bluuebunny/crossref_metadata_2025 huggingface dataset:
Dynamically Reconfigurable Architectures
Authors: Rychly Marek
Published: November 2017

Dynamic aspects of behavior of software systems in dynamically reconfigurable runtime architectures can result in significant architectural violations during runtime. In such cases, a system's architecture evolves during the runtime according to the actual state of the system's environment, and consequently, runtime reconfigurations may eventually lead to incorrect architecture configurations that were not considered during the system's design phases. These architectural violations are known as architectural erosion or architectural drift, and they contribute to an increasing brittleness of the system, or a lack of its coherence and clarity of its form. This chapter describes and compares possible measures to prevent architectural violations in dynamic service and component models. The aim of this chapter is to evaluate the applicability of those measures in combination with advanced features of reconfigurable runtime architectures such as ad hoc reconfiguration, service or component mobility, composition hierarchy preservation, and architectural aspects.
Model-Based Testing of Highly Configurable Embedded Systems
Authors: Streitferdt Detlef , Kantz Florian , Nenninger Philipp , Ruschival Thomas , Kaul Holger , Bauer Thomas , Hussain Tanvir , Eschbach Robert
Published: November 2017

This chapter reports the results of a cycle computer case study and a previously conducted industrial case study from the automation domain. The key result is a model-based testing process for highly configurable embedded systems. The initial version of the testing process was built upon parameterizeable systems. The cycle computer case study adds the configuration using the product line concept and a feature model to store the parameterizable data. Thus, parameters and their constraints can be managed in a very structured way. Escalating demand for flexibility has made modern embedded software systems highly adjustable. This configurability is often realized through parameters and a highly configurable system possesses a handful of those. Small changes in parameter values can often account for significant changes in the system's behavior, whereas in some other cases, changed parameters may not result in any perceivable reaction. The case studies address the challenge of applying model-based testing to configurable embedded software systems in order to reduce development effort. As a result of the case studies, a model-based testing process was developed. This process integrates existing model-based testing methods and tools such as combinatorial design and constraint processing as well as the product line engineering approach. The testing process was applied as part of the case studies and analyzed in terms of its actual saving potentials, which turned out to reduce the testing effort by more than a third.
A Multi-Agent-Based Approach for Critical Components Identification and Testing
Authors: Mala D. Jeya , Iswarya R.
Published: November 2017

In real time software systems, testing plays a crucial role as any of the critical components in these systems are left undetected, then inadvertent effects will happen which will lead to erroneous operations, system failure, high cost and resource wastage etc. To address this most important and the emergent problem, this research work proposes an effective method by means of multi-agents based approach to identify such critical components and execute test cases along the critical test paths which will aid in effectively covering them during testing. Finally, this paper also compared the performance with existing approaches in terms of time taken for the search process and the component coverage based test adequacy criterion to ensure quality of the software.
Developing Secure Software Using UML Patterns
Authors: Schmidt Holger , Hatebur Denis , Heisel Maritta
Published: November 2017

This chapter presents a security engineering process based on UML security problem frames and concretized UML security problem frames. Both kinds of frames constitute patterns for analyzing security problems and associated solution approaches. They are arranged in a pattern system that makes dependencies between them explicit. The authors describe step-by-step how the pattern system can be used to analyze a given security problem and how solution approaches can be found. Then, solution approaches are specified by generic security components and generic security architectures, which constitute architectural patterns. Finally, the generic security components and the generic security architecture that composes them are refined, and the result is a secure software product built from existing and/or tailor-made security components.
Natural Language Processing
Authors: Yilmaz A. Egemen
Published: November 2017

Requirement analysis is the very first and crucial step in the software development processes. On the other hand, as previously addressed by other researchers, it is the Achilles' heel of the whole process since the requirements lie on the problem space, whereas other software artifacts are on the solution space. Stating the requirements in a clear manner eases the following steps in the process as well as reducing the number of potential errors. In this paper, techniques for the improvement of the requirements expressed in the natural language are revisited. These techniques try to check the requirement quality attributes via lexical and syntactic analysis methods sometimes with generic, and sometimes domain and application specific knowledge bases.
Object-Oriented Cognitive Complexity Measures
Authors: Misra Sanjay , Adewumi Adewole
Published: November 2017

This chapter presents the analysis of ten recently proposed object-oriented metrics based on cognitive informatics. The metrics based on cognitive informatics use cognitive weight. Cognitive weight is the representation of the understandability of the piece of software that evaluates the difficulty experienced in comprehending and/or performing the piece of software. Development of metrics based on Cognitive Informatics (CI) is a new area of research, and from this point of view, for the analysis of these metrics, it is important to know their acceptability from other existing evaluation and validation criteria. This chapter presents a critical review on existing object-oriented cognitive complexity measures. In addition, a comparative study based on some selected attributes is presented.
Excess Entropy in Computer Systems
Authors: Loboz Charles
Published: November 2017

