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Genes2WordCloud: a quick way to identify biological themes from gene lists and free textKeywords: Word Cloud, Tag Cloud, Text Mining, Gene List Analysis Abstract: Genes2WordCloud is a web application that enables users to quickly identify biological themes from gene lists and research relevant text by constructing and displaying word-clouds. It provides users with several different options and ideas for the sources that can be used to generate a word-cloud. Different options for rendering and coloring the word-clouds give users the flexibility to quickly generate customized word-clouds of their choice.Genes2WordCloud is a word-cloud generator and a word-cloud viewer that is based on WordCram implemented using Java, Processing, AJAX, mySQL, and PHP. Text is fetched from several sources and then processed to extract the most relevant terms with their computed weights based on word frequencies. Genes2WordCloud is freely available for use online; it is open source software and is available for installation on any web-site along with supporting documentation at http://www.maayanlab.net/G2W webcite.Genes2WordCloud provides a useful way to summarize and visualize large amounts of textual biological data or to find biological themes from several different sources. The open source availability of the software enables users to implement customized word-clouds on their own web-sites and desktop applications.Information overload in biomedical research can benefit from methods that can quickly summarize knowledge about specific topics from large bodies of text or data. Word-clouds or tag-clouds are compact visual displays of words where the size and orientation of words represent the underlying importance. Word-clouds can be used to visually summarize information about a specific topic condensing most important terms into minimum amount of space. Word-clouds have been used in other contexts to accomplish this task in many web applications such as summarizing news articles [1]. However, their application in Bioinformatics and Biomedicine has been limited. Desai et al. [2] discussed the use of word-clouds as an alternative way to visualize
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