bluuebunny/crossref_metadata_2025_split huggingface dataset:
DISSEQT - DIStribution based modeling of SEQuence space Time dynamics
Authors: Henningsson R. , Moratorio G. , Bordería A.V. , Vignuzzi M. , Fontes M. 
Published: May 2018

AbstractRapidly evolving microbes are a challenge to model because of the volatile, complex and dynamic nature of their populations. We developed the DISSEQT pipeline (DIStribution-based SEQuence space Time dynamics) for analyzing, visualizing and predicting the evolution of heterogeneous biological populations in multidimensional genetic space, suited for population-based modeling of deep sequencing and high-throughput data. DISSEQT is openly available on GitHub (https://github.com/rasmushenningsson/DISSEQT.jl) and Synapse (https://www.synapse.org/#!Synapse:syn11425758), covering the entire workflow from read alignment to visualization of results. DISSEQT is centered around robust dimension and model reduction algorithms for analysis of genotypic data with additional capabilities for including phenotypic features to explore dynamic genotype-phenotype maps. We illustrate its utility and capacity with examples from evolving RNA virus populations, which present on of the highest degrees of population heterogeneity found in nature. Using DISSEQT, we empirically reconstruct the evolutionary trajectories of evolving populations in sequence space and genotype-phenotype fitness landscapes. We show that while sequence space is vastly multidimensional, the relevant genetic space of evolving microbial populations is of intrinsically low dimension. In addition, evolutionary trajectories of these populations can be faithfully monitored to identify the key minority genotypes contributing most to evolution. Finally, we show that empirical fitness landscapes, when reconstructed to include minority variants, can predict phenotype from genotype with high accuracy.
Diagnostic host gene signature to accurately distinguish enteric fever from other febrile diseases
Authors: Blohmke CJ , Muller J , Gibani MM , Dobinson H , Shrestha S , Perinparajah S , Jin C , Hughes H , Blackwell L , Dongol S , Karkey A , Schreiber F , Pickard D , Basnyat B , Dougan G , Baker S , Pollard AJ , Darton TC 
Published: May 2018

ABSTRACTMisdiagnosis of enteric fever is a major global health problem resulting in patient mismanagement, antimicrobial misuse and inaccurate disease burden estimates. Applying a machine-learning algorithm to host gene expression profiles, we identified a diagnostic signature which could accurately distinguish culture-confirmed enteric fever cases from other febrile illnesses (AUROC<95%). Applying this signature to a culture-negative suspected enteric fever cohort in Nepal identified a further 12.6% as likely true cases. Our analysis highlights the power of data-driven approaches to identify host-response patterns for the diagnosis of febrile illnesses. Expression signatures were validated using qPCR highlighting their utility as PCR-based diagnostic for use in endemic settings.
Prediction and inference diverge in biomedicine: Simulations and real-world data
Authors: Bzdok Danilo , Engemann Denis , Grisel Olivier , Varoquaux Gaël , Thirion Bertrand 
Published: May 2018

AbstractIn the 20thcentury many advances in biological knowledge and evidence-based medicine were supported by p-values and accompanying methods. In the beginning 21stcentury, ambitions towards precision medicine put a premium on detailed predictions for single individuals. The shift causes tension between traditional methods used to infer statistically significant group differences and burgeoning machine-learning tools suited to forecast an individual’s future. This comparison applies the linear model for identifyingsignificantcontributing variables and for finding the mostpredictivevariable sets. In systematic data simulations and common medical datasets, we explored how statistical inference and pattern recognition can agree and diverge. Across analysis scenarios, even small predictive performances typically coincided with finding underlying significant statistical relationships. However, even statistically strong findings with very low p-values shed little light on their value for achieving accurate prediction in the same dataset. More complete understanding of different ways to define ‘important’ associations is a prerequisite for reproducible research findings that can serve to personalize clinical care.
A data mining paradigm for identifying key factors in biological processes using gene expression data
Authors: Li Jin , Zheng Le , Uchiyama Akihiko , Bin Lianghua , Mauro Theodora M. , Elias Peter M. , Pawelczyk Tadeusz , Sakowicz-Burkiewicz Monika , Trzeciak Magdalena , Leung Donald Y. M. , Morasso Maria I. , Yu Peng 
Published: May 2018

