scholarly journals Scool: a new data storage format for single-cell Hi-C data

2021 ◽  
Author(s):  
Joachim Wolff ◽  
Nezar Abdennur ◽  
Rolf Backofen ◽  
Björn Grüning
Keyword(s):  
Single Cell ◽  
Data Storage ◽  
Storage Format

scholarly journals Scool: a new data storage format for single-cell Hi-C data

2020 ◽  
Author(s):  
Joachim Wolff ◽  
Nezar Abdennur ◽  
Rolf Backofen ◽  
Björn Grüning
Keyword(s):  
Single Cell ◽  
Data Storage ◽  
Supplementary Information ◽  
File Format ◽  
C Storage ◽  
Storage Format ◽  
User Friendly ◽  
And Storage ◽  
Labour Time ◽  
Interaction Matrices

Abstract Motivation Single-cell Hi-C research currently lacks an efficient, easy to use and shareable data storage format. Recent studies have used a variety of sub-optimal solutions: publishing raw data only, text-based interaction matrices, or reusing established Hi-C storage formats for single interaction matrices. These approaches are storage and pre-processing intensive, require long labour time and are often error-prone. Results The single-cell cooler file format (scool) provides an efficient, user-friendly and storage-saving approach for single-cell Hi-C data. It is a flavour of the established cooler format and guarantees stable API support. Availability and implementation The single-cell cooler format is part of the cooler file format as of API version 0.8.9. It is available via pip, conda and github: https://github.com/mirnylab/cooler. Contact [email protected] Supplementary information Supplementary data are available at Bioinformatics online.

Study on data storage format of a volume holographic memory

2003 ◽  
Author(s):  
Changsheng Xie ◽  
Wei Li ◽  
Xiandeng Pei
Keyword(s):  
Data Storage ◽  
Holographic Memory ◽  
Storage Format

scholarly journals ORGANIZATIONAL INTEROPERABILITY IN SUPPORT OF COMPETITIVENESS

2016 ◽  
Vol 13 (1) ◽  
pp. 58
Author(s):  
Elizangela Dias Pereira ◽  
Maria Inacia Favila Salum ◽  
Carlos Manoel Taboada Rodriguez
Keyword(s):  
Information Technology ◽  
Software Development ◽  
Information Management ◽  
Data Storage ◽  
Programming Language ◽  
Extra Effort ◽  
Related Information ◽  
Communication Frequency ◽  
Storage Format ◽  
Original Concept

This paper presents a new context in the logistic field of organizations. This concept emerged due to the expansion of the application of the original concept proposed by the area of software development, in which the goal was to enable the exchange of information between different systems in such a way that no extra effort was needed. Therefore, this area of Information Technology (IT) is constituted by the standardization of programming language, commands, data storage format, among others. Eventually, principles that were already quite widespread in the sphere of IT gradually became used in different areas, untilit started being used amongst the business field. Thus, in order to make corporate processes interoperable, it has contributed to approach and facilitate the communication between companies based on some of the principles of the software field, such as standardization, form of communication, frequency of orders…etc. On the logistic field, which actually connects industrial and commercial companies through the flux of material and related information, the inoperability has by goal help on the resolution of problems regarding received and sent information management, fulfilling more rapidly the demands and opportunities of the market. In this context, we intend to define the part of interoperability on organizational competitiveness.

scholarly journals Multi-channel data storage format definition for visualization tasks on the example of SPOT-4 images

2019 ◽  
pp. 302-308
Author(s):  
N Yu Sevastianova ◽  
N S Vinogradova
Keyword(s):  
Remote Sensing ◽  
Data Storage ◽  
Remote Sensing Data ◽  
Disk Arrays ◽  
Sensing Data ◽  
Incomplete Knowledge ◽  
Emergency Situations ◽  
Data Interleaving ◽  
Storage Format ◽  
Production Problems

One of the features of a remote sensing data storage is the widespread utilization of large-capacity disk arrays. Emergency situations arising from the use of arrays can lead to the fact that the remote sensing data, usually stored in uncompressed form, may become partially damaged. But even with incomplete recovery, this kind of data can be used in the future to solve production problems. However, this recovery is sometimes hampered by incomplete knowledge of the format of the corrupted data. The article describes an approach to automatic recognition of multichannel data interleaving type (BIP, BIL or BSQ) and its application to a recovery of SPOT-4 remote sensing data stored in the segment format "SEG", which were damaged after a disk array failure.

