Information visualization techniques in bioinformatics during the postgenomic era

Tang, Ying; Liu, Yang; Friedman, Carol; Lussier, Yves A.

doi:10.1016/s1741-8364(04)02423-0

Cited by 38 publications

(35 citation statements)

References 69 publications

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“…Bioinformatics is an important area which various information visualization techniques have been recently applied [16]. There have been many visualization techniques for gene or protein interaction networks, and some of them are relevant to our techniques since they represent experimental values (e.g.…”

Section: Visualization Of Biological Networkmentioning

confidence: 99%

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Itoh

Muelder

et al. 2009

2009 IEEE Pacific Visualization Symposium

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Many graphs used in real-world applications consist of nodes belonging to more than one category. We call such graph "multiplecategory graphs". Social networks are typical examples of multiplecategory graphs: nodes are persons, links are friendships, and categories are communities that the persons belong to. It is often helpful to visualize both connectivity and categories of the graphs simultaneously. In this paper, we present a new visualization technique for multiple-category graphs. The technique firstly constructs hierarchical clusters of the nodes based on both connectivity and categories. It then places the nodes by a new hybrid space-filling and force-directed layout algorithm to clearly display both connectivity and category information. We show layout results using our hybrid method and compare it with other methods, and present a case study using an active biological network dataset.

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Section: Visualization Of Biological Networkmentioning

confidence: 99%

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

Itoh

Muelder

et al. 2009

2009 IEEE Pacific Visualization Symposium

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“…Visual methods are useful in displaying data in ways that capitalize upon the particular strengths of human pattern processing abilities (15). Information visualization techniques have been successfully used in many areas of bioinformatics, including molecular structures, expression profile, genome and sequence annotation, sequence analysis, molecular pathway, ontology, taxonomy and phylogeny (16). Application of information visualization techniques in gene set analysis will not only help the visualization of large amount of information, but also facilitate data mining by aiding recognition of patterns and trends.…”

Section: Introductionmentioning

confidence: 99%

WebGestalt: an integrated system for exploring gene sets in various biological contexts

Zhang

Kirov

Snoddy

2005

Nucleic Acids Research

1,635

1,503

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High-throughput technologies have led to the rapid generation of large-scale datasets about genes and gene products. These technologies have also shifted our research focus from ‘single genes’ to ‘gene sets’. We have developed a web-based integrated data mining system, WebGestalt (), to help biologists in exploring large sets of genes. WebGestalt is composed of four modules: gene set management, information retrieval, organization/visualization, and statistics. The management module uploads, saves, retrieves and deletes gene sets, as well as performs Boolean operations to generate the unions, intersections or differences between different gene sets. The information retrieval module currently retrieves information for up to 20 attributes for all genes in a gene set. The organization/visualization module organizes and visualizes gene sets in various biological contexts, including Gene Ontology, tissue expression pattern, chromosome distribution, metabolic and signaling pathways, protein domain information and publications. The statistics module recommends and performs statistical tests to suggest biological areas that are important to a gene set and warrant further investigation. In order to demonstrate the use of WebGestalt, we have generated 48 gene sets with genes over-represented in various human tissue types. Exploration of all the 48 gene sets using WebGestalt is available for the public at .

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“…In Herman et al [2000], graph visualization techniques are presented and categorized from the graph drawing point of view. The Tao et al [2004] review approaches the issue of visualization from the point of view of Bioinformatics, including techniques for the presentation of the GO ontology [Gene Ontology Consortium www.go.org].…”

Section: Related Workmentioning

confidence: 99%

Ontology visualization methods—a survey

et al. 2007

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Ontologies, as sets of concepts and their interrelations in a specific domain, have proven to be a useful tool in the areas of digital libraries, the semantic web, and personalized information management. As a result, there is a growing need for effective ontology visualization for design, management and browsing. There exist several ontology visualization methods and also a number of techniques used in other contexts that could be adapted for ontology representation. The purpose of this article is to present these techniques and categorize their characteristics and features in order to assist method selection and promote future research in the area of ontology visualization.

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Information visualization techniques in bioinformatics during the postgenomic era

Cited by 38 publications

References 69 publications

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

A hybrid space-filling and force-directed layout method for visualizing multiple-category graphs

WebGestalt: an integrated system for exploring gene sets in various biological contexts

Ontology visualization methods—a survey

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