Modern data centers house tens of thousands of servers in complex layouts. That requires sophisticated reporting – turning available terabytes of data into information. The classical approach was introduced decades ago to handle a small number of lightly connected computers. Today, we also need to identify problematic groups of servers, strange patterns in load, and changes in composition with minimal human involvement. The authors show how, as a single concept, entropy can describe multiple aspects of system use. Entropy is well grounded in physics, used in economics, and the authors extend it to large computer systems.
Parameterized Transformation Schema for a Non-Functional Properties Model in the Context of MDE
Authors: García Gustavo Millán , Crespo Rubén González , Martínez Oscar Sanjuán
Published: November 2017

The integration between design models of software systems and analytical models of non-functional properties is an ideal framework on which lay the foundation for a deep understanding of the architectures present in software systems and their properties. In order to reach this integration, this chapter proposes a parameterized transformation for a model of performance properties derived from a system model in the MDE context. The idea behind a parameterized term is to leave open the transformation framework to adopt future improvements and make the approach reusable. The authors believe that this kind of integration permits the addition of analysis capabilities to the software development process and permits an early evaluation of design decisions.
A Mixed-Criticality Integration in Cyber-Physical Systems
Authors: Isakovic Haris , Grosu Radu
Published: November 2017

A Cyber-Physical System (CPS) describes a system or a system-of-systems closely and actively coupled with environment. It comprises the digital intelligence system, a co-dependent physical system (i.e., electrical, mechanical) and the system environment. Since the beginning of modern computer systems integration was ever present challenge, from the huge single room computers to the IoT. Today applications interleave and build larger systems with different system requirements and properties. Implementation of safety critical applications together with non-critical applications within the same platform is almost inevitable in modern industrial systems. This article provides a retrospective overview of the major integration challenges and the current problems in mixed-criticality environments. Finally, it provides an insight in a hardware solution which creates deterministic platform for mixed-criticality applications.
Organization and Information Support of Expert Reviews of I&C Systems Modernization at NPP of Ukraine
Authors: Klevtsov Alexander , Inyushev Vladislav
Published: November 2017

Safety assessment of Instrumentation and Control systems (I&C systems) of NPP is performed during expert reviews of nuclear and radiation safety in the framework of the licensing process at all life cycle stages of I&C systems. Life cycle stages of NPP I&C systems, which are determined by current guides, rules, and standards of Ukraine, are considered in the chapter. A short overview of the main principles of safety regulation of nuclear facilities, licensing, and expert review of nuclear and radiation safety is presented. Specific safety assessments of NPP I&C systems at different life cycle stages are analyzed (in particular, a list of documents proving NPP I&C safety that should be submitted for expert review at each stage is given). Such assessment is a labor-intensive process that requires processing considerable amounts of a variety of information. Hence, it is reasonable to provide experts with information support for assessing the safety of NPP I&C systems. The chapter gives suggestions and examples of practical implementation of the automated system for support of expert activities and considers the knowledge base for I&C systems.
Preventing the Increasing Resistance to Change Through a Multi-Model Environment as a Reference Model in Software Process Improvement
Authors: Muñoz Mirna , Mejia Jezreel
Published: November 2017

Organizational process improvement offers a key opportunity for organizations to become more efficient. As a consequence, the software industry, among others, is more interested in software process improvement. However, one of the most common issues identified when an organization tries to implement a software process improvement initiative is the difficulty that they face in selecting the reference model and its adaptation to the current organization scenario. Moreover, selecting the wrong reference model according to the way the organization works becomes a trigger to increase resistance to change. This chapter presents a methodology that allows the use of a multi-model environment as a reference model so that the organization can select best practices that best fit the way it works to implement software process improvement. The results of the implementation of an improvement using the methodology proposed are also presented.
Prediction of Change-Prone Classes Using Machine Learning and Statistical Techniques
Authors: Malhotra LinRuchika , Bansal Ankita Jain
Published: November 2017