Panoramic Image Browser Design Based on Cylindrical Surface

2012 ◽  
Vol 468-471 ◽  
pp. 2441-2444
Author(s):  
Gang Yang
Keyword(s):  
Data Storage ◽  
Cylindrical Surface ◽  
Three Dimension ◽  
Panoramic Image ◽  
Display Format ◽  
Storage Format

After generating panorama, panoramic browser can display it.In order to develop the browser, Using glscene component developed in Delphi,which encapsulates functions of OpenGL and includes a set of base classes that develop quickly three-dimension graphics system, then putting forward an open format based on XML,which can prevent the display format from confining the data storage format,to show panoramic space of different systems in the brower,and hotspot principle is adopted to achieve different scene switch.

scholarly journals Comparative Analysis of 3D Data Storage Format in Intelligent Systems and Virtual Reality

2015 ◽  
Vol 0 (4) ◽  
pp. 3
Author(s):  
Дмитрий Алексеевич Чувиков ◽  
Виктор Петрович Феоктистов
Keyword(s):  
Virtual Reality ◽  
Comparative Analysis ◽  
Data Storage ◽  
Intelligent Systems ◽  
3D Data ◽  
Storage Format

scholarly journals A Beginner’s Guide on Integrating *Omics Approaches to Study Marine Microbial Communities: Details and Discussions From Sample Collection to Bioinformatics Analysis

2021 ◽  
Vol 8 ◽  
Author(s):  
Sabrina Natalie Wilms
Keyword(s):  
Single Cell ◽  
Data Storage ◽  
High Throughput Sequencing ◽  
Marine Ecosystem ◽  
Cloud Services ◽  
Small Scale ◽  
Species Differentiation ◽  
Sequencing Data ◽  
The World ◽  
Microbial Organisms

The variety of Earth’s organisms is manifold. However, it is the small-scale marine community that makes the world goes round. Microbial organisms of pro- and eukaryotic origin drive the carbon supply and nutrient cycling, thus are mediating the primary productivity within the world largest ecosystem called ocean. But due to the ocean’s great size and large number of biogeographically habitats, the total of microbial species can hardly be grabbed and therefore their functional roles not fully described. However, recent advances in high-throughput sequencing technologies are revolutionizing our understanding of the marine microbial diversity, ecology and evolution. Nowadays, research questions on species differentiation can be solved with genomic approaches such as metabarcoding, while transcriptomics offers the possibility to assign gene functions even to a single cell, e.g., single-cell transcriptomics. On the other hand, due to the diversified amount of sequencing data, the certainty of a data crisis is currently evolving. Scientists are forced to broaden their view on bioinformatics resources for analysis and data storage in from of, e.g., cloud services, to ensure the data’s exchangeability. Which is why time resources are now shifting toward solving data problems rather than answering the eco-evolutionary questions stated in the first place. This review is intended to provide exchange on *omics approaches and key points for discussions on data handling used to decipher the relevant diversity and functions of microbial organisms in the marine ecosystem.

scholarly journals Visualisation and analysis of multi-resolution raster geodatasets in the cloud

2019 ◽  
Vol 1 ◽  
pp. 1-2
Author(s):  
Lassi Lehto ◽  
Jaakko Kähkönen ◽  
Juha Oksanen ◽  
Tapani Sarjakoski
Keyword(s):  
Data Storage ◽  
Web Applications ◽  
Cloud Service ◽  
Visual Exploration ◽  
Geospatial Information ◽  
Computing Platform ◽  
Interactive Analysis ◽  
Digital Elevation ◽  
Administrative Unit ◽  
Storage Format

