bluuebunny/crossref_metadata_2025_split huggingface dataset:
Systems Biology Graphical Notation: Activity Flow language Level 1 Version 1.2
Authors: Mi Huaiyu , Schreiber Falk , Moodie Stuart , Czauderna Tobias , Demir Emek , Haw Robin , Luna Augustin , Le Novère Nicolas , Sorokin Anatoly , Villéger Alice 
Published: December 2017

Summary The Systems Biological Graphical Notation (SBGN) is an international community effort for standardized graphical representations of biological pathways and networks. The goal of SBGN is to provide unambiguous pathway and network maps for readers with different scientific backgrounds as well as to support efficient and accurate exchange of biological knowledge between different research communities, industry, and other players in systems biology. Three SBGN languages, Process Description (PD), Entity Relationship (ER) and Activity Flow (AF), allow for the representation of different aspects of biological and biochemical systems at different levels of detail.The SBGN Activity Flow language represents the influences of activities among various entities within a network. Unlike SBGN PD and ER that focus on the entities and their relationships with others, SBGN AF puts the emphasis on the functions (or activities) performed by the entities, and their effects to the functions of the same or other entities. The nodes (elements) describe the biological activities of the entities, such as protein kinase activity, binding activity or receptor activity, which can be easily mapped to Gene Ontology molecular function terms. The edges (connections) provide descriptions of relationships (or influences) between the activities, e.g., positive influence and negative influence. Among all three languages of SBGN, AF is the closest to signaling pathways in biological literature and textbooks, but its well-defined semantics offer a superior precision in expressing biological knowledge.
Multi-agent System for Obtaining Relevant Genes in Expression Analysis between Young and Older Women with Triple Negative Breast Cancer
Authors: González-Briones Alfonso , Ramos Juan , De Paz Juan F. , Corchado Juan M. 
Published: December 2017

Summary Triple negative breast cancer is an aggressive form of breast cancer. Despite treatment with chemotherapy, relapses are frequent and response to these treatments is not the same in younger women as in older women. Therefore, the identification of genes that cause this difference is required. The identification of therapeutic targets is one of the sought after goals to develop new drugs. Within the range of different hybridization techniques, the developed system uses expression array analysis to measure the expression of the signal levels of thousands of genes in a given sample. Probesets of Gene 1.0 ST GeneChip arrays provide categorical genome transcript coverage, providing a measurement of the expression level of the sample. This paper proposes a multi-agent system to manage information of expression arrays, with the goal of providing an intuitive system that is also extensible to analyze and interpret the results. The roles of agent integrate different types of techniques, statistical and data mining methods that select a set of genes, searching techniques that find pathways in which such genes participate, and an information extraction procedure that applies a CBR system to check if these genes are involved in the disease.
UV-visible scanning spectrophotometry and chemometric analysis as tools for carotenoids analysis in cassava genotypes (Manihot esculenta Crantz)
Authors: Moresco Rodolfo , Uarrota Virgílio G. , Pereira Aline , Tomazzoli Maíra , Nunes Eduardo da C. , Martins Peruch Luiz Augusto , Gazzola Jussara , Costa Christopher , Rocha Miguel , Maraschin Marcelo 
Published: December 2017

Summary In this study, the metabolomics characterization focusing on the carotenoid composition of ten cassava (Manihot esculenta) genotypes cultivated in southern Brazil by UV-visible scanning spectrophotometry and reverse phase-high performance liquid chromatography was performed. Cassava roots rich in β-carotene are an important staple food for populations with risk of vitamin A deficiency. Cassava genotypes with high pro-vitamin A activity have been identified as a strategy to reduce the prevalence of deficiency of this vitamin. The data set was used for the construction of a descriptive model by chemometric analysis. The genotypes of yellow-fleshed roots were clustered by the higher concentrations of cis- β-carotene and lutein. Inversely, cream-fleshed roots genotypes were grouped precisely due to their lower concentrations of these pigments, as samples rich in lycopene (redfleshed) differed among the studied genotypes. The analytical approach (UV-Vis, HPLC, and chemometrics) used showed to be efficient for understanding the chemodiversity of cassava genotypes, allowing to classify them according to important features for human health and nutrition.
PetriScape - A plugin for discrete Petri net simulations in Cytoscape
Authors: Almeida Diogo , Azevedo Vasco , Silva Artur , Baumbach Jan 
Published: December 2017