For software development, availability of resources is limited, thereby necessitating efficient and effective utilization of resources. This can be achieved through prediction of key attributes, which affect software quality such as fault proneness, change proneness, effort, maintainability, etc. The primary aim of this chapter is to investigate the relationship between object-oriented metrics and change proneness. Predicting the classes that are prone to changes can help in maintenance and testing. Developers can focus on the classes that are more change prone by appropriately allocating resources. This will help in reducing costs associated with software maintenance activities. The authors have constructed models to predict change proneness using various machine-learning methods and one statistical method. They have evaluated and compared the performance of these methods. The proposed models are validated using open source software, Frinika, and the results are evaluated using Receiver Operating Characteristic (ROC) analysis. The study shows that machine-learning methods are more efficient than regression techniques. Among the machine-learning methods, boosting technique (i.e. Logitboost) outperformed all the other models. Thus, the authors conclude that the developed models can be used to predict the change proneness of classes, leading to improved software quality.
Software Evolution Visualization
Authors: Novais Renato Lima , Neto Manoel Gomes de Mendonça
Published: November 2017

Software Visualization is the field of Software Engineering that aims to help people to understand software through the use of visual resources. It can be effectively used to analyze and understand the large amount of data produced during software evolution. Several Software Evolution Visualization (SEV) approaches have been proposed. The goals of the proposed approaches are varied, and they try to help programmers and managers to deal with software evolution in their daily software activities. Despite their goals, their applicability in real development scenarios is questionable. In this chapter, the authors discuss the current state of the art and challenges in software evolution visualization, presenting issues and problems related to the area, and they propose some solutions and recommendations to circumvent them. Finally, the authors discuss some research directions for the SEV domain.
Towards a New Approach for Controlling the Reorganization Process of Multi-Agent Systems
Authors: Ayyoub Kalache , Mokhati Farid , Badri Mourad
Published: November 2017

Reorganization in Multi-Agent Systems plays a crucial role in the dynamic adaptation of the structure and the behaviour of organizations. In order to ensure consistency of the resulting organization, the reorganization process has to be controlled. This paper proposes a novel approach for controlling the reorganization process of Multi-Agent Systems, which are specified and implemented using the Framework OMACS (Organizational Model for Adaptive Computational Systems). The proposed control process is accomplished using the Framework MOP (Monitoring Oriented Programming) for supporting the verification of some reorganizational properties. The proposed approach, supported by a software tool that we developed, is illustrated using a concrete case study.
A Relational Perspective on Patient Engagement
Authors: Donato Silvia , Bertoni Anna
Published: November 2017

Research on the engagement of patients and their partners and the literature on couple relationships have remained surprisingly separated. In response to this gap, the first aim of the chapter is to show the advantages of an integration of these two lines of research in the context of promoting engagement in patients and their partners. Particular attention is devoted to couples' stress and coping literature and to those few studies that investigated the role played for patient engagement by characteristics of patients, partners, and their relationship. Couple-based research can inform engagement literature about facilitators and barriers to couples' coping with illness and about how to promote engagement in the context of the couple. Within this research, the concept of dyadic coping can be especially helpful in understanding how partners can effectively deal with the stress related to acute and chronic illness as well as the barriers to this process. A second aim of the chapter is to connect the suggestions from couple-based research with the field of engagement promotion.
A Collaborative M-Health Platform for Evidence-Based Self-Management and Detection of Chronic Multimorbidity Development and Progression
Authors: Giokas Kostas , Katrakazas Panagiotis , Koutsouris Dimitris
Published: November 2017

The ageing process of EU population has played a key role raising the prevalence of chronic disease, with more than 80% of people in the last age group (65-74) reported to be having three or more long-term Multimorbidity or Multiple Chronic Conditions (MCCs). The main problem is that currently, clinicians have limited guidance, as well as evidence of how to approach care decisions for such patients. As a consequence, the understanding of how to best take care of patients with multimorbidity conditions, may lead to improvements in Quality of Life (QoL), utilization of healthcare, safety, morbidity and mortality. The root of this problem is not narrowly confined to guidelines development and application, but is inherent throughout the translational path from the generation of evidence to the synthesis of the evidence upon which guidelines depend.
Management of Tacit Knowledge and the Issue of Empowerment of Patients and Stakeholders in the Health Care Sector
Authors: Jacquinet Marc , Curado Henrique , Nobre Ângela Lacerda , Sousa Maria José , Arraya Marco , Pimenta Rui , Martins António Eduardo
Published: November 2017

There is a growing literature on health and health care dedicated to empowerment of patients; but there is still a gap in the literature to conceptualize knowledge, to extend the discussion of the empowerment of the patients to the stakeholders. The discussion is at the level of managerial processes of empowerment and knowledge management related to health care. The present chapter starts with a review on empowerment, especially focused on the health sector. The following sections will develop a critical analysis of empowerment, mainly around the concept of tacit knowledge (Polanyi) and knowledge management. One key variable is the proximity of the actors involved in the empowerment process. This key variable is very much related to the tacitness issue of knowledge production and flows. The chapter extends the discussion of the empowerment of the patients to that of the stakeholders and the general debate about health literacy. A model is briefly described for the purpose of illustrating the learning process in a knowledge management implemented in health care.
Knowledge Sharing for Healthcare and Medicine in Developing Countries
Authors: Moahi Kgomotso H. , Bwalya Kelvin J.
Published: November 2017

