scholarly journals Extending MapMan Ontology to Tobacco for Visualization of Gene Expression

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Maurice H. T. Ling ◽  
Roel C. Rabara ◽  
Prateek Tripathi ◽  
Paul J. Rushton ◽  
Xijin Ge

Microarrays are a large-scale expression profiling method which has been used to study the transcriptome of plants under various environmental conditions. However, manual inspection of microarray data is difficult at the genome level because of the large number of genes (normally at least 30 000) and the many different processes that occur within any given plant. MapMan software, which was initially developed to visualize microarray data for Arabidopsis, has been adapted to other plant species by mapping other species onto MapMan ontology. This paper provides a detailed procedure and the relevant computing codes to generate a MapMan ontology mapping file for tobacco (Nicotiana tabacum L.) using potato and Arabidopsis as intermediates. The mapping file can be used directly with our custom-made NimbleGen oligoarray, which contains gene sequences from both the tobacco gene space sequence and the tobacco gene index 4 (NTGI4) collection of ESTs. The generated dataset will be informative for scientists working on tobacco as their model plant by providing a MapMan ontology mapping file to tobacco, homology between tobacco coding sequences and that of potato and Arabidopsis, as well as adapting our procedure and codes for other plant species where the complete genome is not yet available.

1984 ◽  
Vol 16 (1-2) ◽  
pp. 281-295 ◽  
Author(s):  
Donald C Gordon

Large-scale tidal power development in the Bay of Fundy has been given serious consideration for over 60 years. There has been a long history of productive interaction between environmental scientists and engineers durinn the many feasibility studies undertaken. Up until recently, tidal power proposals were dropped on economic grounds. However, large-scale development in the upper reaches of the Bay of Fundy now appears to be economically viable and a pre-commitment design program is highly likely in the near future. A large number of basic scientific research studies have been and are being conducted by government and university scientists. Likely environmental impacts have been examined by scientists and engineers together in a preliminary fashion on several occasions. A full environmental assessment will be conducted before a final decision is made and the results will definately influence the outcome.


2021 ◽  
Vol 13 (3) ◽  
pp. 355
Author(s):  
Weixian Tan ◽  
Borong Sun ◽  
Chenyu Xiao ◽  
Pingping Huang ◽  
Wei Xu ◽  
...  

Classification based on polarimetric synthetic aperture radar (PolSAR) images is an emerging technology, and recent years have seen the introduction of various classification methods that have been proven to be effective to identify typical features of many terrain types. Among the many regions of the study, the Hunshandake Sandy Land in Inner Mongolia, China stands out for its vast area of sandy land, variety of ground objects, and intricate structure, with more irregular characteristics than conventional land cover. Accounting for the particular surface features of the Hunshandake Sandy Land, an unsupervised classification method based on new decomposition and large-scale spectral clustering with superpixels (ND-LSC) is proposed in this study. Firstly, the polarization scattering parameters are extracted through a new decomposition, rather than other decomposition approaches, which gives rise to more accurate feature vector estimate. Secondly, a large-scale spectral clustering is applied as appropriate to meet the massive land and complex terrain. More specifically, this involves a beginning sub-step of superpixels generation via the Adaptive Simple Linear Iterative Clustering (ASLIC) algorithm when the feature vector combined with the spatial coordinate information are employed as input, and subsequently a sub-step of representative points selection as well as bipartite graph formation, followed by the spectral clustering algorithm to complete the classification task. Finally, testing and analysis are conducted on the RADARSAT-2 fully PolSAR dataset acquired over the Hunshandake Sandy Land in 2016. Both qualitative and quantitative experiments compared with several classification methods are conducted to show that proposed method can significantly improve performance on classification.