SummarySystems biology plays a central role for biological network analysis in the post-genomic era. Cytoscape is the standard bioinformatics tool offering the community an extensible platform for computational analysis of the emerging cellular network together with experimental omics data sets. However, only few apps/plugins/tools are available for simulating network dynamics in Cytoscape 3. Many approaches of varying complexity exist but none of them have been integrated into Cytoscape as app/plugin yet. Here, we introduce PetriScape, the first Petri net simulator for Cytoscape. Although discrete Petri nets are quite simplistic models, they are capable of modeling global network properties and simulating their behaviour. In addition, they are easily understood and well visualizable. PetriScape comes with the following main functionalities: (1) import of biological networks in SBML format, (2) conversion into a Petri net, (3) visualization as Petri net, and (4) simulation and visualization of the token flow in Cytoscape. PetriScape is the first Cytoscape plugin for Petri nets. It allows a straightforward Petri net model creation, simulation and visualization with Cytoscape, providing clues about the activity of key components in biological networks.
Web-based hybrid-dimensional Visualization and Exploration of Cytological Localization Scenarios
Authors: Kovanci Gökhan , Ghaffar Mehmood , Sommer Björn 
Published: December 2017

Summary
The CELLmicrocosmos 4.2 PathwayIntegration (CmPI) is a tool which provides hybriddimensional visualization and analysis of intracellular protein and gene localizations in the context of a virtual 3D environment. This tool is developed based on Java/Java3D/JOGL and provides a standalone application compatible to all relevant operating systems. However, it requires Java and the local installation of the software. Here we present the prototype of an alternative web-based visualization approach, using Three.js and D3.js. In this way it is possible to visualize and explore CmPI-generated localization scenarios including networks mapped to 3D cell components by just providing a URL to a collaboration partner. This publication describes the integration of the different technologies - Three.js, D3.js and PHP - as well as an application case: a localization scenario of the citrate cycle. The CmPI web viewer is available at: http://CmPIweb.CELLmicrocosmos.org.
Clustering of Biological Datasets in the Era of Big Data
Authors: Röttger Richard 
Published: December 2017

SummaryClustering is a long-standing problem in computer science and is applied in virtually any scientific field for exploring the inherent structure of datasets. In biomedical research, clustering tools have been utilized in manifold areas, among many others in expression analysis, disease subtyping or protein research. A plethora of different approaches have been developed but there is only little guideline what approach is the optimal in what particular situation. Furthermore, a typical cluster analysis is an entire process with several highly interconnected steps; from preprocessing, proximity calculation, the actual clustering to evaluation and optimization. Only when all steps seamlessly work together, an optimal result can be achieved. This renders a cluster analyses tiresome and error-prone especially for non-experts. A mere trial-and-error approach renders increasingly infeasible when considering the tremendous growth of available datasets; thus, a strategic and thoughtful course of action is crucial for a cluster analysis. This manuscript provides an overview of the crucial steps and the most common techniques involved in conducting a state-of-the-art cluster analysis of biomedical datasets.
Computational miRNomics
Authors: Allmer Jens , Yousef Malik 
Published: December 2017

EditorialThe term MicroRNA or its contraction miRNA currently appears in 21,215 titles of abstracts, published between 1997 and now, available on Pubmed (2016-21-22:12:59 EET). 4,108 of these were published in 2016 alone which signifies the importance of miRNA-related research. MicroRNAs can be detected experimentally using various techniques like directional cloning of endogenous small RNAs but they are time consuming [1]. Additionally, it is necessary for the miRNA and its mRNA target(s) to be co-expressed to infer a functional relationship which is difficult, if not impossible, to achieve [2]. Since experimental approaches are facing such difficulties, they have been complemented by computational approaches [3] thereby defining the field of computational miRNomics. Due to the rapid development in the discipline, it is important to assess the state-of-the-art. In this special issue, several areas of the field are investigated ranging from pre-miRNA detection via machine learning to application of differential expression analysis in plants. First, Saçar Demirci et al. discuss an approach to virus pre-miRNA detection using machine learning [4]. Such approaches are based on parameterization of miRNAs and Yousef et al. discuss how to select among such features [5]. A different computational perspective is provided by Kotipalli et al. who model the kinetics of miRNA genesis and targeting [6]. To fuel more refined future models for genesis and targeting, it is important to establish miRNA and target expression under varying conditions. Zhang et al. [7] and Kanke et al. [8] discuss two approaches to quantify miRNAs and other non-coding short RNAs. Diler et al., finally, discuss actual biological implications of differentially expressed miRNAs [9]. This special issue on computational miRNomics, thus, provides a trajectory from detection of pre-miRNAs to biological implications of differentially expressed miRNAs. Additional topics will be covered in the upcoming second volume of the special issue on computational miRNomics.
Ensemble Clustering Classification Applied to Competing SVM and One-Class Classifiers Exemplified by Plant MicroRNAs Data
Authors: Yousef Malik , Khalifa Waleed , AbdAllah Loai 
Published: December 2017