Knowledge sharing has always been used as a platform for cross-pollination of ideas and innovations in a bid to improve and enhance performance thereby increasing competitiveness and responsiveness both in organizations and individual levels. Healthcare systems are not an exception. However, for knowledge sharing to take place there is need for certain factors to be noted and addressed such as the individual, organizational and technological. Further, knowledge sharing goes hand in hand with knowledge management and must become part of the strategic fabric of organizations. This chapter focuses on knowledge sharing by health professionals in healthcare and medicine in developing countries. The chapter covers knowledge management and its link with knowledge sharing; the various methods of knowledge sharing in healthcare; factors that make knowledge sharing an important strategic move for healthcare organizations; and factors and issues that affect or determine knowledge sharing behavior. Finally, a literature search for examples of knowledge sharing in developing or low and middle-income countries was conducted and the results are presented. The chapter shows that developing countries have recognized the value of knowledge sharing in healthcare systems and there are tangible signs that this is going to shape cross-pollination of ideas and innovations in the health systems in the foreseeable future.
The Administrative Policy Quandary in Canada's Health Service Organizations
Authors: Paterson Grace I. , MacDonald Jacqueline M. , Mensink Naomi Nonnekes
Published: November 2017

This chapter examines the process for administrative health service policy development with respect to information sharing and decision-making as well as the relationship of policy to decision making. The challenges experienced by health service managers are identified. The administrative health policy experience in Nova Scotia is described. There is a need for integrated policy at multiple levels (public, clinical, and administrative). The quandary is that while working to share health information systems, most Canadian health service organizations continue to individually develop administrative health policy, expending more resources on policy writing than on translation/education, monitoring, or evaluation. By exploring the importance and nature of administrative policy as a foundation for quality improvement in healthcare delivery, a case is made for greater use of health informatics tools and processes.
Social Media
Authors: Kaur Manpreet , Verma Rajesh
Published: November 2017

Internet usage has shown drastic growth in the initial half of the year 2015 in India. The user base has increased over 354 million and with this India has become the top second country after China in terms of internet usage. Facebook is the prime social networking site which is used by 96% of urban users, followed by Google Plus (61%), Twitter (43%) and LinkedIn (24%). This extensive use of social media by the public had attracted the attention of the politicians to use it for election campaigns and has given researchers a reason to find out how politicians are engaging the public through this platform. Influence of Social media on the electorate has been proved from its successful use in the US presidential election in 2008 and by political parties in the 2014 Lok Sabha elections in India. This paper intends to explore the use of social media and its effectiveness in political elections through an extensive literature review. Social media has become an effective tool for political engagement and political participation as it is a low cost media as compared to traditional media. The low cost of this media has made it one of the main source to get information for advanced analysis and in-depth understanding of the electoral process. This paper will provide an insight to politicians, political analysts, journalists and electoral candidates regarding social media usage. The paper will also present a future research agenda to study how political parties can benefit from use of social media and change their strategies to engage workers and the voters.
Social Media and Business
Authors: Gupta Saurabh , Singh Anurag , Duhan Punita
Published: November 2017

The influence of social media on the various facets of society has attracted a lot of attention of the researchers in the last few years who are probing its multifaceted impact. One important aspect of social media is its role in promoting instant gratification. It has far reaching consequences for evolution of self, which in turn has important implications for society and businesses. Drawing from the conceptual foundations of the theories of identity and social comparison, the researchers tried to develop a model as to how the dual role of social media acts to alter the identity and hence behavior. In this context, the significance of the study lies in exposing the intricate interplay between the attributes of social media and the dynamic self. The study goes a long way in providing a deeper understanding of self-concept in connection to social media, which has immense importance for consumer behavior and can help businesses to fine-tune their strategies with the changing consumer psychology.
Visualizing Social Network Influence
Authors: Lipschultz Jeremy Harris
Published: November 2017

Billions of social media users communicate via Web and mobile platforms. A variety of measurement tools may be used to advance research methodologies in the study of computer-mediated communication (CMC). Social networking sites (SNS), such as Twitter, allow researchers to conduct exploratory data scraping and create visual mapping of possible relationships between social network accounts. The nature of the visualization depends upon the number of accounts within the social network, the amount of communication activity, the direction of specific communication, the amplification of messages across the network and other factors. A major challenge of this research method is disclosure and verification of individuals operating online identities. Additionally, most free research tools fail to disclose algorithms for generating scores and ranks. The purpose of this chapter is to explain how individual position, or centrality, is one reflection among many in the measurement of social network influence.
Random Grid and Reversible Watermarking-Based On Verifiable Secret Sharing for Outsourcing Images in Cloud
Authors: Gao Hang , Hu Mengting , Gao Tiegang , Cheng Renhong
Published: November 2017