Morphology ◽  
2021 ◽  
Author(s):  
Rossella Varvara ◽  
Gabriella Lapesa ◽  
Sebastian Padó

AbstractWe present the results of a large-scale corpus-based comparison of two German event nominalization patterns: deverbal nouns in -ung (e.g., die Evaluierung, ‘the evaluation’) and nominal infinitives (e.g., das Evaluieren, ‘the evaluating’). Among the many available event nominalization patterns for German, we selected these two because they are both highly productive and challenging from the semantic point of view. Both patterns are known to keep a tight relation with the event denoted by the base verb, but with different nuances. Our study targets a better understanding of the differences in their semantic import.The key notion of our comparison is that of semantic transparency, and we propose a usage-based characterization of the relationship between derived nominals and their bases. Using methods from distributional semantics, we bring to bear two concrete measures of transparency which highlight different nuances: the first one, cosine, detects nominalizations which are semantically similar to their bases; the second one, distributional inclusion, detects nominalizations which are used in a subset of the contexts of the base verb. We find that only the inclusion measure helps in characterizing the difference between the two types of nominalizations, in relation with the traditionally considered variable of relative frequency (Hay, 2001). Finally, the distributional analysis allows us to frame our comparison in the broader coordinates of the inflection vs. derivation cline.


2021 ◽  
Vol 11 (5) ◽  
pp. 2098
Author(s):  
Heyi Wei ◽  
Wenhua Jiang ◽  
Xuejun Liu ◽  
Bo Huang

Knowledge of the sunshine requirements of landscape plants is important information for the adaptive selection and configuration of plants for urban greening, and is also a basic attribute of plant databases. In the existing studies, the light compensation point (LCP) and light saturation point (LSP) have been commonly used to indicate the shade tolerance for a specific plant; however, these values are difficult to adopt in practice because the landscape architect does not always know what range of solar radiation is the best for maintaining plant health, i.e., normal growth and reproduction. In this paper, to bridge the gap, we present a novel digital framework to predict the sunshine requirements of landscape plants. First, the research introduces the proposed framework, which is composed of a black-box model, solar radiation simulation, and a health standard system for plants. Then, the data fitting between solar radiation and plant growth response is used to obtain the value of solar radiation at different health levels. Finally, we adopt the LI-6400XT Portable Photosynthetic System (Li-Cor Inc., Lincoln, NE, USA) to verify the stability and accuracy of the digital framework through 15 landscape plant species of a residential area in the city of Wuhan, China, and also compared and analyzed the results of other researchers on the same plant species. The results show that the digital framework can robustly obtain the values of the healthy, sub-healthy, and unhealthy levels for the 15 landscape plant species. The purpose of this study is to provide an efficient forecasting tool for large-scale surveys of plant sunshine requirements. The proposed framework will be beneficial for the adaptive selection and configuration of urban plants and will facilitate the construction of landscape plant databases in future studies.


2016 ◽  
Vol 10 (4) ◽  
pp. 631-632 ◽  
Author(s):  
Mary Anne Duncan ◽  
Maureen F. Orr

AbstractWhen a large chemical incident occurs and people are injured, public health agencies need to be able to provide guidance and respond to questions from the public, the media, and public officials. Because of this urgent need for information to support appropriate public health action, the Agency for Toxic Substances and Disease Registry (ATSDR) of the US Department of Health and Human Services has developed the Assessment of Chemical Exposures (ACE) Toolkit. The ACE Toolkit, available on the ATSDR website, offers materials including surveys, consent forms, databases, and training materials that state and local health personnel can use to rapidly conduct an epidemiologic investigation after a large-scale acute chemical release. All materials are readily adaptable to the many different chemical incident scenarios that may occur and the data needs of the responding agency. An expert ACE team is available to provide technical assistance on site or remotely. (Disaster Med Public Health Preparedness. 2016;10:631–632)


1991 ◽  
Vol 6 ◽  
pp. 151-165 ◽  
Author(s):  
Hala Fattah

Anyone who watched the televison coverage of, or read about the African famine some years ago could not help but be appalled by the many obstacles erected to impede the progress of getting food to the starving millions in Ethiopia, Somalia and the Sudan. While it is true that the difficult terrain, an inhospitable climate and the lack of rain were partly responsible for the large-scale spread of famine and dearth in the African sub-continent, it is also true that local governments were responsible for creating impediments to the alleviation of mass hunger and starvation. Governments waging war against secessionist regimes and rebel armies used political means—primarily blockades of grain and other foodstuffs—to starve the enemy forces, creating misery among the military as well as civilian populations in the rebel areas.


