic (MIL), able to represent these graphs and we present a method to automatically translate graphs into MIL formulas. Then we show how MIL formulas can be translated into linear time temporal logic, and then grounded into propositional classical logic. This enables us to solve complex queries on graphs using only propositional classical reasoning tools such as SAT solvers.

Protein folding with cellular automata in the 3D HP model

In the difficult ab initio prediction in protein folding only the information of the primary structure of amino acids is used to determine the final folded conformation. The complexity of the interactions and the nature of the amino acid elements are reduced with the use of lattice models like HP, which categorizes the amino acids regarding their hydrophobicity. On the contrary to the intense research performed on the direct prediction of the final folded conformation, our aim here is to model the dynamic and emergent folding process through time, using the scheme of cellular automata but implemented with artificial neural networks optimized with Differential Evolution. Moreover, as the iterative folding also provides the final folded conformation, we can compare the results with those from direct prediction methods of the final protein conformation.

Abductive Reasoning on Molecular Interaction Maps

Metabolic networks, formed by a series of metabolic pathways, are made of intra-cellular and extracellular reactions that determine the biochemical properties of a cell, and by a set of interactions that guide and regulate the activity of these reactions. Cancer, for example, can sometimes appear in a cell as a result of some pathology in a metabolic pathway. Most of these pathways are formed by an intricate and complex network of chain reactions, and are often represented in Molecular Interaction Maps (MIM), a graphical, human readable form of the cell cycle checkpoint pathways. In this paper, we present a logic, called Molecular Interaction Logic, which semantically characterizes MIMs and, moreover, allows us to apply deductive and abductive reasoning on MIMs in order to find inconsistencies, answer queries and infer important properties about those networks.