A novel random grid and reversible watermarking based verifiable secret sharing scheme for outsourcing image in cloud is proposed in the paper. In the proposed scheme, data owner firstly embeds the hash value of the secret image into the secret image itself using reversible watermarking algorithm; then, watermarked image is divided into $n$ sub image. Secondly, the hash of n sub image is calculated, and then the hash value is transformed into the initial value of hyper-chaos, thus n random grids are generated by different hyper-chaos. Lastly, after expanding the sub-image to the same size with the original secret image, it is performer XOR operation with the corresponding random grid, this will accordingly produce $n$ sharing secret. In order to securely outsource the image in the cloud, the generated shares are issued to the $n$ different cloud server. For authorized user, (s)he can get shares from different cloud server, and then can recover the original secret image through a series of decryption operations and extraction of reversible watermarking. The proposed scheme can losslessly restore the original secret image, and have the double verification ability, that is to say, it can verify whether the anyone of the sharing is modified, and it can also verify whether the original secret image is completely reconstructed. Some analysis and comparisons are given to show the security and effectiveness of proposed scheme.
Relationships Among Dimensions of Online Second-Hand Shopping, Satisfaction, and Repurchase Intention
Authors: Swapana Murali , Padmavathy Chandrasekaran
Published: November 2017

The purpose of this study is to examine the relationships among dimensions of online second-hand shopping, customer satisfaction, and repurchase intention. Responses obtained from 608 Indian online second-hand shoppers show that the dimensions of online second-hand shopping such as price, website quality, nostalgia, and brand image influence customer satisfaction. In addition, customer satisfaction positively affects repurchase intention. Findings of the present study provide intuitive guidelines for online second-hand marketers in approaching emerging markets through effective online shopping strategies.
Efficiency Analysis of the U.S. Publicly Held Insurance Industry
Authors: Copeland Mary Kay , Cabanda Emilyn
Published: November 2017

This paper aims to measure and analyze the efficiency of the US publicly-held insurance industry from 2011 to 2013. The paper uses a two-stage efficiency model: (1) data envelopment analysis (DEA), a non-parametric model for measuring the efficiency of 141 panel data of US publicly-held insurance firms, and (2) stochastic Tobit regression model for determining associations between insurers' financial performance and efficiency. Three significant findings are obtained: (1) There is no evidence that US insurance firms consistently improve in efficiency over time using the input-output mix. (2) There is an overall positive significant association between insurers' financial performance and technical efficiency at a very high confidence level. (3) Type of insurance is found to have a negative and significant effect on efficiency. These new findings add empirical evidence to the efficiency analysis of the US insurance industry.
MCWDF
Authors: Shivakumar Shailesh , Pachigolla Venkata Suresh
Published: November 2017

Segregating the web page content into logical chunks is one of the popular techniques for modular organization of web page. While chunk-based approach works well for public web scenarios, in case of mobile-first personalization cases, chunking strategy would not be as effective for performance optimization due to dynamic nature of the Web content and due to the nature of content granularity. In this paper, the authors propose a novel framework Micro chunk based Web Delivery Framework which proposes and uses a novel concept of “micro chunk”. The micro chunk based Web Delivery framework aims to address the performance challenges posed by regular chunk in a personalized web scenario. The authors will look at the methods for creating micro chunk and they will discuss the advantages of micro chunk when compared to a regular chunk for a personalized mobile web scenario. They have created a prototype application implementing the Micro chunk based Web Delivery Framework and benchmarked it against a regular personalized web application to quantify the performance improvements achieved by micro chunk design.
A Simulation Model for Application Development in Data Warehouses
Authors: Rahman Nayem
Published: November 2017

Software development projects have been blamed for being behind schedule, cost overruns, and the delivery of poor quality product. This paper presents a simulation model of a data warehouse to evaluate the feasibility of different software development controls and measures to better manage a software development lifecycle, and improve the performance of the launched software. This paper attempts to address the practical issue of code defects in each stage of data warehouse application development. The author has compared the defect removal rate of their previous project to the newly proposed enhanced project development life cycle that uses code inspection and code scorecard along with other phases of software development life cycle. Simulation results show that the code inspection and code score-carding have achieved a significant code defect reduction. This has also significantly improved the software development process and allowed for a flawless production execution. The author proposes this simulation model to a data warehouse application development process to enable developers to improve their current process.
Evidence for a Complex Mosaic Genome Pattern in a Full-length Hepatitis C Virus Sequence
Authors: Ross R.S. , Verbeeck J. , Viazov S. , Lemey P. , Van Ranst M. , Roggendorf M.
Published: November 2017