2008 ◽  
Vol 26 (11) ◽  
pp. 3411-3428 ◽  
Author(s):  
P. Daum ◽  
M. H. Denton ◽  
J. A. Wild ◽  
M. G. G. T. Taylor ◽  
J. Šafránková ◽  
...  

Abstract. Among the many challenges facing the space weather modelling community today, is the need for validation and verification methods of the numerical models available describing the complex nonlinear Sun-Earth system. Magnetohydrodynamic (MHD) models represent the latest numerical models of this environment and have the unique ability to span the enormous distances present in the magnetosphere, from several hundred kilometres to several thousand kilometres above the Earth's surface. This makes it especially difficult to develop verification and validation methods which posses the same range spans as the models. In this paper we present a first general large-scale comparison between four years (2001–2004) worth of in situ Cluster plasma observations and the corresponding simulated predictions from the coupled Block-Adaptive-Tree-Solarwind-Roe-Upwind-Scheme (BATS-R-US) MHD code. The comparison between the in situ measurements and the model predictions reveals that by systematically constraining the MHD model inflow boundary conditions a good correlation between the in situ observations and the modeled data can be found. These results have an implication for modelling studies addressing also smaller scale features of the magnetosphere. The global MHD simulation can therefore be used to place localised satellite and/or ground-based observations into a global context and fill the gaps left by measurements.


Plants ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 2411
Author(s):  
Hamada E. Ali ◽  
Solveig Franziska Bucher

Land-use changes have huge impacts on natural vegetation, especially megaprojects, as the vegetation layer is destroyed in the course of construction works affecting the plant community composition and functionality. This large-scale disturbance might be a gateway for the establishment of invasive plant species, which can outcompete the natural flora. In contrast, species occurring in the area before the construction are not able to re-establish. In this study, we analyzed the impact of a pipeline construction on a wetland nature reserve located in northern Egypt. Therefore, we analyzed the plant species occurrence and abundance and measured each plant species’ traits before the construction in 2017 as well as on multiple occasions up to 2 years after the construction had finished on altogether five sampling events. We found that the construction activity led to the establishment of an invasive species which previously did not occur in the area, namely, Imperata cylindrica, whereas five species (Ipomoea carnea, Pluchea dioscoridis, Polygonum equisetiforme, Tamarix nilotica, and Typha domingensis) could not re-establish after the disturbance. The functionality of ecosystems assessed via the analysis of plant functional traits (plant height, specific leaf area, and leaf dry matter content) changed within species over all sampling events and within the community showing a tendency to approximate pre-construction values. Functional dispersion and Rao’s quadratic diversity were higher after the megaproject than before. These findings are important to capture possible re-establishment and recovery of natural vegetation after construction and raise awareness to the impact of megaprojects, especially in areas which are high priority for conservation.


2019 ◽  
Author(s):  
Anna Danese ◽  
Maria L. Richter ◽  
David S. Fischer ◽  
Fabian J. Theis ◽  
Maria Colomé-Tatché

ABSTRACTEpigenetic single-cell measurements reveal a layer of regulatory information not accessible to single-cell transcriptomics, however single-cell-omics analysis tools mainly focus on gene expression data. To address this issue, we present epiScanpy, a computational framework for the analysis of single-cell DNA methylation and single-cell ATAC-seq data. EpiScanpy makes the many existing RNA-seq workflows from scanpy available to large-scale single-cell data from other -omics modalities. We introduce and compare multiple feature space constructions for epigenetic data and show the feasibility of common clustering, dimension reduction and trajectory learning techniques. We benchmark epiScanpy by interrogating different single-cell brain mouse atlases of DNA methylation, ATAC-seq and transcriptomics. We find that differentially methylated and differentially open markers between cell clusters enrich transcriptome-based cell type labels by orthogonal epigenetic information.


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