26 papers · ranked by Valyu relevance
Maged N Kamel Boulos, Teeradache Viangteeravat, Matthew N Anyanwu, Venkateswara Ra Nagisetty + 1 more
'Venkateswara Ra Nagisetty' 'Emin Kuscu'] The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable…
Han Wu, Kamran Sedig, Ariane Machado-Lima, Uba Backonja + 11 more
'David Borland' 'Jawad Ahmed Chishtie' 'Jessica Babineau' 'Iwona Anna Bielska' 'Monica Cepoiu-Martin' 'Michael Irvine' 'Andriy Koval' 'Jean-Sebastien Marchand' 'Luke Turcotte' 'Tara Jeji' 'Susan Jaglal'] Background Visual analytics (VA) promotes the understanding of data using visual, interactive techniques and using…
Alexandr A. Kalinin, Selvam Palanimalai, Junqi Zhu, Wenyi Wu + 5 more
'Nikhil Devraj' 'Chunchun Ye' 'Nellie Ponarul' 'Syed S. Husain' 'Ivo D. Dinov'] Many systems for exploratory and visual data analytics require platform-dependent software installation, coding skills, and analytical expertise. The rapid advances in data-acquisition, web-based information, and communication and…
Yury Kashnitsky
Visual analytics is a subdomain of data analysis which combines both human and machine analytical abilities and is applied mostly in decision-making and data mining tasks. Triclustering, based on Formal Concept Analysis (FCA), was developed to detect groups of objects with similar properties under similar conditions.…
Yi Chen, Caixia Wu, Qinghui Zhang, Di Wu
With the availability of big data for food safety, more and more advanced data analysis methods are being applied to risk analysis and prewarning (RAPW). Visual analytics, which has emerged in recent years, integrates human and machine intelligence into the data analysis process in a visually interactive manner…
Anton Stratmann, Martin Beyß, Johann F. Jadebeck, Katharina Nöh
Understanding input-output relationships within multivariate datasets is an ubiquitous task in the life and data sciences. For this, visual analysis is indispensable for providing expressive summaries and preparing decision-making. We present the visual analysis approach and software MooViE, which is designed to strike…
Jaka Kokošar, Cagatay Turkay, Luka Avsec, Miha Štajdohar + 1 more
We introduce a visual analytics methodology for survival analysis, and propose a framework that defines a reusable set of visualization and modeling components to support exploratory and hypothesis-driven biomarker discovery. Survival analysis—essential in biomedicine—evaluates patients’ survival rates and the onset of…
Chih-Wei Huang, Richard Lu, Usman Iqbal, Shen-Hsien Lin + 7 more
'Phung Anh (Alex) Nguyen' 'Hsuan-Chia Yang' 'Chun-Fu Wang' 'Jianping Li' 'Kwan-Liu Ma' 'Yu-Chuan (Jack) Li' 'Wen-Shan Jian'] Background Electronic medical records (EMRs) contain vast amounts of data that is of great interest to physicians, clinical researchers, and medial policy makers. As the size, complexity, and…
Astrid van den Brandt, Folkert de Vries, Robin van Esch, Sander Vlugter + 4 more
The growing number of sequences and increasing proof that single references create reference bias have driven the development of pangenomes to represent the genomic diversity of species. To leverage this complex diversity information for biological insights, analysis and visualization support are needed to explore the…
Olivera Marjanovic
Inspired by leading industry practices, this paper describes an innovative learning activity designed to combine data visualisation and cross-functional collaboration supported by enterprise social media. The activity is structured around sharing, co-creation and negotiation of departmental/disciplinary insights across…
Ronald A. Rensink
Traditionally, vision science and information/data visualization have interacted by using knowledge of human vision to help design effective displays. It is argued here, however, that this interaction can also go in the opposite direction: the investigation of successful visualizations can lead to the discovery of…
Lu Ying, Aoyu Wu, Haotian Li, Zikun Deng + 6 more
'Yong Wang' 'Huamin Qu' 'Dazhen Deng' 'Yingcai Wu'] Visual analytics (VA) systems have been widely used in various application domains. However, VA systems are complex in design, which imposes a serious problem: although the academic community constantly designs and implements new designs, the designs are difficult to…
Ana Lavalle, Alejandro Maté, Juan Trujillo
> Abstract. Choosing the right Visualization techniques is critical in Big Data Analytics. However, decision makers are not experts on visualization and they face up with enormous difficulties in doing so. There are currently many different (i) Big Data sources and also (ii) many different visual analytics to be…
Ana Lavalle, Alejandro Maté, Juan Trujillo, Stefano Rizzi