AbstractA large volume of biological data is being generated for studying mechanisms of various biological processes. These precious data enable large-scale computational analyses to gain biological insights. However, it remains a challenge to mine the data efficiently for knowledge discovery. The heterogeneity of these data makes it difficult to consistently integrate them, slowing down the process of biological discovery. We introduce a data processing paradigm to identify key factors in biological processes via systematic collection of gene expression datasets, primary analysis of data, and evaluation of consistent signals. To demonstrate its effectiveness, our paradigm was applied to epidermal development and identified many genes that play a potential role in this process. Besides the known epidermal development genes, a substantial proportion of the identified genes are still not supported by gain- or loss-of-function studies, yielding many novel genes for future studies. Among them, we selected a top gene for loss-of-function experimental validation and confirmed its function in epidermal differentiation, proving the ability of this paradigm to identify new factors in biological processes. In addition, this paradigm revealed many key genes in cold-induced thermogenesis using data from cold-challenged tissues, demonstrating its generalizability. This paradigm can lead to fruitful results for studying molecular mechanisms in an era of explosive accumulation of publicly available biological data.
Exercise-related genes analysis of Mongolian Horse
Authors: Pan Jing , Purev Chimge , Zhao Hongwei , Zhang Zhipeng , Wang Feng , Wendoule Nashun , Qi Guichun , Zhou Huanmin 
Published: May 2018

ABSTRACTThe Mongolian horses, as a neglected scientific resource, have excellent endurance and stress resistance to adapt to the cold and harsh plateau conditions. Intraspecific genetic diversity is mainly embodied in various genetic advantages of different branches of Mongolian horse. Abaga horse is better than Wushen horse in running speed, for example. Because people pay progressively attention to the athletic performance of horse, such as horse racing in Mongolia’s Naadam festival, we expect to guide the exercise-oriented breeding of horses through genomics research. We obtained the clean data of 630,535,376,400 bp through the entire genome second-generation sequencing for the whole blood of 4 Abaga horses and 10 Wushen horses. Based on the data analysis of single nucleotide polymorphism (SNP), we severally detected that 479 and 943 positively selected genes, particularly exercise-related, were mainly enriched on equine chromosome 4 in Abaga horses and Wushen horses, which implied that the chromosome 4 may be associated with the evolution of the Mongolian horse and athletic performance. Four hundred and forty genes of positive selection were enriched in 12 exercise-related pathways and narrowed in 21 exercise-related genes in Abaga horse, which were distinguished from Wushen horse. So, we speculated that the Abaga horse may have oriented genes for the motorial mechanism and 21 exercise-related genes also provided molecular genetic basis for exercise-directed breeding of Mongolian horse.
phastWeb: a web interface for evolutionary conservation scoring of multiple sequence alignments using phastCons and phyloP
Authors: Ramani Ritika , Krumholz Katie , Huang Yifei , Siepel Adam 
Published: May 2018

ABSTRACTThe Phylogenetic Analysis with Space/Time models (PHAST) package is a widely used software package for comparative genomics that has been freely available for download since 2002. Here we introduce a web interface (phastWeb) that makes it possible to use two of the most popular programs in PHAST, phastCons and phyloP, without downloading and installing the PHAST software. This interface allows users to upload a sequence alignment and either upload a corresponding phylogeny or have one estimated from the alignment. After processing, users can visualize alignments and conservation scores as genome browser tracks, and download estimated tree models and raw scores for further analysis. Altogether, this resource makes key features of the PHAST package conveniently available to a broad audience.AVAILABILITYphastWeb is freely available on the web at http://compgen.cshl.edu/phastweb/. The website provides instructions as well as examples.CONTACTphasthelp@cshl.edu
Inference and visualization of DNA damage patterns using a grade of membership model
Authors: Al-Asadi Hussein , Dey Kushal K , Novembre John , Stephens Matthew 
Published: May 2018

