bluuebunny/crossref_metadata_2025_split huggingface dataset:
Linking FANTOM5 CAGE peaks to annotations with CAGEscan
Authors: Bertin Nicolas , Mendez Mickaël , Hasegawa Akira , Lizio Marina , Abugessaisa Imad , Severin Jessica , Sakai-Ohno Mizuho , Lassmann Timo , Kasusawa Takeya , Kawaji Hideya , Hayashizaki Yoshihide , Forrest Alistair R. R. , Carninci Piero , Plessy Charles 
Published: April 2017

AbstractThe FANTOM5 expression atlas is a quantitative measurement of the activity of nearly 200,000 promoter regions across nearly 2,000 different human primary cells, tissue types and cell lines. Generation of this atlas was made possible by the use of CAGE, an experimental approach to localise transcription start sites at single-nucleotide resolution by sequencing the 5′ ends of capped RNAs after their conversion to cDNAs. While 50% of CAGE-defined promoter regions could be confidently associated to adjacent transcriptional units, nearly 100,000 promoter regions remained gene-orphan. To address this, we used the CAGEscan method, in which random-primed 5′-cDNAs are paired-end sequenced. Pairs starting in the same region are assembled in transcript models called CAGEscan clusters. Here, we present the production and quality control of CAGEscan libraries from 56 FANTOM5 RNA sources, which enhances the FANTOM5 expression atlas by providing experimental evidence associating core promoter regions with their cognate transcripts.
BasePlayer: Versatile Analysis Software for Large-scale Genomic Variant Discovery
Authors: Katainen Riku , Donner Iikki , Cajuso Tatiana , Kaasinen Eevi , Palin Kimmo , Mäkinen Veli , Aaltonen Lauri A. , Pitkänen Esa 
Published: April 2017

AbstractNext-generation sequencing (NGS) is being routinely applied in life sciences and clinical practice, where the interpretation of the resulting massive data has become a critical challenge. Computational workflows, such as the Broad GATK, have been established to take raw sequencing data and produce processed data for downstream analyses. Consequently, results of these computationally demanding workflows, consisting of e.g. sequence alignment and variant calling, are increasingly being provided for customers by sequencing and bioinformatics facilities. However, downstream variant analysis, whole-genome level in particular, has been lacking a multi-purpose tool, which could take advantage of rapidly growing genomic information and integrate genetic variant, sequence, genomic annotation and regulatory (e.g. ENCODE) data interactively and in a visual fashion. Here we introduce a highly efficient and user-friendly software, BasePlayer (http://baseplayer.fi), for biological discovery in large-scale NGS data. BasePlayer enables tightly integrated comparative variant analysis and visualization of thousands of NGS data samples and millions of variants, with numerous applications in disease, regulatory and population genomics. Although BasePlayer has been designed primarily for whole-genome and exome sequencing data, it is well-suited to various study settings, diseases and organisms by supporting standard and upcoming file formats. BasePlayer transforms an ordinary desktop computer into a large-scale genomic research platform, enabling also a non-technical user to perform complex comparative variant analyses, population frequency filtering and genome level annotations under intuitive, scalable and highly-responsive user interface to facilitate everyday genetic research as well as the search of novel discoveries.
Combinatorial regulation of the balance between dynein microtubule end accumulation and initiation of directed motility
Authors: Jha Rupam , Roostalu Johanna , Trokter Martina , Surrey Thomas 
Published: April 2017

