José Ignacio Requeno

Temporal logics for phylogenetic analysis via model checking

The need for general-purpose algorithms for the study of biological properties in phylogenetics motivates the research in formal verification frameworks so that researchers can focus their efforts exclusively on evolution modelling and property specification. To this end, model checking, a mature automated verification technique from computer science, is proposed for phylogenetic analysis. Three cornerstones found our approach: modelling evolution dynamics with transition systems; specifying phylogenetic properties using temporal logic formulae; and verifying the latter by means of automated computer tools. As prominent advantages stemming of studying phylogenetic properties with this approach, different models of evolution can be considered, complex properties can be specified as the logical composition of others, and the refinement of unfulfilled properties as well as the discovery of new ones can be undertaken by exploiting the verification results.

Modeling performance of Hadoop applications: A journey from queueing networks to stochastic well formed nets

Nowadays, many enterprises commit to the extraction of actionable knowledge from huge datasets as part of their core business activities. Applications belong to very different domains such as fraud detection or one-to-one marketing, and encompass business analytics and support to decision making in both private and public sectors. In these scenarios, a central place is held by the MapReduce framework and in particular its open source implementation, Apache Hadoop. In such environments, new challenges arise in the area of jobs performance prediction, with the needs to provide Service Level Agreement guarantees to the end-user and to avoid waste of computational resources. In this paper we provide performance analysis models to estimate MapReduce job execution times in Hadoop clusters governed by the YARN Capacity Scheduler. We propose models of increasing complexity and accuracy, ranging from queueing networks to stochastic well formed nets, able to estimate job performance under a number of scenarios of interest, including also unreliable resources. The accuracy of our models is evaluated by considering the TPC-DS industry benchmark running experiments on Amazon EC2 and the CINECA Italian supercomputing center. The results have shown that the average accuracy we can achieve is in the range 9–14%.

Phylogenetic Analysis Using an SMV Tool

The need for general methods to verify biological properties in phylogenetics motivates research in formal frameworks so that biologists can focus their efforts exclusively in evolution modeling and property specification. Model checking is proposed to this end. Three pillars found this approach: modeling evolution dynamics as transition systems; specifying phylogenetic properties using temporal logic formulae; and verifying the former by means of automated computer tools. As prominent advantages for studying biological properties under our approach, different models of evolution can be considered, complex properties can be specified as the logical composition of others, and the refinement of unfulfilled properties as well as the discovery of new ones can be undertaken by exploiting the results of verification. Preliminary experimental results using the Cadence Symbolic Model Verifier support the feasibility of the methodology.

Temporal Logics for Phylogenetic Analysis via Model Checking

The need for general-purpose algorithms for studying biological properties in phylogenetics motivates research into formal verification frameworks. Researchers can focus their efforts exclusively on evolution trees and property specifications. To this end, model checking, a mature automated verification technique originating in computer science, is applied to phylogenetic analysis. Our approach is based on three cornerstones: a logical modeling of the evolution with transition systems; the specification of both phylogenetic properties and trees using flexible temporal logic formulas; and the verification of the latter by means of automated computer tools. The most conspicuous result is the inception of a formal framework which allows for a symbolic manipulation of biological data (based on the codification of the taxa). Additionally, different logical models of evolution can be considered, complex properties can be specified in terms of the logical composition of others, and the refinement of unfulfilled properties as well as the discovery of new properties can be undertaken by exploiting the verification results. Some experimental results using a symbolic model verifier support the feasibility of the approach.

Compact Representation of Biological Sequences Using Set Decision Diagrams

Nowadays, the exponential availability of biological sequences and the complexity of the computational methods that use them as input motivate the research of new compact representations. To this end, we propose an alternative method for storing sets of sequences based on set decision diagrams instead of classical compression techniques. The set decision diagrams are an extension of the reduced ordered binary decision diagrams, a graph data structure used as a symbolic compact representation of sets or relations between sets. Some experiments with genes of the mitochondrion DNA support the feasibility of our approach.