AbstractQuality control plays a major role in the analysis of ancient DNA (aDNA). One key step in this quality control is assessment of DNA damage: aDNA contains unique signatures of DNA damage that distinguish it from modern DNA, and so analyses of damage patterns can help confirm that DNA sequences obtained are from endogenous aDNA rather than from modern contamination. Predominant signatures of DNA damage include a high frequency of cytosine to thymine substitutions (C-to-T) at the ends of fragments, and elevated rates of purines (A & G) before the 5’ strand-breaks. Existing QC procedures help assess damage by simply plotting for each sample, the C-to-T mismatch rate along the read and the composition of bases before the 5’ strand-breaks. Here we present a more flexible and comprehensive model-based approach to infer and visualize damage patterns in aDNA, implemented in an R package aRchaic. This approach is based on a “grade of membership” model (also known as “admixture” or “topic” model) in which each sample has an estimated grade of membership in each of K damage profiles that are estimated from the data. We illustrate aRchaic on data from several aDNA studies and modern individuals from 1000 Genomes Project Consortium (2012). Here, aRchaic clearly distinguishes modern from ancient samples irrespective of DNA extraction, lab and sequencing protocols. Additionally, through an in-silico contamination experiment, we show that the aRchaic grades of membership reflect relative levels of exogenous modern contamination. Together, the outputs of aRchaic provide a concise visual summary of DNA damage patterns, as well as other processes generating mismatches in the data. Availability: aRchaic is available for download from https://www.github.com/kkdey/aRchaic.Contact: halasadi@uchicago.edu, kkdey@uchicago.edu
Identification of Casiopeina II-gly secondary targets through a systems pharmacology approach
Authors: de Anda-Jáuregui Guillermo , Espinal-Enríquez Jesús , Hur Junguk , Alcalá-Corona Sergio Antonio , Ruiz-Azuara Lena , Hernández-Lemus Enrique 
Published: May 2018

AbstractCasiopeinas are a group of copper-based compounds designed to be used as less toxic, more efficient chemotherapeutic agents. In this study, we analyzed the in vitro effects of Casiopeina Il-gly on the expression of canonical biological pathways. Using microarray data from HeLa cell lines treated with Casiopeina II-gly, we identified biological pathways that are perturbed after treatment. We present a novel approach integrating pathway analysis and network theory: The Pathway Crosstalk Network. We constructed a network with deregulated pathways, featuring links between those pathways that crosstalk with each other. We identified modules grouping deregulated pathways that are functionally related. Through this approach, we were able to identify three features of Casiopeina treatment: a) Perturbation of signaling pathways, related to induction of apoptosis; b) perturbation of metabolic pathways, and c) activation of immune responses. These findings can be useful to drive new experimental exploration on their role in adverse effects and efficacy of Casiopeinas.
Optimization of Tenocyte Lineage-related Factors from Tonsil-derived Mesenchymal Stem Cells using Response Surface Methodology
Authors: Lee Seung Yeol , Kim Hyang , Shin Sang-Jin , Kwon Soon-Sun 
Published: May 2018

AbstractResearchers should consider various potential factors that affect tenogenic differentiation of mesenchymal stem cells (MSCs); however, this requires numerous experimental settings, which are associated with high cost and time. We aimed to assess the differential effects of transforming growth factor beta 3 (TGF-β3) on the tenogenesis of tonsil-derived MSCs (T-MSCs) and bone marrow-derived MSCs (BM-MSCs) using design of experiments (DoE). Bone marrow and tonsillar tissue was collected from four patients; mononuclear cells were separated and treated with 5 and 10 ng/mL of TGF-β3 with vehicle control. A full-factorial experimental design with a categorical factor of 0 was employed to study the effect of tension based on T-MSCs. Eighty-four trials were utilized, fitted with RSM, and then used to obtain mathematical prediction models. Exposure of T-MSCs and BM-MSCs to TGF-β3 increased the expression of scleraxis (SCX), tenomodulin (TNMD), decorin, collagen I, and tenascin C. Expression of most of these factors reached a maxima after 2–3 days of treatment. Considering all of the tenocyte lineage-related factors that were assessed, the predicted value of the factors from T-MSCs was significantly induced at 2.7 ng/mL of TGF-β3 during 2.5-day culture, whereas the predicted value of the factors from BM-MSCs was significantly induced during 2.3-day culture, regardless of TGF-β3 concentration. This study demonstrated that tenogenic differentiation of T-MSCs and BM-MSCs under TGF-β3 stimulation showed a similar culture time for peak expression of tenocyte-related mRNAs using RSM. This study suggests the potential of using the DoE approach for optimization of the culture protocol for tenogenesis of MSCs.
First report and multilocus genotyping of Enterocytozoon bieneusi from Tibetan pigs in southwestern China
Authors: Luo Run , Xiang Leiqiong , Liu Haifeng , Zhong Zhijun , Liu Li , Deng Lei , Song Yuan , Liu Ling , Huang Xiangming , Zhou Ziyao , Fu Hualin , Luo Yan , Peng Guangneng 
Published: May 2018

