共查询到20条相似文献，搜索用时 171 毫秒
1.
Background
Suppression subtractive hybridization is a popular technique for gene discovery from non-model organisms without an annotated genome sequence, such as cowpea (Vigna unguiculata (L.) Walp). We aimed to use this method to enrich for genes expressed during drought stress in a drought tolerant cowpea line. However, current methods were inefficient in screening libraries and management of the sequence data, and thus there was a need to develop software tools to facilitate the process. 相似文献2.
Background
Arabidopsis thaliana is a useful model organism for deciphering the genetic determinants of seed size; however the small size of its seeds makes measurements difficult. Bulk seed weights are often used as an indicator of average seed size, but details of individual seed is obscured. Analysis of seed images is possible but issues arise from variations in seed pigmentation and shadowing making analysis laborious. We therefore investigated the use of a consumer level scanner to facilitate seed size measurements in conjunction with open source image-processing software. 相似文献3.
Background
Recent years have seen an increase in methods for plant phenotyping using image analyses. These methods require new software solutions for data extraction and treatment. These solutions are instrumental in supporting various research pipelines, ranging from the localisation of cellular compounds to the quantification of tree canopies. However, due to the variety of existing tools and the lack of central repository, it is challenging for researchers to identify the software that is best suited for their research.Results
We present an online, manually curated, database referencing more than 90 plant image analysis software solutions. The website, plant-image-analysis.org, presents each software in a uniform and concise manner enabling users to identify the available solutions for their experimental needs. The website also enables user feedback, evaluations and new software submissions.Conclusions
The plant-image-analysis.org database provides an overview of existing plant image analysis software. The aim of such a toolbox is to help users to find solutions, and to provide developers a way to exchange and communicate about their work.4.
Context
Objective identification of locations on transportation networks, where animal-vehicle collisions (AVC) occur more frequently than expected (hotspots), is an important step for the effective application of mitigation measures.Objectives
We introduce the KDE+ software which is a programmed version of the KDE+ method for effective identification of traffic accident hotspots. The software can be used in order to analyze animal-vehicle collision data.Methods
The KDE+ method is based on principles of Kernel Density Estimation (KDE). The symbol ‘+’ indicates that the method allows for the objective selection of significant clusters and for the ranking of the hotspots. It is also simultaneously applicable to an unlimited number of road segments.Results
We applied the KDE+ method to the entire Czech road network. The hotspots were ranked according to their significance. The resulting hotspots represent a short overall road length which should require a more detailed assessment in the field. The 100 most important clusters of AVC represent, for example, only 19.7 km of the entire road network (37,469 km).Conclusions
We present an objective method for hotspots identification which can be used for AVC data. This method is unique because it determines the significance level of hotspots in an objective way. The prioritization of hotspots allows a transportation manager to effectively allocate resources to a feasible number of identified hotspots. We describe the software, data preparation and present the KDE+ application to AVC data.5.
6.