SummaryThe performance of many learning and data mining algorithms depends critically on suitable metrics to assess efficiency over the input space. Learning a suitable metric from examples may, therefore, be the key to successful application of these algorithms. We have demonstrated that the k-nearest neighbor (kNN) classification can be significantly improved by learning a distance metric from labeled examples. The clustering ensemble is used to define the distance between points in respect to how they co-cluster. This distance is then used within the framework of the kNN algorithm to define a classifier named ensemble clustering kNN classifier (EC-kNN). In many instances in our experiments we achieved highest accuracy while SVM failed to perform as well. In this study, we compare the performance of a two-class classifier using EC-kNN with different one-class and two-class classifiers. The comparison was applied to seven different plant microRNA species considering eight feature selection methods. In this study, the averaged results show that EC-kNN outperforms all other methods employed here and previously published results for the same data. In conclusion, this study shows that the chosen classifier shows high performance when the distance metric is carefully chosen.
Differential Expression of Hyperhydricity Responsive Peach MicroRNAs
Authors: Diler Ebru , Unver Turgay , Karakülah Gökhan 
Published: December 2017

SummaryHyperhydricity is a syndrome that causes morpho-physiological malformations in tissue culture plantlets. Micro-RNAs (miRNA) are small non-coding RNAs that play important regulatory roles in plant development, stress response, and adaptation to environmental conditions. In this study, differential expression analysis indicated that miRNAs play an underlying role in the responses to the hyperhydricity syndrome in peach Prunus persica (L.) leaves. 24 known and three novel potential miRNAs were characterized in hyperhydric and non-hyperhydric transcriptome libraries. The miRNA-target transcript analyses indicated that transport, plant cuticle development, intracellular part, and stress response are regulated by miRNAs in hyperhydric leaves. It is also suggested that miR5021 and miRnovel2 might play critical regulatory roles in hyperhydricity regarding miRNA-based response to stress. This study went one step further to advance understanding of molecular miRNA-based regulatory mechanisms regarding responses to hyperhydricity in peach.
Diversity Challenges and Organizational Cynicism: A study on Egyptian Physicians
Authors: Mousa Mohamed 
Published: December 2017

AbstractAs a result of globalization and interactions of people with various identities, cultural diversity has become a noticeable norm in today’s business life. Accordingly, managing such cultural diversity requires a dependence on a much more tolerant culture in which employees seek to attain both career and organizational objectives without being hurdled by irrelevant factors of religion, race, ethnicity and so on. During the last two decades, organizational cynicism has found a place in academic management literature. It has a vital role in interpreting many organizational unwanted behaviors such as: absenteeism, day dreaming and the state of being careless when doing work. This study investigates the association between cultural diversity challenges and organizational cynicism dimensions by conducting a quantitative study of physicians in Kasr El Eini public hospital in Egypt. Upon using correlation and regression analysis for the collected data, it appears that not all cultural diversity challenges have a negative impact on organizational cynicism dimensions.
Nonautonomous partial functional differential equations; existence and regularity
Authors: Kpoumiè Moussa El-Khalil , Ezzinbi Khalil , Békollè David 
Published: December 2017

Abstract
The aim of this work is to establish several results on the existence and regularity of solutions for some nondensely nonautonomous partial functional differential equations with finite delay in a Banach space. We assume that the linear part is not necessarily densely defined and generates an evolution family under the conditions introduced by N. Tanaka.We show the local existence of the mild solutions which may blow up at the finite time. Secondly,we give sufficient conditions ensuring the existence of the strict solutions. Finally, we consider a reaction diffusion equation with delay to illustrate the obtained results.
Programmable optical processor chips: toward photonic RF filters with DSP-level flexibility and MHz-band selectivity
Authors: Xie Yiwei , Geng Zihan , Zhuang Leimeng , Burla Maurizio , Taddei Caterina , Hoekman Marcel , Leinse Arne , Roeloffzen Chris G.H. , Boller Klaus-J. , Lowery Arthur J. 
Published: December 2017

AbstractIntegrated optical signal processors have been identified as a powerful engine for optical processing of microwave signals. They enable wideband and stable signal processing operations on miniaturized chips with ultimate control precision. As a promising application, such processors enables photonic implementations of reconfigurable radio frequency (RF) filters with wide design flexibility, large bandwidth, and high-frequency selectivity. This is a key technology for photonic-assisted RF front ends that opens a path to overcoming the bandwidth limitation of current digital electronics. Here, the recent progress of integrated optical signal processors for implementing such RF filters is reviewed. We highlight the use of a low-loss, high-index-contrast stoichiometric silicon nitride waveguide which promises to serve as a practical material platform for realizing high-performance optical signal processors and points toward photonic RF filters with digital signal processing (DSP)-level flexibility, hundreds-GHz bandwidth, MHz-band frequency selectivity, and full system integration on a chip scale.
Optofluidics for handling and analysis of single living cells
Authors: Perozziello Gerardo , Candeloro Patrizio , Coluccio Maria Laura , Di Fabrizio Enzo 
Published: December 2017