The genome of the hepatitis C virus (HCV) exhibits a high genetic variability. This remarkable heterogeneity is mainly attributed to the gradual accumulation of mutational changes, whereas the contribution of recombination events to the evolution of HCV remains controversial so far. While performing phylogenetic analyses including a large number of sequences deposited in the GenBank, we encountered a full-length HCV sequence (AY651061) that showed evidence for inter-subtype recombination and was, therefore, subjected to a detailed analysis of its molecular structure. The obtained results indicated that AY651061 does not represent a “simple” HCV 1c isolate, but a complex 1a/1c mosaic genome, showing five putative breakpoints in the core to NS3 regions. To our knowledge, this is the first report on a mosaic HCV full-length sequence with multiple breakpoints. The molecular structure of AY651061 is reminiscent of complex homologous recombinant variants occurring among other members of the flaviviridae family, e.g. GB virus C, dengue virus, and Japanese encephalitis virus. Our finding of a mosaic HCV sequence may have important implications for many fields of current HCV research which merit careful consideration.
A Mixture Model and a Hidden Markov Model to Simultaneously Detect Recombination Breakpoints and Reconstruct phylogenies
Authors: Boussau Bastien , Guéguen Laurent , Gouy Manolo
Published: November 2017

Homologous recombination is a pervasive biological process that affects sequences in all living organisms and viruses. In the presence of recombination, the evolutionary history of an alignment of homologous sequences cannot be properly depicted by a single bifurcating tree: some sites have evolved along a specific phylogenetic tree, others have followed another path. Methods available to analyse recombination in sequences usually involve an analysis of the alignment through sliding-windows, or are particularly demanding in computational resources, and are often limited to nucleotide sequences. In this article, we propose and implement a Mixture Model on trees and a phylogenetic Hidden Markov Model to reveal recombination breakpoints while searching for the various evolutionary histories that are present in an alignment known to have undergone homologous recombination. These models are sufficiently efficient to be applied to dozens of sequences on a single desktop computer, and can handle equivalently nucleotide or protein sequences. We estimate their accuracy on simulated sequences and test them on real data.
REFGEN and TREENAMER: Automated Sequence Data Handling for Phylogenetic Analysis in the Genomic Era
Authors: Leonard Guy , Stevens Jamie R. , Richards Thomas A.
Published: November 2017

The phylogenetic analysis of nucleotide sequences and increasingly that of amino acid sequences is used to address a number of biological questions. Access to extensive datasets, including numerous genome projects, means that standard phylogenetic analyses can include many hundreds of sequences. Unfortunately, most phylogenetic analysis programs do not tolerate the sequence naming conventions of genome databases. Managing large numbers of sequences and standardizing sequence labels for use in phylogenetic analysis programs can be a time consuming and laborious task. Here we report the availability of an online resource for the management of gene sequences recovered from public access genome databases such as GenBank. These web utilities include the facility for renaming every sequence in a FASTA alignment file, with each sequence label derived from a user-defined combination of the species name and/or database accession number. This facility enables the user to keep track of the branching order of the sequences/taxa during multiple tree calculations and re-optimisations. Post phylogenetic analysis, these webpages can then be used to rename every label in the subsequent tree files (with a user-defined combination of species name and/or database accession number). Together these programs drastically reduce the time required for managing sequence alignments and labelling phylogenetic figures. Additional features of our platform include the automatic removal of identical accession numbers (recorded in the report file) and generation of species and accession number lists for use in supplementary materials or figure legends.
On the Use of Bootstrapped Topologies in Coalescent-Based Bayesian MCMC Inference: A Comparison of Estimation and Computational Efficiencies
Authors: Rodrigo Allen G. , Tsai Peter , Shearman Helen
Published: November 2017

Coalescent-based Bayesian Markov chain Monte Carlo (MCMC) inference generates estimates of evolutionary parameters and their posterior probability distributions. As the number of sequences increases, the length of time taken to complete an MCMC analysis increases as well. Here, we investigate an approach to distribute the MCMC analysis across a cluster of computers. To do this, we use bootstrapped topologies as fixed genealogies, perform a single MCMC analysis on each genealogy without topological rearrangements, and pool the results across all MCMC analyses. We show, through simulations, that although the standard MCMC performs better than the bootstrap-MCMC at estimating the effective population size (scaled by mutation rate), the bootstrap-MCMC returns better estimates of growth rates. Additionally, we find that our bootstrap-MCMC analyses are, on average, 37 times faster for equivalent effective sample sizes.
A Comprehensive Analysis of Gene Expression Evolution between Humans and Mice
Authors: Wang Yupeng , Rekaya Romdhane
Published: November 2017

