PsicquicGraph, a BioJS component to visualize molecular interactions from PSICQUIC servers

Summary: Protein interaction networks have become an essential tool in large-scale data analysis, integration, and the visualization of high-throughput data in the context of complex cellular networks. Many individual databases are available that provide information on binary interactions of proteins and small molecules. Community efforts such as PSICQUIC aim to unify and standardize information emanating from these public databases. Here we introduce PsicquicGraph, an open-source, web-based visualization component for molecular interactions from PSIQUIC services. Availability: PsicquicGraph is freely available at the BioJS Registry for download and enhancement. Instructions on how to use the tool are available here http://goo.gl/kDaIgZ and the source code can be found at http://github.com/biojs/biojs and DOI:10.5281/zenodo.7709.

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XlinkCyNET: a Cytoscape application for visualization of protein interaction networks based on cross-linking mass-spectrometry identifications

10.1101/2020.12.20.423654 ◽

2020 ◽

Author(s):

Diogo Borges Lima ◽

Ying Zhu ◽

Fan Liu

Keyword(s):

Mass Spectrometry ◽

Protein Interaction ◽

Large Scale ◽

Interaction Network ◽

Protein Interaction Networks ◽

Interaction Networks ◽

Cross Linking ◽

Protein Interaction Data ◽

Interaction Data ◽

Link Type

ABSTRACTSoftware tools that allow visualization and analysis of protein interaction networks are essential for studies in systems biology. One of the most popular network visualization tools in biology is Cytoscape, which offers a large selection of plugins for interpretation of protein interaction data. Chemical cross-linking coupled to mass spectrometry (XL-MS) is an increasingly important source for such interaction data, but there are currently no Cytoscape tools to analyze XL-MS results. In light of the suitability of Cytoscape platform but also to expand its toolbox, here we introduce XlinkCyNET, an open-source Cytoscape Java plugin for exploring large-scale XL-MS-based protein interaction networks. XlinkCyNET offers rapid and easy visualization of intra and intermolecular cross-links and the locations of protein domains in a rectangular bar style, allowing subdomain-level interrogation of the interaction network. XlinkCyNET is freely available from the Cytoscape app store: http://apps.cytoscape.org/apps/xlinkcynet and at https://www.theliulab.com/software/xlinkcynet.

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WebViz: A Web-Based Collaborative Interactive Visualization System for Large-Scale Data Sets

Lecture Notes in Earth System Sciences - GPU Solutions to Multi-scale Problems in Science and Engineering ◽

10.1007/978-3-642-16405-7_37 ◽

2013 ◽

pp. 587-606 ◽

Cited By ~ 2

Author(s):

Yichen Zhou ◽

Robin M. Weiss ◽

Elizabeth McArthur ◽

David Sanchez ◽

Xiang Yao ◽

...

Keyword(s):

Large Scale ◽

Interactive Visualization ◽

Data Sets ◽

Web Based ◽

Visualization System ◽

Large Scale Data ◽

Scale Data ◽

Large Scale Data Sets

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A Hierarchical 3D Data Rendering System Synchronized with HTML

International Journal of Virtual Reality ◽

10.20870/ijvr.2006.5.2.2691 ◽

2006 ◽

Vol 5 (2) ◽

pp. 67-72

Author(s):

Yousuke Kimura ◽

Tomohiro Mashita ◽

Atsushi Nakazawa ◽

Takashi Machida ◽

Kiyoshi Kiyokawa ◽

...

Keyword(s):

Large Scale ◽

Frame Rate ◽

Web Based ◽

Geometric Data ◽

Large Scale Data ◽

3D Data ◽

Interactive Frame ◽

Encoding Method ◽

Hierarchical Encoding ◽

Scale Data

We propose a new rendering system for large-scale, 3D geometic data that can be used with web-based content man-agement systems (CMS). To achieve this, we employed a geometry hierarchical encoding method "QSplat" and implemented this in a Java and JOGL (Java bindings of OpenGL) environment. Users can view large-scale geometric data using conventional HTML browsers with a non-powerful CPU and low-speed networks. Further, this system is independent of the platforms. We add new functionalities so that users can easily understand the geometric data: Annotations and HTML Synchronization. Users can see the geometric data with the associated annotations that describe the names or the detailed explanations of the particular portions. The HTML Synchronization enables users to smoothly and interactively switch our rendering system and HTML contents. The experimental results show that our system performs an interactive frame rate even for a large-scale data whereas other systems cannot render them

