Over more than a decade, we have continuously perfectioned techniques and vocabularies for the biocuration of biological experiments. Our unique collections of deeply curated and high quality transcriptomic data, combined with our high-performance but easy-to-use tools, enable global and instant analysis of the world's transcriptomic data for novel discoveries and for validation.
Imagine analyzing thousands of studies simultaneously to find genes specifically related to a drug or to a disease. Or searching for conditions or diseases related to a gene signature. This - and more - can be done with ease using our tools, based on deeply structured and fully harmonized public and proprietary data.
Genes differentially expressed between damaged and intact cartilage tissues are displayed on a volcano plot. Specific subsets of genes can be selected for further analysis, e,g. to visualize their expression across tissues or other conditions. (Differential Expression tool)
Identifcation of cell lines having the highest expression level of gene CTLA4. Sample-level expression of the selected cell line, SU-DHL-1, is shown in the detailed view (lower plot). (Cell Lines tool from CONDITION SEARCH toolset)
Identification of genes most specifically expressed in a chosen cell line as compared to other cell lines. (Cell Lines tool from GENE SEARCH toolset)
Response of CTLA4 and ERBB2 in various breast cancer related comparisons from TCGA and other sources. A selected comparison comparing ERBB2 positive samples against control is shown on a sample-level detail in the lower section. This tool is often used gene characterization as well as target and biomarker validation. (Perturbations tool from CONDITION SEARCH toolset)
Identification of genes most correlated with APOC3 across a selected compendium of human RNA-Seq data. Edges indicating pairwise co-expression allow identifying distinct gene clusters correlated with APOC3, which can be selected for visualization in other tools for further characterization. This tool is frequently used to identify novel targets related to a disease or biological process. (Co-Expression tool from SIMILARITY SEARCH toolset)
Validation of a gene expression signature for psoriasis by correlating it against other perturbations or diseases derived from the human RNA-Seq compendium. This tool identifies positively or negatively correlated conditions and is often used for biomarker validation, indication finding or drug repositioning. (Signature tool from SIMILARITY SEARCH toolset)
Comparison of the expression of PCSK9 against ANGPTL3 in all samples from the compendium of Affymetrix Human 133 Plus2 datasets. Selected tissues, conditions or patient characteristics can be colored manually. (2-Genes Plot tool from SIMILARITY SEARCH toolset)
Expression of TNFAIP6 across samples from selected studies of osteoarthritis. An aggregated view shows expression grouped by different types of stimuli. (Perturbations tool from CONDITION SEARCH toolset)
Identifcation of condition-specific reference genes for RT-qPCR analysis. Candidate reference genes are compared to routinely used reference genes. (RefGenes tool from GENE SEARCH toolset)
Hierarchical clustering of a gene signature for psoriasis against a selected set of experimental conditions. (Hierarchical Clustering tool from SIMILARITY SEARCH toolset)
The expression level of CTLA4 is plotted against over 400 different tissue and cell types. The most srongly expessing cell types are shown. (Anatomy tool from CONDITION SEARCH toolset)
Search for genes specifically up-regulated in response to atopic dermatitis, as compared to expression in over 1800 other diseases and experimental conditions (only a portion of this list is visible on this screenshot). (Perturbations tool in GENE SEARCH toolset)
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