ABSTRACTCytoplasmic dynein is involved in a multitude of essential cellular functions. Dynein’s activity is controlled by the combinatorial action of several regulators. The molecular mechanism of this regulation is poorly understood. Using purified proteins, we reconstitute the regulation of the human dynein complex by three prominent regulators on dynamic microtubules in the presence of end binding proteins (EBs). We find that dynein can be in biochemically and functionally distinct pools: either passively tracking dynamic microtubule plus-ends in an EB-dependent manner or moving processively towards minus ends in an adaptor protein-dependent manner. Whereas both dynein pools share the dynactin complex, they have opposite preferences for binding other regulators, either the adaptor protein Bicaudal D2 (BicD2) or the multifunctional regulator Lisencephaly-1 (Lis1). Remarkably, dynactin, but not EBs, strongly biases motility initiation locally from microtubule plus ends by autonomous plus end recognition. BicD2 and Lis1 together control the overall efficiency of motility initiation. Our study provides insight into the mechanism of dynein activity regulation by dissecting the distinct functional contributions of the individual members of a dynein regulatory network.
Generalising Better: Applying Deep Learning to Integrate Deleteriousness Prediction Scores for Whole-Exome SNV Studies
Authors: Korvigo Ilia , Afanasyev Andrey , Romashchenko Nikolay , Skoblov Mihail 
Published: April 2017

AbstractMany automatic classifiers were introduced to aid inference of phenotypical effects of uncategorised nsSNVs (nonsynonymous Single Nucleotide Variations) in theoretical and medical applications. Lately, several meta-estimators have been proposed that combine different predictors, such as PolyPhen and SIFT, to integrate more information in a single score. Although many advances have been made in feature design and machine learning algorithms used, the shortage of high-quality reference data along with the bias towards intensively studied in vitro models call for improved generalisation ability in order to further increase classification accuracy and handle records with insufficient data. Since a meta-estimator basically combines different scoring systems with highly complicated nonlinear relationships, we investigated how deep learning (supervised and unsupervised), which is particularly efficient at discovering hierarchies of features, can improve classification performance. While it is believed that one should only use deep learning for high-dimensional input spaces and other models (logistic regression, support vector machines, Bayesian classifiers, etc) for simpler inputs, we still believe that the ability of neural networks to discover intricate structure in highly heterogenous datasets can aid a meta-estimator. We compare the performance with various popular predictors, many of which are recommended by the American College of Medical Genetics and Genomics (ACMG), as well as available deep learning-based predictors. Thanks to hardware acceleration we were able to use a computationally expensive genetic algorithm to stochastically optimise hyper-parameters over many generations. Overfitting was hindered by noise injection and dropout, limiting coadaptation of hidden units. Although we stress that this work was not conceived as a tool comparison, but rather an exploration of the possibilities of deep learning application in ensemble scores, our results show that even relatively simple modern neural networks can significantly improve both prediction accuracy and coverage. We provide open-access to our finest model at http://score.generesearch.ru.
Conservation of epigenetic regulation by the MLL3/4 tumour suppressor in planarian pluripotent stem cells
Authors: Mihaylova Yuliana , Abnave Prasad , Kao Damian , Hughes Samantha , Lai Alvina , Jaber-Hijazi Farah , Kosaka Nobuyoshi , Aboobaker A. Aziz 
Published: April 2017

AbstractCurrently, little is known about the evolution of epigenetic regulation in animal stem cells. Using the planarian stem cell system to investigate the role of the COMPASS family of MLL3/4 histone methyltransferases, we demonstrate that their role as tumour suppressors in stem cells is conserved over a large evolutionary distance in animals. This also suggested the potential conservation of a genome wide epigenetic regulation program in animal stem cells, so we assessed the regulatory effects of Mll3/4 loss of function by performing RNA-seq and ChIP-seq on the G2/M planarian stem cell population, part of which contributes to the formation of outgrowths. We find many oncogenes and tumour suppressors among the affected genes that are therefore likely candidates for mediating MLL3/4 tumour suppression function in mammals, where little is known aboutin vivoregulatory targets. Our work demonstrates conservation of an important epigenetic regulatory program in animals and highlights the utility of the planarian model system for studying epigenetic regulation.
Framework for reanalysis of publicly available Affymetrix®GeneChip®data sets based on functional regions of interest
Authors: Saka Ernur , Harrison Benjamin J. , West Kirk , Petruska Jeffrey C. , Rouchka Eric C. 
Published: April 2017