<p><strong>Abstract.</strong> Raster geodatasets are an important data source for map-related web applications. However, existing differences in how those datasets are georeferenced, formatted and made available complicate their integration for analysis and visualisation purposes. Furthermore, the inconsistent cell resolutions make it difficult to perform efficient and reliable display of the datasets over a range of scales. In particular, it is challenging to achieve satisfactory user experience in visual exploration of interactive analysis operations carried out on these datasets.</p><p>Dataset harmonisation carried out as a pre-processing procedure seems to be necessary for resolving the raster geodata inconsistency challenge. After the pre-processing step, the harmonized datasets have to be stored into an easily accessible data storage, preferably in close connection with the computing platform where the analysis operations are to be performed.</p><p>Multidimensional datacube has emerged as a conceptual framework for organising a repository of harmonised raster geodatasets. Satellite images have so far been the most popular geospatial application area for datacubes. The set of dimensions of such geodatacube typically consist of two or three coordinate axes, time, and the content theme. While being ingested into the datacube, the involved datasets are brought into a common georeferencing frame, series of cell resolutions, and storage format. The selected harmonised resolution levels can actually be seen as a set of individual geodatacubes.</p><p>An initiative has launched in Finland to build a harmonised multi-resolution geodatacube, called GeoCubes Finland, containing some of the most important national geodatasets. The datasets currently incorporated into the geodatacube include digital elevation models together with land cover, superficial deposit, forest inventory and administrative unit datasets. GeoCubes Finland is being built as part of the Finnish Open Geospatial Information Infrastructure for Research (oGIIR) programme, aimed at developing the geospatial research infrastructure of the country. The data storage and the related computing facilities have been implemented on a cloud service platform provided by CSC - IT Center for Science that serves Finnish universities and research institutes.</p>

Read Method for LTD-2100 GPR Data Based on Matlab

2014 ◽  
Vol 501-504 ◽  
pp. 170-173
Author(s):  
Jian Luo ◽  
Zhong Qiu Xie ◽  
Wen Chang Huang ◽  
Da Gang Wang
Keyword(s):  
User Interface ◽  
Data Storage ◽  
Graphical User Interface ◽  
Ground Penetrating Radar ◽  
Radar Data ◽  
Processing Technologies ◽  
Unique Data ◽  
Practical Engineering ◽  
Storage Format ◽  
Ground Penetrating

LTD-2100 type ground penetrating radar has its own unique data storage format, and the acquisition data is stored in lte format. This article explained in detail the data of lte format, especially illustrated and analyzed the header file parts of the radar data in tabular form. With a practical engineering as an example, the application of Matlab achieved a goal to read the ground penetrating radar, create a graphical user interface (GUI) and display the GPR data on graphical user interface. The actual data processing shows the effectiveness and practicality of the processing technologies.

scholarly journals Performance evaluation on structural mapping choices for data-centric XML documents

2020 ◽  
Vol 18 (3) ◽  
pp. 1539
Author(s):  
Su-Cheng Haw ◽  
Emyliana Soong
Keyword(s):  
Data Storage ◽  
Data Exchange ◽  
Test Cases ◽  
Structural Mapping ◽  
Xml Data ◽  
Xml Documents ◽  
Model Based ◽  
Type Definition ◽  
Storage Format ◽  
Mapping Purpose

<span>eXtensible Mark-up Language (XML) has been widely used as the de facto standard for data exchange over the Web. It is crucial to ensure that the data can be mapped correctly into the underlying data storage format, that is, without any lost of information. The two mapping strategies are structural-based and model-based. The structural-based mapping involves the presence of Data Type Definition (DTD) for schema mapping while the model-based mapping does not require the present of DTD or any schema for the mapping purpose. The structural-based mapping is good especially for data-centric type of data, i.e., data which is structured and can be binded into certain schema. As such, this paper evaluates and compares the performances of two selected existing structural-based mapping via simulation. Two main evaluations are: (i) storing the XML data into relational database (RDB), <br /> and (ii) querying the XML data from the RDB. The time taken for each respective process will be recorded and compared. From the experimental results, it is observed that the s-XML approach outperformed the SAX approach in terms of storing and query evaluations for most of the test cases conducted.</span>

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