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PPI layouts: BioJS components for the display of Protein-Protein Interactions

F1000Research ◽

10.12688/f1000research.3-50.v1 ◽

2014 ◽

Vol 3 ◽

pp. 50 ◽

Cited By ~ 6

Author(s):

Gustavo A. Salazar ◽

Ayton Meintjes ◽

Nicola Mulder

Keyword(s):

Protein Interaction ◽

Protein Interactions ◽

Protein Interaction Networks ◽

Interaction Networks ◽

Third Party ◽

Protein Protein Interactions ◽

Web Based ◽

Protein Protein Interaction ◽

Link Type ◽

Protein Protein Interaction Networks

Summary: We present two web-based components for the display of Protein-Protein Interaction networks using different self-organizing layout methods: force-directed and circular. These components conform to the BioJS standard and can be rendered in an HTML5-compliant browser without the need for third-party plugins. We provide examples of interaction networks and how the components can be used to visualize them, and refer to a more complex tool that uses these components. Availability: http://github.com/biojs/biojs; http://dx.doi.org/10.5281/zenodo.7753

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Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data

10.1101/117812 ◽

2017 ◽

Cited By ~ 1

Author(s):

Julie A McMurry ◽

Nick Juty ◽

Niklas Blomberg ◽

Tony Burdett ◽

Tom Conlin ◽

...

Keyword(s):

Best Practices ◽

Large Scale ◽

Data Science ◽

Life Science ◽

Core Component ◽

Science Data ◽

Web Based ◽

Large Scale Data ◽

Online Databases ◽

Scale Data

AbstractIn many disciplines, data is highly decentralized across thousands of online databases (repositories, registries, and knowledgebases). Wringing value from such databases depends on the discipline of data science and on the humble bricks and mortar that make integration possible; identifiers are a core component of this integration infrastructure. Drawing on our experience and on work by other groups, we outline ten lessons we have learned about the identifier qualities and best practices that facilitate large-scale data integration. Specifically, we propose actions that identifier practitioners (database providers) should take in the design, provision and reuse of identifiers; we also outline important considerations for those referencing identifiers in various circumstances, including by authors and data generators. While the importance and relevance of each lesson will vary by context, there is a need for increased awareness about how to avoid and manage common identifier problems, especially those related to persistence and web-accessibility/resolvability. We focus strongly on web-based identifiers in the life sciences; however, the principles are broadly relevant to other disciplines.

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Implementasi Sistem Crowdsourced Labelling Berbasis Web dengan Metode Weighted Majority Voting

Jurnal ULTIMA InfoSys ◽

10.31937/si.v6i2.223 ◽

2016 ◽

Vol 6 (2) ◽

pp. 76-82

Author(s):

Antonius Rachmat ◽

Yuan Lukito

Keyword(s):

Supervised Learning ◽

Large Scale ◽

Majority Voting ◽

Training Data ◽

Web Based ◽

Weighted Majority ◽

Large Scale Data ◽

Labelling Process ◽

Weighted Majority Voting ◽

Scale Data

Crowdsourced Labelling is a large scale data labelling process, solicits a large group of people to label the data, usually via Internet. This paper discusses about design and implementation of Web-based Crowdsourced Labelling. Supervised learning classification methods need labelled training data for its training phase. Unfortunately, in many cases, there aren’t any already available labelled training data. Large scale data labelling is a tedious and time consuming work. This research develops a web-based crowdsourced labelling which able to solicit a large group of people as data labeler to speed up the data labelling process. This system also allows multiple labeler for every data. The final label is calculated using Weighted Majority Voting method. We grabbed and used Facebook comments from the two candidates’ Facebook Page of 2014 Indonesian Presidential Election as testing data. Based on the testing conducted we can conclude that this system is able to handle all the labelling steps well and able to handle collision occurred when multiple labeler labelling a same data in the same time. The system successfully produces final label in CSV format, which can be processed further with many sentiment analysis tools or machine learning tools. Index Terms - Crowdsources labeling, web-based system, supervised learning, weighted majority voting.

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