—Information visualization plays a key role in business intelligence analytics. With ever larger amounts of data that need to be interpreted, using the right visualizations is crucial in order to understand the underlying patterns and results obtained by analysis algorithms. Despite its importance, defining the right…
Leixian Shen, Enya Shen, Zhiwei Tai, Yihao Xu + 2 more
'Jianmin Wang'] General visualization recommendation systems typically make design decisions for the dataset automatically. However, most of them can only prune meaningless visualizations but fail to recommend targeted results. This paper contributes TaskVis, a task-oriented visualization recommendation system that…
Klaus Eckelt, Patrick Adelberger, Markus J. Bauer, Thomas Zichner + 1 more
We propose an interactive visual analytics approach for the characterization and comparison of patient subgroups (i.e., cohorts). Despite having the same disease and similar demographic characteristics, patients respond differently to therapy. One reason for this is the vast number of variables in the genome that…
Kevin Mildau, Christoph Büschl, Jürgen Zanghellini, Justin J.J. van der Hooft
Computational metabolomics workflows have revolutionized the untargeted metabolomics field. However, the organization and prioritization of metabolite features remains a laborious process. Organizing metabolomics data is often done through mass fragmentation-based spectral similarity grouping, resulting in feature sets…
Julia Keizer, Christian F. Luz, Bhanu Sinha, Lisette van Gemert-Pijnen + 3 more
Data and data visualization are integral parts of (clinical) decision-making in general and stewardship (antimicrobial stewardship, infection control, and institutional surveillance) in particular. However, systematic research on the use of data visualization in stewardship is lacking. This study aimed at filling this…
Rania Mkhinini Gahar, Olfa Arfaoui, Minyar Sassi Hidri
The new age of digital growth has marked all fields. This technological evolution has impacted data flows which have witnessed a rapid expansion over the last decade that makes the data traditional processing unable to catch up with the rapid flow of massive data. In this context, the implementation of a big data…
Min Chen, Amos Golan
—In this paper, we present an abstract model of visualization and inference processes and describe an information-theoretic measure for optimizing such processes. In order to obtain such an abstraction, we first examined six classes of workflows in data analysis and visualization, and identified four levels of typical…
Murat Cihan Sorkun, Dajt Mullaj, J. M. Vianney A. Koelman, Süleyman Er
Visualizing chemical spaces streamlines the analysis of molecular datasets by reducing the information to human perception level, hence it forms an integral piece of molecular engineering, including chemical library design, high-throughput screening, diversity analysis, and outlier detection. We present here ChemPlot…
Victor Cavaller
This article consists of a conceptual analysis-from the perspective of communication sciences-of the relevant aspects that should be considered during operational steps in data visualization. The analysis is performed taking as a reference the components that integrate the communication framework theory-the message…
Fernanda I. Saldívar-González, José L. Medina-Franco
Chemical space is a powerful, general, and practical conceptual framework in drug discovery and other areas in chemistry that addresses the diversity of molecules and it has various applications. Moreover, chemical space is a cornerstone of chemoinformatics as a scientific discipline. In response to the increase in the…
David Meijer, Marnix H. Medema, Justin J. J. van der Hooft
Effective visualization of small molecules is paramount in conveying concepts and results in cheminformatics. Scalable vector graphics (SVG) are preferred for creating such visualizations, as SVGs can be easily altered in post-production and exported to other formats. A wide spectrum of software applications already…
Dimitar Georgiev, Simon Vilms Pedersen, Ruoxiao Xie, Álvaro Fernández-Galiana + 2 more
Raman spectroscopy is a non-destructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardisation, and the…
Sergio Pablo-García, Raúl Pérez-Soto, Albert Sabadell-Rendón, Diego Garay-Ruiz + 2 more
In the study of chemical reactions, visualizing reaction networks is pivotal for identifying crucial compounds and reactions. Traditional methods, such as network schematics and reaction path linear plots, often struggle to effectively represent complex reaction networks due to their size and intricate connectivity.…