Ji Zhou Christopher Applegate Albor Dobon Alonso Daniel Reynolds Simon Orford Michal Mackiewicz Simon Griffiths Steven Penfield Nick Pullen 《Plant methods》2017,13(1):117
Background
Plants demonstrate dynamic growth phenotypes that are determined by genetic and environmental factors. Phenotypic analysis of growth features over time is a key approach to understand how plants interact with environmental change as well as respond to different treatments. Although the importance of measuring dynamic growth traits is widely recognised, available open software tools are limited in terms of batch image processing, multiple traits analyses, software usability and cross-referencing results between experiments, making automated phenotypic analysis problematic.Results
Here, we present Leaf-GP (Growth Phenotypes), an easy-to-use and open software application that can be executed on different computing platforms. To facilitate diverse scientific communities, we provide three software versions, including a graphic user interface (GUI) for personal computer (PC) users, a command-line interface for high-performance computer (HPC) users, and a well-commented interactive Jupyter Notebook (also known as the iPython Notebook) for computational biologists and computer scientists. The software is capable of extracting multiple growth traits automatically from large image datasets. We have utilised it in Arabidopsis thaliana and wheat (Triticum aestivum) growth studies at the Norwich Research Park (NRP, UK). By quantifying a number of growth phenotypes over time, we have identified diverse plant growth patterns between different genotypes under several experimental conditions. As Leaf-GP has been evaluated with noisy image series acquired by different imaging devices (e.g. smartphones and digital cameras) and still produced reliable biological outputs, we therefore believe that our automated analysis workflow and customised computer vision based feature extraction software implementation can facilitate a broader plant research community for their growth and development studies. Furthermore, because we implemented Leaf-GP based on open Python-based computer vision, image analysis and machine learning libraries, we believe that our software not only can contribute to biological research, but also demonstrates how to utilise existing open numeric and scientific libraries (e.g. Scikit-image, OpenCV, SciPy and Scikit-learn) to build sound plant phenomics analytic solutions, in a efficient and effective way.Conclusions
Leaf-GP is a sophisticated software application that provides three approaches to quantify growth phenotypes from large image series. We demonstrate its usefulness and high accuracy based on two biological applications: (1) the quantification of growth traits for Arabidopsis genotypes under two temperature conditions; and (2) measuring wheat growth in the glasshouse over time. The software is easy-to-use and cross-platform, which can be executed on Mac OS, Windows and HPC, with open Python-based scientific libraries preinstalled. Our work presents the advancement of how to integrate computer vision, image analysis, machine learning and software engineering in plant phenomics software implementation. To serve the plant research community, our modulated source code, detailed comments, executables (.exe for Windows; .app for Mac), and experimental results are freely available at https://github.com/Crop-Phenomics-Group/Leaf-GP/releases.7.
Berthold Heinze 《Plant methods》2007,3(1):4-7
Background
Chloroplast genomes evolve slowly and many primers for PCR amplification and analysis of chloroplast sequences can be used across a wide array of genera. In some cases 'universal' primers have been designed for the purpose of working across species boundaries. However, the essential information on these primer sequences is scattered throughout the literature. 相似文献8.
Background
In vivo detection of protein-bound genomic regions can be achieved by combining chromatin-immunoprecipitation with next-generation sequencing technology (ChIP-seq). The large amount of sequence data produced by this method needs to be analyzed in a statistically proper and computationally efficient manner. The generation of high copy numbers of DNA fragments as an artifact of the PCR step in ChIP-seq is an important source of bias of this methodology.Results
We present here an R package for the statistical analysis of ChIP-seq experiments. Taking the average size of DNA fragments subjected to sequencing into account, the software calculates single-nucleotide read-enrichment values. After normalization, sample and control are compared using a test based on the ratio test or the Poisson distribution. Test statistic thresholds to control the false discovery rate are obtained through random permutations. Computational efficiency is achieved by implementing the most time-consuming functions in C++ and integrating these in the R package. An analysis of simulated and experimental ChIP-seq data is presented to demonstrate the robustness of our method against PCR-artefacts and its adequate control of the error rate.Conclusions
The software ChIP-seq Analysis in R (CSAR) enables fast and accurate detection of protein-bound genomic regions through the analysis of ChIP-seq experiments. Compared to existing methods, we found that our package shows greater robustness against PCR-artefacts and better control of the error rate. 相似文献9.
Background
Allotetraploid white clover (Trifolium repens L.) is an important forage legume widely cultivated in most temperate regions. Only a small number of microsatellite markers are publicly available and can be utilized in white clover breeding programs. The objectives of this study were to develop an integrated approach for microsatellite development and to evaluate the approach for the development of new SSR markers for white clover. 相似文献10.
Thomas H Hansen Kristian H Laursen Daniel P Persson Pai Pedas Søren Husted Jan K Schjoerring 《Plant methods》2009,5(1):12-11
Background
Quantitative multi-elemental analysis by inductively coupled plasma (ICP) spectrometry depends on a complete digestion of solid samples. However, fast and thorough sample digestion is a challenging analytical task which constitutes a bottleneck in modern multi-elemental analysis. Additional obstacles may be that sample quantities are limited and elemental concentrations low. In such cases, digestion in small volumes with minimum dilution and contamination is required in order to obtain high accuracy data. 相似文献11.
