bluuebunny/crossref_metadata_2025_split huggingface dataset:
Computational approaches to standard-compliant biofilm data for reliable analysis and integration
Authors: Sousa Ana Margarida , Ferreira Andreia , Azevedo Nuno F. , Pereira Maria Olivia , Lourenço Anália 
Published: December 2017

Summary The study of microorganism consortia, also known as biofilms, is associated to a number of applications in biotechnology, ecotechnology and clinical domains. Nowadays, biofilm studies are heterogeneous and data-intensive, encompassing different levels of analysis. Computational modelling of biofilm studies has become thus a requirement to make sense of these vast and ever-expanding biofilm data volumes.The rationale of the present work is a machine-readable format for representing biofilm studies and supporting biofilm data interchange and data integration. This format is supported by the Biofilm Science Ontology (BSO), the first ontology on biofilms information. The ontology is decomposed into a number of areas of interest, namely: the Experimental Procedure Ontology (EPO) which describes biofilm experimental procedures; the Colony Morphology Ontology (CMO) which characterises morphologically microorganism colonies; and other modules concerning biofilm phenotype, antimicrobial susceptibility and virulence traits. The overall objective behind BSO is to develop semantic resources to capture, represent and share data on biofilms and related experiments in a regularized fashion manner. Furthermore, the present work also introduces a framework in assistance of biofilm data interchange and analysis - BiofOmics (http://biofomics.org) - and a public repository on colony morphology signatures - MorphoCol (http://stardust.deb.uminho.pt/morphocol).
Automatic knowledge extraction in sequencing analysis with multiagent system and grid computing
Authors: González Roberto , Zato Carolina , Benito Rocío , Bajo Javier , Hernández Jesús M. , De Paz Juan F. , Vera Vicente , Corchado Juan M. 
Published: December 2017

Summary Advances in bioinformatics have contributed towards a significant increase in available information. Information analysis requires the use of distributed computing systems to best engage the process of data analysis. This study proposes a multiagent system that incorporates grid technology to facilitate distributed data analysis by dynamically incorporating the roles associated to each specific case study. The system was applied to genetic sequencing data to extract relevant information about insertions, deletions or polymorphisms.
A Semi-Automated Approach for Anatomical Ontology Mapping
Authors: Petrov Peter , Krachunov Milko , Vassilev Dimitar 
Published: December 2017

Summary This paper presents a study in the domain of semi-automated and fully-automated ontology mapping. A process for inferring additional cross-ontology links within the domain of anatomical ontologies is presented and evaluated on pairs from three model organisms. The results of experiments performed with various external knowledge sources and scoring schemes are discussed.
On Comparison of SimTandem with State-of-the-Art Peptide Identification Tools, Efficiency of Precursor Mass Filter and Dealing with Variable Modifications
Authors: Novák Jiří , Hoksza David , Skopal Tomáš , Kohlbacher Oliver 
Published: December 2017

Summary The similarity search in theoretical mass spectra generated from protein sequence databases is a widely accepted approach for identification of peptides from query mass spectra produced by shotgun proteomics. Growing protein sequence databases and noisy query spectra demand database indexing techniques and better similarity measures for the comparison of theoretical spectra against query spectra. We employ a modification of previously proposed parameterized Hausdorff distance for comparisons of mass spectra. The new distance outperforms the original distance, the angle distance and state-of-the-art peptide identification tools OMSSA and X!Tandem in the number of identified peptides even though the q-value is only 0.001. When a precursor mass filter is used as a database indexing technique, our method outperforms OMSSA in the speed of search. When variable modifications are not searched, the search time is similar to X!Tandem. We show that the precursor mass filter is an efficient database indexing technique for high-accuracy data even though many variable modifications are being searched. We demonstrate that the number of identified peptides is bigger when variable modifications are searched separately by more search runs of a peptide identification engine. Otherwise, the false discovery rates are affected by mixing unmodified and modified spectra together resulting in a lower number of identified peptides. Our method is implemented in the freely available application SimTandem which can be used in the framework TOPP based on OpenMS.
Model checking software for phylogenetic trees using distribution and database methods
Authors: Requeno José Ignacio , Colom José Manuel 
Published: December 2017

Summary 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.
BioNetLink - An Architecture for Working with Network Data
Authors: Klapperstück Matthias , Schreiber Falk 
Published: December 2017