AbstractBackgroundSince the introduction of microarrays in 1995, researchers world-wide have used both commercial and custom-designed microarrays for understanding differential expression of transcribed genes. Public databases such as ArrayExpress and the Gene Expression Omnibus (GEO) have made millions of samples readily available. One main drawback to microarray data analysis involves the selection of probes to represent a specific transcript of interest, particularly in light of the fact that transcript-specific knowledge (notably alternative splicing) is dynamic in nature.ResultsWe therefore developed a framework for reannotating and reassigning probe groups for Affymetrix®GeneChip®technology based on functional regions of interest. This framework addresses three issues of Affymetrix®GeneChip®data analyses: removing nonspecific probes, updating probe target mapping based on the latest genome knowledge and grouping probes into gene, transcript and region-based (UTR, individual exon, CDS) probe sets. Updated gene and transcript probe sets provide more specific analysis results based on current genomic and transcriptomic knowledge. The framework selects unique probes, aligns them to gene annotations and generates a custom Chip Description File (CDF). The analysis reveals only 87% of the Affymetrix®GeneChip®HG-U133 Plus 2 probes uniquely align to the current hg38 human assembly without mismatches. We also tested new mappings on the publicly available data series using rat and human data from GSE48611 and GSE72551 obtained from GEO, and illustrate that functional grouping allows for the subtle detection of regions of interest likely to have phenotypical consequences.ConclusionThrough reanalysis of the publicly available data series GSE48611 and GSE72551, we profiled the contribution of UTR and CDS regions to the gene expression levels globally. The comparison between region and gene based results indicated that the detected expressed genes by gene-based and region-based CDFs show high consistency and regions based results allows us to detection of changes in transcript formation.
The central amygdala controls learning in the lateral amygdala
Authors: Yu Kai , Ahrens Sandra , Zhang Xian , Schiff Hillary , Ramakrishnan Charu , Fenno Lief , Deisseroth Karl , Zhou Pengcheng , Paninski Liam , Li Bo 
Published: April 2017

SUMMARYBoth the lateral and the central nuclei of the amygdala are required for adaptive behavioral responses to environmental cues predicting threats. While experience-driven synaptic plasticity in the lateral amygdala is thought to underlie the formation of association between a sensory stimulus and an ensuing threat, how the central amygdala participates in such learning process remains unclear. Here we show that a specific class of central amygdala neurons, the protein kinase C-δ-expressing neurons, is essential for the synaptic plasticity underlying learning in the lateral amygdala, as it is required for lateral amygdala neurons to respond to unconditioned stimulus, and furthermore carries information about the unconditioned stimulus to instruct learning. Our results uncover an amygdala functional organization that may play a key role in diverse learning processes.
Wheel running increases hyperthermia and mortality rate following 3,4-methylenedioxymethamphetamine (MDMA) in rats
Authors: Taffe M. A. 
Published: April 2017

AbstractHyperthermic responses are commonly reported in cases of human medical emergency following recreational use of 3,4-methylenedioxymethamphetamine (MDMA, “Ecstasy”), but a precise determination of contributing environmental factors has been elusive given the relative scarcity of threatening and fatal reactions in humans. This study was conducted to determine if elevated physical activity contributes to hyperthermic responses to MDMA in a well controlled animal model. Unrestrained male Wistar rats were monitored with minimally-invasive radiotelemetry techniques following challenge with MDMA (1.0, 5.6 and 10.0 mg/kg, s.c.). Studies were conducted in low (23-25°C) and high (27°C) ambient temperature (TA), with and without access to an activity wheel. The study confirmed dose dependent effects on body temperature, chamber activity and wheel activity which were modified by different TAconditions. Increases in wheel and home chamber activity produced by 10 mg/kg MDMA increased the magnitude of hyperthermia under 27°C TA. Furthermore, greater subject mortality was observed in the wheel-access condition compared with the no-wheel condition. These data provide direct evidence that sustained physical activity increases the hyperthermic response to MDMA and that this is associated with increased lethality. This is the first direct experimental confirmation that increased physical activity may be a risk factor for adverse reactions to MDMA in human user populations.
Histopathological image QTL discovery of immune infiltration variants
Authors: Barry Joseph D. , Fagny Maud , Paulson Joseph N. , Aerts Hugo J. W. L. , Platig John , Quackenbush John 
Published: April 2017

