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A Galaxy based web server for processing and visualizing deeply sequenced data. The web server's core functionality consists of a suite of newly developed tools, called deepTools, that enable users with little bioinformatic background to explore the results of their sequencing experiments in a standardized setting. Users can upload pre-processed files with continuous data in standard formats and generate heatmaps and summary plots in a straight-forward, yet highly customizable manner.
A work space to graphically explore gene expression data. PermutMatrix uses the graphical Eisen approach, and extends it to optimal reorganization methods. It can also offer several methods for the optimal reorganization of rows and columns of a numerical dataset. This software yields different and complementary results than hierarchical clustering, therefore contributing to the understanding and identification of different gene expression profile. Large datasets can be thoroughly and quickly analyzed.
A web-tool that allows genome scale comparison of high throughput experiments (ChIP-seq, RNA-seq and CAGE) provided by a user, to the data in the public domain. Heat*seq allows users to contextualise their sequencing data with respect to vast amounts of public data in a few minutes without requiring any programming skills. Heat*seq currently contains over 12,000 experiments across diverse tissues and cell types in human, mouse and drosophila. Heat*seq displays interactive correlation heatmaps, with an ability to dynamically subset datasets to contextualise user experiments. High quality figures and tables are produced and can be downloaded in multiple formats.
Assists in creating a shareable HTML file that contains an interactive cluster heatmap. Heatmaply is an R package that permits users to hover the mouse pointer over a cell to show details. It also includes the ability to zoom from the dendrogram panes and the placing of factor variables in the sides of the heatmap. A graphic interface guides researcher with the heatmap construction, with the functionality to export heatmap and summaries parameter specifications to reproduce it.
Generates color-grids representations. JColorGrid is a data visualization and standardization tool that is able to represent complex datasets with the aim of providing an effective data presentation and analysis. It allows users to parameters such as minimum/maximum, inflection colors, scale increments, or exceptions. The software can be run through a graphic interface for standard data exploration or through a command-line application for advanced and customized parameters.
Builds combined visualizations of microarray studies. HeatMapper displays a correlation plot in combination with sample characteristics in a dynamic and flexible manner. It permits the accurate and rapid interpretation of the data obtained by large scale gene expression profiling. This tool boasts results in form of a triangular heatmap. It maps sample-sample similarity, such as Pearson correlation, Spearman correlation or Euclidean distance, to a color scale ranging from blue to red.
Generates interactive graphs in R. RJSplot contributes to the development of interactive visualization packages in R oriented toward computational biology research. The software implements 16 interactive graphical representations. It provides a dynamic and customizable visualization and allows actions such as browsing, movement, zoom adjustment, viewing values, or identifying variables. It can be used to allow a comprehensive visualization of information and an improved diffusion of scientific results.
Permits interactive visualization that shows time series data for both gene activity and metabolite levels over multiple pathways and multiple species. Pathline supports the visual analysis of all four kinds of data (functional genomics data across multiple pathways, multiple genes and metabolites, and multiple species) and three kinds of task levels. It provides linearized pathways view that allows an overview of multiple aggregate similarity scores for each gene across multiple pathways.
A BioJS component that lays-out and renders two-dimensional (2D) plots or heat maps that are ideally suited to visualize matrix formatted data in biology such as for the display of microarray experiments or the outcome of mutational studies and the study of SNP-like sequence variants. HeatMapViewer can be easily integrated into documents and provides a powerful, interactive way to visualize heat maps in web applications. The software tool uses a scalable graphics technology that adapts the visualization component to any required resolution, a useful feature for a presentation with many different data-points. The component can be applied to present various biological data types.
Qlucore Omics Explorer
Assists users in investigating normalized omics large datasets. Qlucore Omics Explorer is a modular platform divided into four main functionalities (i) Visualization includes features for generating various plots types including principal component analysis (PCA) plots and real-time visualization; (ii) Exploration furnishes tools for comparing, browsing and selecting targeted information (iii) Analysis includes statistical methods such as quadratic regression, f-tests, or ANOVA and (iv) Sharing allows users to export results as multiple formats including videos or variable lists.
Iheatmapr / Interactive Heat Map
Creates an interactive heatmap, with each cell linked to plots of horizontal and vertical slices. Iheatmapr is an R package for building complex, interactive heatmaps using modular building blocks. The iheatmapr package includes two functions, iheatmap and add iheatmap, that wrap together several of the modular building blocks that are often used in conjunction to make common types of heatmaps. There are two main types of plots in iheatmapr “main heatmaps” and subplots. Subplots can be added to the left, right, top, or bottom of a main heatmap.
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Creates customizable static and interactive heatmaps. Shinyheatmap is a low memory footprint program, making it particularly well-suited for the interactive visualization of extremely large datasets that cannot typically be computed in-memory due to size restrictions. The software aims to enrich the genomic data exploration experience by providing a variety of customization options to investigate large input datasets.
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