BioSieve
A sieve for biological data

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ExpressionSieve™  is a microarray data analysis, data mining and data visualization software package. 

ExpressionSieve™ combines the best practice of statistical analysis, software engineering, bioinformatics and complex data visualization. ExpressionSieve™ is aimed at providing not only set of basic tools for expression analysis, but also tools bridging between expression data and other domain data, such as gene ontology, pathway, genomics, literature, biochemical assay, clinical data, mass spectrometry data, etc. ExpressionSieve™ is a versatile tool for disease research, drug discovery, and system biology. Find more detail information from product material here .  

GeneOntologyBrowser™ / YeastFunctionCatalogBrowser  enables user browse through the part of Gene Ontology/Yeast Function Catolog, which is relevant to their genes of interest. Starting from a set of genes, whether they are from clustering analysis, sequencing analysis etc., GeneOntologyBrowser™/ YeastFunctionCatalogBrowserTM quickly shows user the partition of this set of genes by gene ontology classification/yeast function catalog, in addition, direct attention to the classification terms that are mostly enriched in this set of genes. 

PathwayBrowser™ enables user to color each gene on a pathway with expression value. By analyzing multiple pathways and multiple expression data sets at the same time, user is able to discover the impact of certain treatment/condition on biological pathways.
These browsers are part of the ExpressionSieve™, however, can also be used/sold separately.


ExpressionSieve TM Lite   is available for free download here . This version has all the basic functions, without the three browsers and data set limitations are either no.genes X no.experiments < 10,000 or (no.genes < 2000 and no.experiments < 20). We would like you to cite our product and our website in your publications if you have used it. Please check back for updated version, and check out product manual and tutorials here .


ExpressionSieveTM flexible licensing policy

ExpressionSieveTM case study
Cancer study:
       
Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling.
          Alizadeh AA, et al. (2000) Nature 403(6769):503-11
Molecular Classification of Cancer: Class Discovery and Class Prediction by Gene Expression.
Golub et al (1999), Science 286:531-537.
Yeast study:
          The transcriptional program of sporulation in budding yeast.
          Chu S, et al. (1998) Science 282(5389):699-705
               
Toxicology study:   available soon