Edward M Golenberg D Noah Sather Leandria C Hancock Kenneth J Buckley Natalie M Villafranco David M Bisaro 《Plant methods》2009,5(1):9-14
Background
Gene silencing is proving to be a powerful tool for genetic, developmental, and physiological analyses. The use of viral induced gene silencing (VIGS) offers advantages to transgenic approaches as it can be potentially applied to non-model systems for which transgenic techniques are not readily available. However, many VIGS vectors are derived from Gemini viruses that have limited host ranges. We present a new, unipartite vector that is derived from a curtovirus that has a broad host range and will be amenable to use in many non-model systems. 相似文献12.
Background
Fluorescent hybridization techniques are widely used to study the functional organization of different compartments within the mammalian nucleus. However, few examples of such studies are known in the plant kingdom. Indeed, preservation of nuclei 3D structure, which is required for nuclear organization studies, is difficult to fulfill. 相似文献13.
Background
Large-scale genetic profiling, mapping and genetic association studies require access to a series of well-characterised and polymorphic microsatellite markers with distinct and broad allele ranges. Selection of complementary microsatellite markers with non-overlapping allele ranges has historically proved to be a bottleneck in the development of multiplex microsatellite assays. The characterisation process for each microsatellite locus can be laborious and costly given the need for numerous, locus-specific fluorescent primers. 相似文献14.
Application of GC-MS for the detection of lipophilic compounds in diverse plant tissues 总被引：2，自引：0，他引：2
Anna Lytovchenko Romina Beleggia Nicolas Schauer Tal Isaacson Jan E Leuendorf Hanjo Hellmann Jocelyn KC Rose Alisdair R Fernie 《Plant methods》2009,5(1):4-11
Background
The concept of metabolite profiling has been around for decades and technical innovations are now enabling it to be carried out on a large scale with respect to the number of both metabolites measured and experiments carried out. However, studies are generally confined to polar compounds alone. Here we describe a simple method for lipophilic compounds analysis in various plant tissues. 相似文献15.
FlordeFátima Rosas-Cárdenas Noé Durán-Figueroa Jean-Philippe Vielle-Calzada Andrés Cruz-Hernández Nayelli Marsch-Martínez Stefan de Folter 《Plant methods》2011,7(1):4
Background
Small RNAs emerged over the last decade as key regulators in diverse biological processes in eukaryotic organisms. To identify and study small RNAs, good and efficient protocols are necessary to isolate them, which sometimes may be challenging due to the composition of specific tissues of certain plant species. Here we describe a simple and efficient method to isolate small RNAs from different plant species. 相似文献16.
Naoki Hirotsu Naomi Murakami Takayuki Kashiwagi Kazuhiro Ujiie Ken Ishimaru 《Plant methods》2010,6(1):12
Background
Genotype analysis using multiple single nucleotide polymorphisms (SNPs) is a useful but labor-intensive or high-cost procedure in plant research. Here we describe an alternative genotyping method that is suited to multi-sample or multi-locus SNP genotyping and does not require electrophoresis or specialized equipment. 相似文献17.
Background
The amount of DNA in the chloroplasts of some plant species has been shown recently to decline dramatically during leaf development. A high-throughput method of DNA detection in chloroplasts is now needed in order to facilitate the further investigation of this process using large numbers of tissue samples. 相似文献18.
Background
Artificial chromosomes (ACs) are a promising next-generation vector for genetic engineering. The most common methods for developing AC constructs are to clone and combine centromeric DNA and telomeric DNA fragments into a single large DNA construct. The AC constructs developed from such methods will contain very short telomeric DNA fragments because telomeric repeats can not be stably maintained in Escherichia coli. 相似文献19.
20.
Jeremy D Edwards Jaroslav Janda Megan T Sweeney Ambika B Gaikwad Bin Liu Hei Leung David W Galbraith 《Plant methods》2008,4(1):13