Performance Analysis of Apache Storm Applications Using Stochastic Petri Nets

Real-time data-processing applications, such as those developed using Apache Storm, need to address highly demanding performance requirements. Engineers should assess these performance requirements while they configure their Storm designs to specific execution contexts, i.e., multi-user private or public cloud infrastructures. To this end, we propose a quality-driven framework for Apache Storm, that covers the following steps. The design with UML, using a novel profile for Apache Storm, allowing performance metrics definition. The transformation of the design into a performance model, concretely stochastic Petri nets. Last but not least, the simulation of the performance model and the retrieval of performance results.

Sliced Model Checking for Phylogenetic Analysis

Model checking provides a powerful and flexible formal framework to state and verify biological properties on phylogenies. However, current model checking techniques fail to scale up the big amount of biological information relevant to each state of the system. This fact motivates the development of novel cooperative algorithms and slicing techniques that distribute not the graph structure of a phylogenetic system but the state information contained in its nodes.

A systematic approach for performance evaluation using process mining: the POSIDONIA operations case study

Modelling plays an important role in the development of software applications, in particular for the assessment of non functional requirements such as performance. The value of a model depends on the level of alignment with the reality. In this paper, we propose a systematic approach to get a performance model that is a good representation of the system under analysis. From an UML-based system design we get automatically a normative Petri net model, which formally represents the system supposed behaviour, by applying model-to-model (M2M) transformation techniques. Then, a conformance checking technique is iteratively applied to align -from the qualitative point of view- the normative model and the data log until the required fitness threshold is not reached. Finally, a trace-driven simulation technique is used to enrich the aligned model with timing specification from the data log, then obtaining the performance Generalized Stochastic Petri Net (GSPN) model. The proposed approach has been applied to a customizable Integrated Port Operations Management System, POSIDONIA Operations, where the performance model has been used to analyse the scalability of the product considering different deployment configurations.

Evaluation of properties over phylogenetic trees using stochastic logics.

BackgroundModel checking has been recently introduced as an integrated framework for extracting information of the phylogenetic trees using temporal logics as a querying language, an extension of modal logics that imposes restrictions of a boolean formula along a path of events. The phylogenetic tree is considered a transition system modeling the evolution as a sequence of genomic mutations (we understand mutation as different ways that DNA can be changed), while this kind of logics are suitable for traversing it in a strict and exhaustive way. Given a biological property that we desire to inspect over the phylogeny, the verifier returns true if the specification is satisfied or a counterexample that falsifies it. However, this approach has been only considered over qualitative aspects of the phylogeny.ResultsIn this paper, we repair the limitations of the previous framework for including and handling quantitative information such as explicit time or probability. To this end, we apply current probabilistic continuous-time extensions of model checking to phylogenetics. We reinterpret a catalog of qualitative properties in a numerical way, and we also present new properties that couldn’t be analyzed before. For instance, we obtain the likelihood of a tree topology according to a mutation model. As case of study, we analyze several phylogenies in order to obtain the maximum likelihood with the model checking tool PRISM. In addition, we have adapted the software for optimizing the computation of maximum likelihoods.ConclusionsWe have shown that probabilistic model checking is a competitive framework for describing and analyzing quantitative properties over phylogenetic trees. This formalism adds soundness and readability to the definition of models and specifications. Besides, the existence of model checking tools hides the underlying technology, omitting the extension, upgrade, debugging and maintenance of a software tool to the biologists. A set of benchmarks justify the feasibility of our approach.

Model checking software for phylogenetic trees using distribution and database methods.

Model checking, a generic and formal paradigm stemming from computer science based on temporal logics, has been proposed for the study of biological properties that emerge from the labeling of the states defined over the phylogenetic tree. This strategy allows us to use generic software tools already present in the industry. However, the performance of traditional model checking is penalized when scaling the system for large phylogenies. To this end, two strategies are presented here. The first one consists of partitioning the phylogenetic tree into a set of subgraphs each one representing a subproblem to be verified so as to speed up the computation time and distribute the memory consumption. The second strategy is based on uncoupling the information associated to each state of the phylogenetic tree (mainly, the DNA sequence) and exporting it to an external tool for the management of large information systems. The integration of all these approaches outperforms the results of monolithic model checking and helps us to execute the verification of properties in a real phylogenetic tree.