AbstractGenotype-to-phenotype association studies typically use macroscopic physiological measurements or molecular readouts as quantitative traits. There are comparatively few suitable quantitative traits available between cell and tissue length scales, a limitation that hinders our ability to identify variants affecting phenotype at many clinically informative levels. Here we show that quantitative image features, automatically extracted from histopathological imaging data, can be used for image Quantitative Trait Loci (iQTL) mapping and variant discovery. Using thyroid pathology images, clinical metadata, and genomics data from the Genotype and Tissue Expression (GTEx) project, we establish and validate a quantitative imaging biomarker for immune cell infiltration. A total of 100,215 variants were selected for iQTL profiling, and tested for genotype-phenotype associations with our quantitative imaging biomarker. Significant associations were found in HDAC9 and TXNDC5. We validated the TXNDC5 association using GTExcis-expression QTL data, and an independent hypothyroidism dataset from the Electronic Medical Records and Genomics network.One Sentence SummaryWe use a histopathological image QTL analysis to identify genomic variants associated with immune cell infiltration.
Quiescence unveils a novel mutational force in fission yeast
Authors: Gangloff Serge , Achaz Guillaume , Villain Adrien , Miled Samia , Denis Claire , Arcangioli Benoit 
Published: April 2017

One Sentence SummaryThe quiescence-driven mutational landscape reveals a novel evolutionary force.AbstractDuring cell division, the spontaneous mutation rate is expressed as the probability of mutationspergeneration, whereas during quiescence it will be expressedperunit of time. In this study, we report that during quiescence, the unicellular haploid fission yeast accumulates mutations as a linear function of time. We determined that 3 days of quiescence generate a number of invalidating mutations equivalent to that of one round of DNA replication. The novel mutational landscape of quiescence is characterized by insertion/deletion accumulating as fast as single nucleotide variants, and elevated amounts of deletions. When we extended the study to 3 months of quiescence, we confirmed the replication-independent mutational spectrum at the whole-genome level of a clonally aged population and uncovered phenotypic variations that subject the cells to natural selection. Thus, our results support the idea that genomes continuously evolve under two alternating phases that will impact on their size and composition.
Effective aperture of X-ray compound refractive lenses
Authors: Kohn V. G. 
Published: April 2017

A new definition of the effective aperture of the X-ray compound refractive lens (CRL) is proposed. Both linear (one-dimensional) and circular (two-dimensional) CRLs are considered. It is shown that for a strongly absorbing CRL the real aperture does not influence the focusing properties and the effective aperture is determined by absorption. However, there are three ways to determine the effective aperture in terms of transparent CRLs. In the papers by Kohn [(2002). JETP Lett.
76, 600–603; (2003). J. Exp. Theor. Phys.
97, 204–215; (2009). J. Surface Investig.
3, 358–364; (2012). J. Synchrotron Rad.
19, 84–92; Kohn et al. (2003). Opt. Commun.
216, 247–260; (2003). J. Phys. IV Fr, 104, 217–220], the FWHM of the X-ray beam intensity just behind the CRL was used. In the papers by Lengeler et al. [(1999). J. Synchrotron Rad.
6, 1153–1167; (1998). J. Appl. Phys.
84, 5855–5861], the maximum intensity value at the focus was used. Numerically, these two definitions differ by 50%. The new definition is based on the integral intensity of the beam behind the CRL over the real aperture. The integral intensity is the most physical value and is independent of distance. The new definition gives a value that is greater than that of the Kohn definition by 6% and less than that of the Lengeler definition by 41%. A new approximation for the aperture function of a two-dimensional CRL is proposed which allows one to calculate the two-dimensional CRL through the one-dimensional CRL and to obtain an analytical solution for a complex system of many CRLs.
Understanding Chinese users’ switching behaviour of cloud storage services
Authors: Xu Fang , Tian Meng , Xu Guohu , Reyes Ayala Brenda , Shen Wen 
Published: April 2017

Purpose
This paper aims to explore the switching intention and behaviour of cloud storage services (CSS) individual users in China by integrating the variables of switching cost and habit into the expectation disconfirmation theory.

