Dynamic Visualization of Spatially Referenced Information

2005 ◽  
pp. 642-646
Author(s):  
Wu Quan ◽  
Mao Lin Huang
Keyword(s):  
Dynamic Visualization

scholarly journals Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Swapna Vidhur Daulatabad ◽  
Rajneesh Srivastava ◽  
Sarath Chandra Janga
Keyword(s):  
Human Genome ◽  
Cellular Localization ◽  
Expression Profiles ◽  
Free Text ◽  
Dynamic Visualization ◽  
Specific Expression ◽  
Web Resource ◽  
Functional Dynamics ◽  
Non Coding Rnas ◽  
Retrieval Engine

Abstract Background With advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare. Results We present a lncRNA annotation extractor and repository (Lantern), developed using PubMed’s abstract retrieval engine and NCBO’s recommender annotation system. Lantern’s annotations were benchmarked against lncRNAdb’s manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform. Conclusions Lantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern.

ExpanDrogram: Dynamic Visualization of Big Data Segmentation over Time

2021 ◽  
Vol 13 (2) ◽  
pp. 1-27
Author(s):  
A. Khalemsky ◽  
R. Gelbard
Keyword(s):  
Big Data ◽  
Visual Presentation ◽  
Trend Detection ◽  
Dynamic Visualization ◽  
Segmentation Process ◽  
Key Points ◽  
Wide Range ◽  
History Of ◽  
The Individual ◽  
Over Time

In dynamic and big data environments the visualization of a segmentation process over time often does not enable the user to simultaneously track entire pieces. The key points are sometimes incomparable, and the user is limited to a static visual presentation of a certain point. The proposed visualization concept, called ExpanDrogram, is designed to support dynamic classifiers that run in a big data environment subject to changes in data characteristics. It offers a wide range of features that seek to maximize the customization of a segmentation problem. The main goal of the ExpanDrogram visualization is to improve comprehensiveness by combining both the individual and segment levels, illustrating the dynamics of the segmentation process over time, providing “version control” that enables the user to observe the history of changes, and more. The method is illustrated using different datasets, with which we demonstrate multiple segmentation parameters, as well as multiple display layers, to highlight points such as new trend detection, outlier detection, tracking changes in original segments, and zoom in/out for more/less detail. The datasets vary in size from a small one to one of more than 12 million records.

scholarly journals ProtozoaDB: dynamic visualization and exploration of protozoan genomes

2007 ◽  
Vol 36 (Database) ◽  
pp. D547-D552 ◽  
Author(s):  
A. M. R. Davila ◽  
P. N. Mendes ◽  
G. Wagner ◽  
D. A. Tschoeke ◽  
R. R. C. Cuadrat ◽  
...  
Keyword(s):  
Dynamic Visualization

DYNAMIC VISUALIZATION OF SPATIO-TEMPORAL PROCESS MODEL BASED ON NetCDF AND OPTIMAL INTERPOLATION FOR MARINE ENVIRONMENT

2020 ◽  
Vol 19 (11) ◽  
pp. 1957-1967
Author(s):  
Wang Xianghong ◽  
Xu Shenghua ◽  
Liu Jiping ◽  
Yang Yi ◽  
Luo An ◽  
...  
Keyword(s):  
Marine Environment ◽  
Process Model ◽  
Optimal Interpolation ◽  
Dynamic Visualization ◽  
Model Based ◽  
Temporal Process ◽  
Spatio Temporal

scholarly journals Computational Fugue Analysis

2015 ◽  
Vol 39 (2) ◽  
pp. 77-96 ◽  
Author(s):  
Mathieu Giraud ◽  
Richard Groult ◽  
Emmanuel Leguy ◽  
Florence Levé
Keyword(s):  
Complete System ◽  
Ground Truth ◽  
Music Analysis ◽  
Automated Analysis ◽  
Western Music ◽  
Dynamic Visualization ◽  
Ground Truth Data ◽  
Dmitri Shostakovich

One of the pinnacles of form in classical Western music, the fugue is often used in the teaching of music analysis and composition. Fugues alternate between instances of a subject and other patterns and modulatory sections, called episodes. Musicological analyses are generally built on these patterns and sections. We have developed several algorithms to perform an automated analysis of a fugue, starting from a score in which all the voices are separated. By focusing on the diatonic similarities between pitch intervals, we detect subjects and countersubjects, as well as partial harmonic sequences inside the episodes. We also implemented tools to detect subject scale degrees, cadences, and pedals, as well as a method for segmenting the fugue into exposition and episodic parts. Our algorithms were tested on a corpus of 36 fugues by J. S. Bach and Dmitri Shostakovich. We provide formalized ground-truth data on this corpus as well as a dynamic visualization of the ground truth and of our computed results. The complete system showed acceptable or good results for about one half of the fugues tested, enabling us to depict their design.

scholarly journals Correction: Dynamic visualization of mRNA splicing variants with a transactivating reporter

2021 ◽  
Vol 57 (75) ◽  
pp. 9626-9626
Author(s):  
Si Chen ◽  
Wenjie Shu ◽  
Haifeng Zheng ◽  
Zhe Ma ◽  
Miao Li ◽  
...  
Keyword(s):  
Mrna Splicing ◽  
Dynamic Visualization ◽  
Splicing Variants

Correction for ‘Dynamic visualization of mRNA splicing variants with a transactivating reporter’ by Si Chen et al., Chem. Commun., 2021, DOI: 10.1039/d1cc02439f.

scholarly journals USE OF SMARTPHONE AND VIRTUAL REALITY AND AUGMENTED REALITY GLASSES IN MATHEMATICS CLASSES

2021 ◽  
Keyword(s):  
Virtual Reality ◽  
Augmented Reality ◽  
Information And Communication Technologies ◽  
Teaching And Learning ◽  
Dynamic Visualization ◽  
Exploratory Research ◽  
Mathematical Concepts ◽  
Information And Communication ◽  
Research Findings ◽  
Object Of Study

The present work presents a research carried out with 6th and 7th grade students of Elementary School II at Escola Municipal Mon. Walfredo Gurgel Alto do Rodrigues/RN, aiming to encourage the use of materials such as Ruler and Square in Mathematics classes and to know your opinion about the use of Augmented Reality and Virtual Reality glasses. This aimed at a reflective analysis of how the inclusion of technologies in education can enhance learning when the use of multimedia resources that help in understanding mathematical concepts or that enable a dynamic visualization of the object of study are encouraged. She seeks to know what the contribution of this device to the teaching and learning process of Mathematics. Methodologically, the work is characterized as an exploratory research of qualitative and quantitative nature, with a bias towards a case study, with data collected through a semi-structured questionnaire with 102 students. We can count on an interdisciplinary planning to present the programmed contents with more meaning. The results were analyzed based on the research instruments and the testimonies of the students, in addition to a brief study on information and communication technologies applied to learning. Thus, the data are organized in graphs where the research findings are expressed.

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