Search Results for "java expression evaluator" - Page 2
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Showing 35 open source projects for "java expression evaluator"
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SLEDRIDE: Simplified Learning about Expression Data Running in a Desktop Environment. To provide a general workbench for pipe-lining microarray gene expression data from supervised learning results into unsupervised learning methods.
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A simple Java application for the analysis and identification of gene networks. ProPesca takes as input shorts temporal series of realtime-PCR expression levels and it clusters genes that exhibit either similar or specular behaviors.
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Genome Expression Pathway Analysis Tool - Analysis and Visualization of Microarray Gene Expression Data under Genomic, Proteomic and Metabolic Context
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NetAtlas is a Cytoscape plugin that uses tissue gene expression data to filter cellular signaling network. The plugin identifies of tissue-defined networks, tissue-specific network components, and components with correlated expression across tissues.
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Open2Dprot is an open-source proteomics project for the development of bioinformatic tools for n-dimensional protein expression data analysis of quantified protein expression across multiple samples from research experiments.
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Maple Tree is a Java based visualization tool used by researchers in the biological sciences to visualize and graphically browse the results of analyses of gene expression data collected from microarray experiments.
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GeneX is an gene expression database system with an integrated toolset that enables researchers to store, analyze, and communicate their data.
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Info Sapient will be an Open Source, Common License 0.5, 100% Pure Java based program that is a mechanism for the expression and execution of business rules.
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Error to trace to log to deploy. One click. No SSH.AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
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BIRBU (BIological Relationship BUilder) is a Java tool for microarray gene expression data analysis. BIRBU identifies biologically significant relationship between genes using microarray data and prior knowledge on relationships between genes.