Design/methodology/approach
Based on 419 valid responses, structural equation modelling was used to examine the research model.

Findings
The results indicated that perceived usefulness and expectation disconfirmation have a positive and negative effect on user satisfaction, respectively. While expectation disconfirmation has a negative impact on perceived usefulness, user satisfaction positively affects users’ habit and switching cost. At the same time, switching intention is affected significantly and negatively by perceived usefulness, user satisfaction, as well as switching cost, where in switching intention and habit can commendably predict switching behaviour. The results can guide for CSS providers on how to successfully retain users in the competitive CSS market.

Originality/value
Previous researches have investigated the effects of perceived usefulness, switching cost and user traits on CSS adoption and continuance intention, as well as behaviour; they neglected the antecedents of switching cost and the effect of user habit on them. Additionally, relatively few studies have been devoted to an empirical examination of the switching behaviour from a particular CSS product to its rival products at the individual user level. This research tries to fill these gaps.
Adolescents’ social reading: motivation, behaviour, and their relationship
Authors: Li Wu , Wu Yuehua 
Published: April 2017

PurposeUsing the case of social reading via WeChat in China, this paper aims to explore adolescents’ social reading motivation and behaviour. It also examines how the specific dimensions of reading motivation contribute to the different aspects of social reading behaviour.Design/methodology/approachThis study used survey approach, which gathered 1,039 valid responses from a cluster sampling in 14 middle and high schools in Shanghai, China.FindingsThe results indicated that social reading motivation was a multidimensional construct, which included the dimensions of social interaction, self-development, peer recognition, information acquisition, personal interests and time killing. The research also found that different motivational dimensions exerted different influences on adolescents’ social reading activities. Specifically, the motivations of time killing and self-development are significant predictors of both the reading act and socializing act. However, information acquisition and personal interests were significant predictors only of the reading act, while social interaction and peer recognition significantly predicted the socializing act.Research limitations/implicationsThe findings would be valuable for those who develop reading programs or administer adolescents’ reading practice. This study can help them understand the complexity of adolescents’ social reading motivation and distinguish between its different dimensions.Originality/valueThe study provides important insights into the nature of adolescents’ social reading motivation and how it relates to their social reading behaviour. It not only confirmed the multidimensionality of social reading motivation as a construct but also expanded the exploration of reading motivation and behaviour to the social media arena.
Energy security, uncertainty and energy resource use options in Ethiopia
Authors: Guta Dawit , Börner Jan 
Published: April 2017

Purpose
Ethiopia’s energy sector faces critical challenges to meeting steadily increasing energy demand given limited infrastructure, heavy reliance on hydroelectric power and underdevelopment of alternative energy resources. The purpose of this paper was to identify optimal least cost investment decisions for integrated energy source diversification. The authors seek to contribute to the relevant literature by paying particular attention to the role of public policy for promoting renewable energy investment and to better understand future energy security implications of various sources of uncertainty.

Design/methodology/approach
The authors created a dynamic linear programming model using General Algebraic Modelling System software to explore the national energy security implications of uncertainties associated with increasing technological advances and efficiency, and climate change scenarios.

Findings
To cope with the impacts of drought expected from future climate change on hydroelectric power production, Ethiopia would need to invest in the development of alternative energy resources. Such investment would not only enhance the sustainability and reliability of energy production but also increase costs. Greater rates of technological and efficiency innovations, however, were found to improve electricity diversification and reduce production costs and shadow prices or resource scarcity, and are thus key for enhancing energy security and reducing the risks posed by drought.

Originality/value
The dynamic linear programming model by the authors represents a flexible sector modelling tool for exploring the sustainability and efficiency of energy resource development pathways and evaluating the effects of different sources of uncertainty on the energy sector.