AbstractEnterocytozoon bieneusi is a common intestinal pathogen and a major cause of diarrhea and enteric diseases in a variety of animals. While the E. bieneusi genotype has become better-known, there are few reports on its prevalence in the Tibetan pig. This study investigated the prevalence, genetic diversity, and zoonotic potential of E. bieneusi in the Tibetan pig in southwestern China. Tibetan pig feces (266 samples) were collected from three sites in the southwest of China. Feces were subjected to PCR amplification of the internal transcribed spacer (ITS) region. E. bieneusi was detected in 83 (31.2%) of Tibetan pigs from the three different sites, with 25.4% in Kangding, 56% in Yaan and 26.7% in Qionglai. Age group demonstrated the prevalence of E. bieneusi range from 24.4%(aged 0 to 1 years) to 44.4%(aged 1 to 2 years). Four genotypes of E. bieneusi were identified: two known genotypes EbpC (n=58), Henan-IV (n=24) and two novel genotypes, SCT01 and SCT02 (one of each). Phylogenetic analysis showed these four genotypes clustered to group 1 with zoonotic potential. Multilocus sequence typing (MLST) analysis three microsatellites (MS1, MS3, MS7) and one minisatellite (MS4) revealed 47, 48, 23 and 47 positive specimens were successfully sequenced, and identified ten, ten, five and five genotypes at four loci, respectively. This study indicates the potential danger of E. bieneusi to Tibetan pigs in southwestern China, and offers basic data for preventing and controlling infections.
Impact of disclosure of risk factors on the initial returns of initial public offerings (IPOs)
Authors: Wasiuzzaman Shaista , Yong Fook Lye Kevin , Sundarasen Sheela Devi D. , Othman Noor Shahaliza 
Published: May 2018

Purpose
When a firm goes public for the first time, its prospectus serves as an important reference for investors. It is required by regulation that the risk factors which have significant influence on the business be disclosed in the prospectus. The purpose of this study is to analyze how disclosure of these risk factors influences the initial returns of initial public offerings (IPOs).

Design/methodology/approach
To do this, a sample of 96 Malaysian new equity offerings (IPOs) from year 2009 to year 2013 is used. Ordinary least squares regression technique is used to regress initial returns against risk disclosures. Aside from overall risk disclosure, individual dimensions of risk (internal risk, external risk and investment risk) are also considered.

Findings
Results of the regression analyses reveal a direct relationship between the IPO initial returns and the disclosure of risk. Overall risk disclosure is found to be highly significant in influencing initial returns. However, further investigation into the individual group of risks shows that only investment risk is highly significant in influencing IPO initial returns.

Originality/value
The results found in this study are interesting as, unlike prior studies, it is shown that disclosures of internal and external risks are not significant in influencing investors’ actions possibly because of their generalizability, whereas disclosures related to investment risks are significant. Equity of firms which disclose more of its risk factors can be expected to generate higher initial returns.
Positive or negative?
Authors: Wei Wanqing , Gao Wei 
Published: May 2018

Purpose
In China, rural-to-urban migrant workers who are from the same place of origin tend to concentrate in the same workplace. If the concentration is sufficiently dense, it means that these migrant workers build up a social network which could be defined as native place enclave (NPE). In this paper, the authors discussed whether there are behavioral differences between enclave workers and non-enclave workers when they have conflicts with their employers.