Evolutionary changes in gene expression account for most phenotypic differences between species. Advances in microarray technology have made the systematic study of gene expression evolution possible. In this study, gene expression patterns were compared between human and mouse genomes using two published methods. Specifically, we studied how gene expression evolution was related to GO terms and tried to decode the relationship between promoter evolution and gene expression evolution. The results showed that (1) the significant enrichment of biological processes in orthologs of expression conservation reveals functional significance of gene expression conservation. The more conserved gene expression in some biological processes than is expected in a purely neutral model reveals negative selection on gene expression. However, fast evolving genes mainly support the neutrality of gene expression evolution, and (2) gene expression conservation is positively but only slightly correlated with promoter conservation based on a motif-count score of the promoter alignment. Our results suggest a neutral model with negative selection for gene expression evolution between humans and mice, and promoter evolution could have some effects on gene expression evolution.
Reverse Conservation Analysis Reveals the Specificity Determining Residues of Cytochrome P450 Family 2 (CYP 2)
Authors: Lee Tai-Sung
Published: November 2017

The concept of conservation of amino acids is widely used to identify important alignment positions of orthologs. The assumption is that important amino acid residues will be conserved in the protein family during the evolutionary process. For paralog alignment, on the other hand, the opposite concept can be used to identify residues that are responsible for specificity. Assuming that the function-specific or ligand-specific residue positions will have higher diversity since they are under evolutionary pressure to fit the target specificity, these function-specific or ligand-specific residues positions will have a lower degree of conservation than other positions in a highly conserved paralog alignment. This study assessed the ability of reverse conservation analysis to identify function-specific and ligand-specific residue positions in closely related paralog.

Reverse conservation analysis of paralog alignments successfully identified all six previously reported substrate recognition sites (SRSs) in cytochrome P450 family 2 (CYP 2). Further analysis of each subfamily identified the specificity-determining residues (SDRs) that have been experimentally found. New potential SDRs were also predicted and await confirmation by further experiments or modeling calculations. This concept may be also applied to identify SDRs in other protein families.
A Model for Protein Sequence Evolution Based on Selective Pressure for Protein Stability: Application to Hemoglobins
Authors: Marsh Lorraine
Published: November 2017

Negative selection against protein instability is a central influence on evolution of proteins. Protein stability is maintained over evolution despite changes in underlying sequences. An empirical all-site stability-based model of evolution was developed to focus on the selection of residues arising from their contributions to protein stability. In this model, site rates could vary. A structure-based method was used to predict stationary frequencies of hemoglobin residues based on their propensity to promote protein stability at a site. Sites with destabilizing residues were shown to change more rapidly in hemoglobins than sites with stabilizing residues. For diverse proteins the results were consistent with stability-based selection. Maximum likelihood studies with hemoglobins supported the stability-based model over simple Poisson-based methods. These observations are consistent with suggestions that purifying selection to maintain protein structural stability plays a dominant role in protein evolution.
Clustering Protein Sequences Using Affinity Propagation Based on an Improved Similarity Measure
Authors: Yang Fan , Zhu Qing-Xin , Tang Dong-Ming , Zhao Ming-Yuan
Published: November 2017

The sizes of the protein databases are growing rapidly nowadays, thus it becomes increasingly important to cluster protein sequences only based on sequence information. In this paper we improve the similarity measure proposed by Kelil et al, then cluster sequences using the Affinity propagation (AP) algorithm and provide a method to decide the input preference of AP algorithm. We tested our method extensively and compared its performance with other four methods on several datasets of COG, G protein, CAZy, SCOP database. We consistently observed that, the number of clusters that we obtained for a given set of proteins approximate to the correct number of clusters in that set. Moreover, in our experiments, the quality of the clusters when quantified by F-measure was better than that of other algorithms (on average, it is 15% better than that of BlastClust, 56% better than that of TribeMCL, 23% better than that of CLUSS, and 42% better than that of Spectral clustering).
Article Commentary: Snapshots of Tree Space
Authors: Wang Zheng , López-Giréidez Francesc , Townsend Jeffrey P.
Published: November 2017

Achievement of the best balance between the accuracy and efficiency is always an important issue when searching a tree space of large data sets. In the 5th issue in 2009, Rodrigo et al used bootstrapped topologies as fixed genealogies to distribute an MCMC analysis across a cluster of computers, resulting in an efficiency yielding results 37 times faster than in the standard MCMC methods. Tree searches can seldom be guided with certainty, so that such snapshots sampling partial but “more-likely” tree space facilitated by parallel programs on computer clusters may provide great promise among a few choices that are computationally affordable when tree space is large and complicated.
Support Vector Machines Trained with Evolutionary Algorithms Employing Kernel Adatron for Large Scale Classification of Protein Structures
Authors: Arana-Daniel Nancy , Gallegos Alberto A. , López-Franco Carlos , Alanís Alma Y. , Morales Jacob , López-Franco Adriana
Published: November 2017