Summary The visualization of biological data gained increasing importance in the last years. There is a large number of methods and software tools available that visualize biological data including the combination of measured experimental data and biological networks. With growing size of networks their handling and exploration becomes a challenging task for the user. In addition, scientists also have an interest in not just investigating a single kind of network, but on the combination of different types of networks, such as metabolic, gene regulatory and protein interaction networks. Therefore, fast access, abstract and dynamic views, and intuitive exploratory methods should be provided to search and extract information from the networks. This paper will introduce a conceptual framework for handling and combining multiple network sources that enables abstract viewing and exploration of large data sets including additional experimental data. It will introduce a three-tier structure that links network data to multiple network views, discuss a proof of concept implementation, and shows a specific visualization method for combining metabolic and gene regulatory networks in an example.
Probabilistic Latent Semantic Analysis Applied to Whole Bacterial Genomes Identifies Common Genomic Features
Authors: Rusakovica J. , Hallinan J. , Wipat A. , Zuliani P. 
Published: December 2017

Summary The spread of drug resistance amongst clinically-important bacteria is a serious, and growing, problem [1]. However, the analysis of entire genomes requires considerable computational effort, usually including the assembly of the genome and subsequent identification of genes known to be important in pathology. An alternative approach is to use computational algorithms to identify genomic differences between pathogenic and non-pathogenic bacteria, even without knowing the biological meaning of those differences. To overcome this problem, a range of techniques for dimensionality reduction have been developed. One such approach is known as latent-variable models [2]. In latent-variable models dimensionality reduction is achieved by representing a high-dimensional data by a few hidden or latent variables, which are not directly observed but inferred from the observed variables present in the model. Probabilistic Latent Semantic Indexing (PLSA) is an extention of LSA [3]. PLSA is based on a mixture decomposition derived from a latent class model. The main objective of the algorithm, as in LSA, is to represent high-dimensional co-occurrence information in a lower-dimensional way in order to discover the hidden semantic structure of the data using a probabilistic framework. In this work we applied the PLSA approach to analyse the common genomic features in methicillin resistant Staphylococcus aureus, using tokens derived from amino acid sequences rather than DNA. We characterised genome-scale amino acid sequences in terms of their components, and then investigated the relationships between genomes and tokens and the phenotypes they generated. As a control we used the non-pathogenic model Gram-positive bacterium Bacillus subtilis.
BacillusRegNet: A transcriptional regulation database and analysis platform for Bacillus species
Authors: Misirli Goksel , Hallinan Jennifer , Röttger Richard , Baumbach Jan , Wipat Anil 
Published: December 2017

Summary As high-throughput technologies become cheaper and easier to use, raw sequence data and corresponding annotations for many organisms are becoming available. However, sequence data alone is not sufficient to explain the biological behaviour of organisms, which arises largely from complex molecular interactions. There is a need to develop new platform technologies that can be applied to the investigation of whole-genome datasets in an efficient and cost-effective manner. One such approach is the transfer of existing knowledge from well-studied organisms to closely-related organisms. In this paper, we describe a system, BacillusRegNet, for the use of a model organism, Bacillus subtilis, to infer genome-wide regulatory networks in less well-studied close relatives. The putative transcription factors, their binding sequences and predicted promoter sequences along with annotations are available from the associated BacillusRegNet website (http://bacillus.ncl.ac.uk).
LmTDRM Database: A Comprehensive Database on Thiol Metabolic Gene/Gene Products in Listeria monocytogenes EGDe
Authors: Srinivas Vanishree , Gopal Shubha 
Published: December 2017

Summary There are a number of databases on the Listeria species and about their genome. However, these databases do not specifically address a set of network that is important in defence mechanism of the bacteria. Listeria monocytogenes EGDe is a well-established intracellular model organism to study host pathogenicity because of its versatility in the host environment. Here, we have focused on thiol disulphide redox metabolic network proteins, specifically in L. monocytogenes EGDe. The thiol redox metabolism is involved in oxidative stress mechanism and is found in all living cells. It functions to maintain the thiol disulphide balance required for protein folding by providing reducing power. Nevertheless, they are involved in the reversible oxidation of thiol groups in biomolecules by creating disulphide bonds; therefore, the term thiol disulphide redox metabolism (TDRM). TDRM network genes play an important role in oxidative stress mechanism and during host-pathogen interaction. Therefore, it is essential to have detailed information on these proteins with regard to other bacteria and its genome analysis to understand the presence of tRNA, transposons, and insertion elements for horizontal gene transfer. LmTDRM database is a new comprehensive web-based database on thiol proteins and their functions. It includes: Description, Search, TDRM analysis, and genome viewer. The quality of these data has been evaluated before they were aggregated to produce a final representation. The web interface allows for various queries to understand the protein function and their annotation with respect to their relationship with other bacteria. LmTDRM is a major step towards the development of databases on thiol disulphide redox proteins; it would definitely help researchers to understand the mechanism of these proteins and their interaction. Database URL: www.lmtdrm.com
Analyzing Phylogenetic Trees with Timed and Probabilistic Model Checking: The Lactose Persistence Case Study
Authors: Requeno José Ignacio , Colom José Manuel 
Published: December 2017