Design/methodology/approach
The authors put two questions to empirical tests. First, do enclave workers experience less sense of deprivation than non-enclave workers? Second, compared to non-enclave workers, are enclave workers more willing to participate in collective action against their employers? Using data from a survey of migrant workers in Pearl River Delta and Yangzi River Delta in 2010, the authors made a comparison between enclave workers and non-enclave workers with respect to sense of deprivation and willingness-to-participate by using a propensity score matching method.

Findings
The authors found that the relationship between NPE and sense of deprivation was negative, so was the relationship between NPE and willingness-to-participate. Meanwhile, the two relationships were stronger than what had been found after the propensity score matching method was used.

Practical implications
The results implied that employers can reduce labor conflicts by using NPE to mitigate migrant workers’ sense of deprivation and by lowering the risk of their collective actions. In this way, NPE may contribute to the upkeep of workplace order and even social order.

Originality/value
There have been hot debates on how NPE would affect migrant workers’ collective action. Resource mobilization theory pointed out that NPE was positively related to workers’ collective action while production politics theory held an opposite view. Our findings provided empirical evidences for the debates.
Investigating TPCK through music focusing on affect
Authors: Macrides Elena , Angeli Charoula 
Published: May 2018

PurposeThe purpose of this paper is to address the lack of a theoretical framework for the integration of technology in music teaching and learning, and explores, within the framework of Technological Pedagogical Content Knowledge (TPCK or TPACK), the importance of affect in instructional design.Design/methodology/approachThe authors reviewed relevant literature related to the fields of music education, instructional design, and technology integration. Accordingly, they developed guidelines for designing technology-enhanced learning for the activities of music composition and listening.FindingsThe authors propose a set of design principles based on the TPCK framework through the subject matter of music focusing on the affective domain, and identify interrelations among musical content, emotions, and technology. The design guidelines were tested in an empirical investigation and the results showed statistically significant differences between the control and the experimental groups in favor of the experimental group.Research limitations/implicationsFurther investigation is necessary to test the effectiveness of the proposed design principles. Including affect in the design process is a complicated and mostly unchartered area, and, thus, further research toward this direction is fully justified.Practical implicationsThe research has practical significance, addressing a gap in the field of music education, as it provides teachers with explicit guidance about how to design music lessons with technology while incorporating affect.Originality/valueThe study extends the theoretical framework of TPCK to a design framework and proposes instructional design guidelines that address both the cognitive and the affective domains of learning, a focus that is currently missing from the existing TPCK or TPACK literature as well as the music education literature.
Multi-actor innovation in the music industry: a state of the art review
Authors: Saragih Harriman Samuel , Simatupang Togar Mangihut , Sunitiyoso Yos 
Published: May 2018

PurposeThis study aims to present a state-of-the-art review pertaining to the topic of multi-actor innovation in the music industry. Because of the changing nature of the marketing paradigm from product dominant to service dominant, as well as the emerging paradigm of open, collaborative and co-innovation, this study attempts to integrate and map the previous papers that have examined the concept of multi-actor innovation in the context of the music industry.Design/methodology/approachA systematic review is carried out to produce the analysis. Various scholarly articles from well-known databases are taken into considerations in this study. These papers are then classified based on the types of innovation, category and sub-category of innovation, value capture and value creation, as well as its general characteristics. This classification is primarily aimed at mapping the development of previous studies in the current field and examining the current research gaps to propose future research agendas.FindingsPrevious researchers have shown that innovation concepts have been developed into various streams, namely, closed, open, collaborative and co-innovation. In addition to this point, the debates regarding the consumers’ roles in the market have pinpointed that innovation also calls for more participative forms rather than isolated. Nevertheless, discussions that pertain to open, collaborative and co-innovation in the context of the music business, have still been lacking and, therefore, demand more explanations.Originality/valueThis study is the first to present the topic of multi-actor innovation in the music business to the scholarly literature. Based on the review carried out in this study, scholars that are particularly interested in the field of open, collaborative and co-innovation within the context of the music industry can comprehend the development of previous discussions and, therefore, justify future research agendas.