With the increasing power of computers, the amount of data that can be processed in small periods of time has grown exponentially, as has the importance of classifying large-scale data efficiently. Support vector machines have shown good results classifying large amounts of high-dimensional data, such as data generated by protein structure prediction, spam recognition, medical diagnosis, optical character recognition and text classiffication, etc. Most state of the art approaches for large-scale learning use traditional optimization methods, such as quadratic programming or gradient descent, which makes the use of evolutionary algorithms for training support vector machines an area to be explored. The present paper proposes an approach that is simple to implement based on evolutionary algorithms and Kernel-Adatron for solving large-scale classiffication problems, focusing on protein structure prediction. The functional properties of proteins depend upon their three-dimensional structures. Knowing the structures of proteins is crucial for biology and can lead to improvements in areas such as medicine, agriculture and biofuels.
How to Summarize Estimates of Ancestral Divergence Times
Authors: Morrison David A.
Published: November 2017

The use of molecular sequence data has increased interest in trying to date evolutionary events, with researchers wanting both an estimate of the divergence time and a confidence interval for that estimate. However, two methodological issues have recently been raised with respect to precision of the estimates: (i) the time of the ancestral event is over-estimated; and (ii) the confidence interval is asymmetrical. I argue that if the estimates of divergence time are considered to be samples from a lognormal probability distribution, then this would explain both of these problems. This implies that divergence times should be presented using geometric means rather than arithmetic means, both for estimates and for their confidence intervals. I present analyses based on both computer simulations and empirical data to show that this approach is effective for both single-gene and multiple-gene data sets. Treating divergence time as a lognormal variable thus provides a simple unifying framework for dealing with many of the problems associated with the estimation of divergence (and possibly coalescence) times. Use of this approach (based on geometric means) can, unfortunately, lead to very different biological conclusions compared to the currently used calculation methods (based on arithmetic means).
Expected Anomalies in the Fossil Record
Authors: Fischer Mareike , Steel Mike
Published: November 2017

The problem of intermediates in the fossil record has been frequently discussed ever since Darwin. The extent of ‘gaps’ (missing transitional stages) has been used to argue against gradual evolution from a common ancestor. Traditionally, gaps have often been explained by the improbability of fossilization and the discontinuous selection of found fossils. Here we take an analytical approach and demonstrate why, under certain sampling conditions, we may not expect intermediates to be found. Using a simple null model, we show mathematically that the question of whether a taxon sampled from some time in the past is likely to be morphologically intermediate to other samples (dated earlier and later) depends on the shape and dimensions of the underlying phylogenetic tree that connects the taxa, and the times from which the fossils are sampled.
Comparative Evolutionary Histories of the Fungal Chitinase Gene Family Reveal Non-Random Size Expansions and Contractions due to Adaptive Natural Selection
Authors: Karlsson Magnus , Stenlid Jan
Published: November 2017

Gene duplication and loss play an important role in the evolution of novel functions and for shaping an organism's gene content. Recently, it was suggested that stress-related genes frequently are exposed to duplications and losses, while growth-related genes show selection against change in copy number. The fungal chitinase gene family constitutes an interesting case study of gene duplication and loss, as their biological roles include growth and development as well as more stress-responsive functions. We used genome sequence data to analyze the size of the chitinase gene family in different fungal taxa, which range from 1 in Batrachochytrium dendrobatidis and Schizosaccharomyces pombe to 20 in Hypocrea jecorina and Emericella nidulans, and to infer their phylogenetic relationships. Novel chitinase subgroups are identified and their phylogenetic relationships with previously known chitinases are discussed. We also employ a stochastic birth and death model to show that the fungal chitinase gene family indeed evolves non-randomly, and we identify six fungal lineages where larger-than-expected expansions (Pezizomycotina, H. jecorina, Gibberella zeae, Uncinocarpus reesii, E. nidulans and Rhizopus oryzae), and two contractions ( Coccidioides immitis and S. pombe) potentially indicate the action of adaptive natural selection. The results indicate that antagonistic fungal-fungal interactions are an important process for soil borne ascomycetes, but not for fungal species that are pathogenic in humans. Unicellular growth is correlated with a reduction of chitinase gene copy numbers which emphasizes the requirement of the combined action of several chitinases for filamentous growth.