AbstractOptofluidics is a field with important applications in areas such as biotechnology, chemical synthesis and analytical chemistry. Optofluidic devices combine optical elements into microfluidic devices in ways that increase portability and sensitivity of analysis for diagnostic or screening purposes .In fact in these devices fluids give fine adaptability, mobility and accessibility to nanoscale photonic devices which otherwise could not be realized using conventional devices. This review describes several cases inwhich optical or microfluidic approaches are used to trap single cells in proximity of integrated optical sensor for being analysed.
Selected health behaviours in professionally active men and women
Authors: Chuchra Maria , Gorbaniuk Julia 
Published: December 2017

Abstract

Introduction. Women suffer from health problems more often and for a longer time, however it is generally men who die earlier.

Aim. The aim of this work is to compare the selected health behaviours of working men and women.

Material and methods. The research included 100 men and 100 women. The respondents were tested with the matched pair-selection method, taking into consideration four variables: place of residence, level of education, marital status, and age. The survey questionnaire was used.

Results. Men and women show similarities with respect to some health behaviours, showing significant differences (amount and kind of alcoholic beverages drunk, regularity of preventive checks) in relation to others.

Conclusions. Women’s health behaviours are to be evaluated more positively than men’s. Both men and women require intensive educational activities concerning the effects of anti-health behaviours, especially bad eating habits and irregularity of preventive checks.
Progress in the research and applications of natural fiber-reinforced polymer matrix composites
Authors: Sun Zhanying 
Published: December 2017

Abstract
The natural and fiber-reinforced resin matrix composites have been increasingly and widely applied in society in order to improve the environment and promote sustainable development. In the first part of this article, the major foci of recent research on natural fiber composites are reviewed in detail, including fiber surface treatment, fiber agglomeration and dispersion, interfacial transcrystallinity, impact strength, foaming technique, inflaming retardance, biodegradable resin matrix and nanofiber reinforcement techniques. The fiber surface treatment and fiber dispersion are important factors in improving the mechanical properties of the natural fiber composites. The interfacial transcrystallinity can be generated on natural fibers owing to the rough surfaces. The natural fiber composites have a low impact strength. In order to reduce the density and improve the flame retardant effect of the composites, both the foaming technique and flame-retardant technology are studied in detail. The biodegradable resin matrix and natural fibers can be mixed to prepare fully-degradable composite materials. Using the natural nano fiber reinforcements in reinforcing resins is another important research area. In the second part of this article, the applications of these composites are summarized systematically, especially those involving the automotive industry, household appliances, construction materials, packaging materials and boards of musical instruments. Currently, the automotive industry and the production of construction materials are the most important application areas of these composites.
“What is essential is invisible to the eye”
Authors: Mayr Beate , Frick Eckhard , Hvidt Niels Christian , Breidenbach Thomas , Erbe Nicole , Seidel Dorothee , Paal Piret 
Published: December 2017

Abstract
Organ donation and transplantation (ODT) is a complex multi-professional clinical procedure. Healthcare professionals’ attitudes and concerns towards the procedure influence the entire process. A 3-hour interview with ODT staff (13 participants) was performed in order to explore ODT professionals’ spiritual attitudes and concerns. The interview was recorded and transcribed verbatim. All (sub)themes were directly derived from the data. The discussants expressed the following issues: (1) ethical considerations and barriers in ODT; (2) individual beliefs about death and afterlife; (3) dealings with patients, relatives and close ones; (4) lack of support for ODT staff; and (5) spiritual facilitators. The interview provided a list of themes that either explicitly or implicitly demonstrate spiritual attitudes and concerns which may influence procedures in ODT. The themes and subthemes formed the basis to design a questionnaire in order to initiate a more detailed investigation of a larger group of professionals.
A New Application of Beta Gompertz Distribution in Reliability
Authors: Hassan M. KH. 
Published: December 2017

Abstract
In this paper, we considered the problem of the estimation R = P(Y &lt; X) that was defined as a life of a component, and which has strength X and is subjected to stress Y. We derive R = P(Y &lt; X) when X and Y are independent beta Gompertz random variables. The reliability is estimated using two estimation methods, they were the maximum likelihood and Bayes estimator. A simulation study was used to compare the two different estimators. Real data was used as a practical application of the proposed procedure.