IPA®
IPA 2011 Winter Release – Cause and Effect
| The newest release of IPA helps you better understand the cause and effect of gene expression changes in your experiment. Now you can predict which transcription factors could be responsible for gene expression and whether those transcription factors are activated or inhibited, all based on experimentally observed relationships. In addition, powerful new tools help you easily visualize downstream effects, so you can determine if your differentially expressed genes are causing an increase or decrease in downstream biological processes or diseases.
The IPA Winter Release also includes a new way to visualize and explore isoform-specific biology by providing an integrated, interactive view of human isoforms and their relation to known biology.
» Register for a live webinar to walk through these highly interactive new capabilities:
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Click to watch a short video overview of the new features. |
Overview:
Predict the cause and effect of changes in gene expression
- Predict the activation or inhibition of transcription factors
- Predict direction of downstream effects on biological processes and disease
Isoform-specific biology
- Visualize and explore isoform-specific biology to support RNA-Sequencing analysis
Highlights:
Adopt a novel approach to transcription factor prediction
- Predict activation or inhibition of transcription factors (TFs) to explain the changes in gene expression in your dataset
- Predict transcription factors using experimentally observed relationships (vs. predicted binding sites) between TFs and genes
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Quickly prioritize predicted transcription factors
- Visualize predicted activation state, which is inferred from the expected vs. observed direction of change in your data set
- Prioritize the most statistically significant TFs
- Select the most interesting TFs and targets and display them as a network
Identify cross-talk between transcription factors in focused regulatory networks
- Automatically generate a TF-target gene network
- Extend the regulatory network with additional relationships to upstream signaling molecules, or associations with diseases and biological processes
- See published evidence for the regulatory interactions
Visualize biological trends in your experiment in a whole new way
- Predict and visualize increase or decrease in downstream biological processes and disease using the direction of change in your gene expression data
- Simplify the biological interpretation of functional results with intuitive visualizations
- Use a hierarchical overview to quickly get a top-to-bottom view of the biology affected in your experiment
- Zoom in on areas of interest and quickly see the specific genes and references that support a prediction
Explore and understand isoform-specific biology with an integrated, interactive view of each human locus
- Explore each human locus, its spliced mRNA, and protein products
- Determine which protein domains are impacted by splicing events
- Review the effect of isoform-specific differences on biological function and disease
- Link to published findings that support isoform-specific differences
10 new signaling pathways – related to neurobiology, epithelial cell junction dynamics, cytoskeletal dynamics, and telomere regulation
- Actin Nucleation by ARP-WASP Complex
- Dopamine-DARPP32 Feedback in cAMP Signaling
- NGF Signaling
- Paxillin Signaling
- Signaling by Rho Family GTPases
- RhoGDI Signaling
- Sertoli Cell-Sertoli Cell Junction Signaling
- Gap Junction Signaling
- Telomerase Signaling
- Telomere Extension by Telomerase
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Quickly prioritize predicted transcription factors |
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Identify cross-talk between transcription factors in focused regulatory networks |
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Predict and visualize effects on downstream biological processes |
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Understand isoform-specific biology with an integrated, interactive view of each human locus |
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