AJAX Interface: A Breakthrough in Bioinformatics Web Applications

Kumar, G. Ramesh; Kumar, R. Sathish; Subha, K.

doi:10.4137/pri.s2261

Cited by 3 publications

(2 citation statements)

References 28 publications

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“…This links our approach to calls for Ajax-based applications in biology [12,13] and a system implementation demonstrating how rendering can be performed on the server and resulting images served asynchronously to the browser [14]. However, the sole difference between this work and offline visualization systems is that control and display are done in a separate place from rendering and computation.…”

Section: Introductionmentioning

confidence: 99%

What google maps can do for biomedical data dissemination: examples and a design study

Jianu

Laidlaw

2013

BMC Res Notes

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BackgroundBiologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data.ResultsWe present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers.ConclusionsWe describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations.

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Section: Introductionmentioning

confidence: 99%

What google maps can do for biomedical data dissemination: examples and a design study

Jianu

Laidlaw

2013

BMC Res Notes

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“…From a programmatic point of view, the models describing the design of web applications (Figure 1B) [Aravindhan et al, 2009] can also be applied to the common biological databases. In the classical model, the interaction between the web browser and the web server is based solely on HTML and CSS.…”

Section: Genetic Databasesmentioning

confidence: 99%

Gene Ontology-based framework to annotate genes of hearing

Ovezmyradov¹

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After introducing the existing GO-based tools, the rationale behind the novel application for mining GO data (AGENDA) is discussed. After illustrating possible applications of GO in hearing research, broader bioinformatics strategies including multiple databases and ontologies will be discussed in context of systems biology. As more efficient genetic techniques become available and powerful bioinformatics tools to support them are developed, the search for deafness genes is expected to accelerate and augment our understanding of hearing on the molecular level. DBMS, handles data), the middle layer (where the database access software and the web server perform performes computations) and the front end (where the web interface interacts with a user) [Stein, 2003]. B. Classical vs. AJAX-based architecture of the web applications. While classical web applications are based solely on HTML and CSS, AJAX web applications also employ the AJAX (Asynchronous Javascript and XML) engine [Aravindhan et al., 2009]. GO SlimsGO Slims are charts created using GO annotations to summarize the properties of gene lists. GO Slimmers are tools that analyze the user's input with GO data and generate GO Slims as the output. They are usually used for the annotation of genomes (see, for example, figure 2) and the functional annotation of microarray data. GO toolsMany tools have been created by the members of GO Consortium and by third parties to enable the searching, browsing and analyzing of the GO database [Gene ontology tools website]. However, some of them accept only a single GO term or gene product as an input. Since some complex biological questions cannot be Figure 2: Genome annotation of 4 genetic model organisms using GO Slim. Columns show how many genes are associated with each GO term in the species-specific manner. All GO terms chosen for this GO Slim set belong to the Cellular Component category. Data presented as of 1 st August 2003 [Harris et al., 2004].

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