Summary Model checking is a generic verification technique that allows the phylogeneticist to focus on models and specifications instead of on implementation issues. Phylogenetic trees are considered as transition systems over which we interrogate phylogenetic questions written as formulas of temporal logic. Nonetheless, standard logics become insufficient for certain practices of phylogenetic analysis since they do not allow the inclusion of explicit time and probabilities. The aim of this paper is to extend the application of model checking techniques beyond qualitative phylogenetic properties and adapt the existing logical extensions and tools to the field of phylogeny. The introduction of time and probabilities in phylogenetic specifications is motivated by the study of a real example: the analysis of the ratio of lactose intolerance in some populations and the date of appearance of this phenotype.
Exceptional single strand DNA word symmetry: analysis of evolutionary potentialities
Authors: Afreixo Vera , Rodrigues João M. O. S. , Bastos Carlos A. C. 
Published: December 2017

Summary Some previous studies point to the extension of Chargaff’s second rule (the phenomenon of symmetry) to words of large length. However, in random sequences generated by an independent symbol model where the probability of occurrence of complementary nucleotides is the same, we expect that the phenomenon of symmetry holds for all word lengths. In this work, we measure the symmetry above that expected in independence contexts (exceptional symmetry), for several organisms: viruses; archaea; bacteria; eukaryotes. We also create 27 control scenarios with the same length of each genome under study. The results for each organism were compared to those obtained in control scenarios. We created a new organism genomic signature consisting of a vector of the measures of exceptional symmetry for words of lengths 1 through 12. We show that the proposed signature is able to capture essential relationships between organisms.
Geometric approach to string analysis for biosequence classification
Authors: Brimkov Boris 
Published: December 2017

Summary Tools that effectively analyze and compare sequences are of great importance in various areas of applied computational research, especially in the framework of molecular biology. In the present paper, we introduce simple geometric criteria based on the notion of string linearity and use them to compare DNA sequences of various organisms, as well as to distinguish them from random sequences. Several other theoretical and statistical results are outlined as well. Our experiments reveal a substantial difference between biosequences and random sequences – the former having much higher deviation from linearity than the latter – as well as a general trend of increasing deviation from linearity between primitive and biologically complex organisms.
GITIRBio: A Semantic and Distributed Service Oriented- Architecture for Bioinformatics Pipeline
Authors: Castillo Luis F. , López-Gartner Germán , Isaza Gustavo A. , Sánchez Mariana , Arango Jeferson , Agudelo-Valencia Daniel , Castaño Sergio 
Published: December 2017

Summary The need to process large quantities of data generated from genomic sequencing has resulted in a difficult task for life scientists who are not familiar with the use of command-line operations or developments in high performance computing and parallelization. This knowledge gap, along with unfamiliarity with necessary processes, can hinder the execution of data processing tasks. Furthermore, many of the commonly used bioinformatics tools for the scientific community are presented as isolated, unrelated entities that do not provide an integrated, guided, and assisted interaction with the scheduling facilities of computational resources or distribution, processing and mapping with runtime analysis. This paper presents the first approximation of a Web Services platform-based architecture (GITIRBio) that acts as a distributed front-end system for autonomous and assisted processing of parallel bioinformatics pipelines that has been validated using multiple sequences. Additionally, this platform allows integration with semantic repositories of genes for search annotations. GITIRBio is available at: http://c-head.ucaldas.edu.co:8080/gitirbio
Specifications of Standards in Systems and Synthetic Biology
Authors: Schreiber Falk , Bader Gary D. , Golebiewski Martin , Hucka Michael , Kormeier Benjamin , Le Novère Nicolas , Myers Chris , Nickerson David , Sommer Björn , Waltemath Dagmar , Weise Stephan 
Published: December 2017

Summary Standards shape our everyday life. From nuts and bolts to electronic devices and technological processes, standardised products and processes are all around us. Standards have technological and economic benefits, such as making information exchange, production, and services more efficient. However, novel, innovative areas often either lack proper standards, or documents about standards in these areas are not available from a centralised platform or formal body (such as the International Standardisation Organisation).Systems and synthetic biology is a relatively novel area, and it is only in the last decade that the standardisation of data, information, and models related to systems and synthetic biology has become a community-wide effort. Several open standards have been established and are under continuous development as a community initiative. COMBINE, the ‘COmputational Modeling in BIology’ NEtwork [1] has been established as an umbrella initiative to coordinate and promote the development of the various community standards and formats for computational models. There are yearly two meeting, HARMONY (Hackathons on Resources for Modeling in Biology), Hackathon-type meetings with a focus on development of the support for standards, and COMBINE forums, workshop-style events with oral presentations, discussion, poster, and breakout sessions for further developing the standards. For more information see http://co.mbine.org/.So far the different standards were published and made accessible through the standards’ web-pages or preprint services. The aim of this special issue is to provide a single, easily accessible and citable platform for the publication of standards in systems and synthetic biology. This special issue is intended to serve as a central access point to standards and related initiatives in systems and synthetic biology, it will be published annually to provide an opportunity for standard development groups to communicate updated specifications.
Simulation Experiment Description Markup Language (SED-ML) Level 1 Version 2
Authors: Bergmann Frank T. , Cooper Jonathan , Le Novère Nicolas , Nickerson David , Waltemath Dagmar 
Published: December 2017

Summary The number, size and complexity of computational models of biological systems are growing at an ever increasing pace. It is imperative to build on existing studies by reusing and adapting existing models and parts thereof. The description of the structure of models is not sufficient to enable the reproduction of simulation results. One also needs to describe the procedures the models are subjected to, as recommended by the Minimum Information About a Simulation Experiment (MIASE) guidelines.This document presents Level 1 Version 2 of the Simulation Experiment Description Markup Language (SED-ML), a computer-readable format for encoding simulation and analysis experiments to apply to computational models. SED-ML files are encoded in the Extensible Markup Language (XML) and can be used in conjunction with any XML-based model encoding format, such as CellML or SBML. A SED-ML file includes details of which models to use, how to modify them prior to executing a simulation, which simulation and analysis procedures to apply, which results to extract and how to present them. Level 1 Version 2 extends the format by allowing the encoding of repeated and chained procedures.
SBML Level 3 package: Hierarchical Model Composition, Version 1 Release 3
Authors: Smith Lucian P. , Hucka Michael , Hoops Stefan , Finney Andrew , Ginkel Martin , Myers Chris J. , Moraru Ion , Liebermeister Wolfram 
Published: December 2017

Summary Constructing a model in a hierarchical fashion is a natural approach to managing model complexity, and offers additional opportunities such as the potential to re-use model components. The SBML Level 3 Version 1 Core specification does not directly provide a mechanism for defining hierarchical models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Hierarchical Model Composition package for SBML Level 3 adds the necessary features to SBML to support hierarchical modeling. The package enables a modeler to include submodels within an enclosing SBML model, delete unneeded or redundant elements of that submodel, replace elements of that submodel with element of the containing model, and replace elements of the containing model with elements of the submodel. In addition, the package defines an optional “port” construct, allowing a model to be defined with suggested interfaces between hierarchical components; modelers can chose to use these interfaces, but they are not required to do so and can still interact directly with model elements if they so chose. Finally, the SBML Hierarchical Model Composition package is defined in such a way that a hierarchical model can be “flattened” to an equivalent, non-hierarchical version that uses only plain SBML constructs, thus enabling software tools that do not yet support hierarchy to nevertheless work with SBML hierarchical models.
Systems Biology Markup Language (SBML) Level 2 Version 5: Structures and Facilities for Model Definitions
Authors: Hucka Michael , Bergmann Frank T. , Dräger Andreas , Hoops Stefan , Keating Sarah M. , Le Novère Nicolas , Myers Chris J. , Olivier Brett G. , Sahle Sven , Schaff James C. , Smith Lucian P. , Waltemath Dagmar , Wilkinson Darren J. 
Published: December 2017

Summary Computational models can help researchers to interpret data, understand biological function, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that can be exchanged between different software systems. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Version 5 of SBML Level 2. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project web site, http://sbml.org/.