IPA®
Learn About IPA
IPA can provide more insight into your experimental systems.
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Overview
IPA is software that helps researchers model, analyze, and understand the complex biological and chemical systems at the core of life science research. IPA has been broadly adopted by the life science research community and is cited in thousands of peer-reviewed journal articles.
IPA helps you understand complex 'omics data at multiple levels by integrating data from a variety of experimental platforms and providing insight into the molecular and chemical interactions, cellular phenotypes, and disease processes of your system. IPA provides insight into the causes of observed gene expression changes and into the predicted downstream biological effects of those changes.
Even if you don’t have experimental data, you can use IPA to intelligently search the Ingenuity®Knowledge Base for information on genes, proteins, chemicals, drugs, and molecular relationships to build biological models or get up to speed in a relevant area of research. IPA provides the right biological context to facilitate informed decision-making, advance research project design, and generate new testable hypotheses. |
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IPA provides many kinds of biological insights |
Highlights
Quickly analyze your experimental data to identify key insights
- Unlock the insights buried in your experimental data (gene expression, RNA-Seq, microRNA, mRNA, qPCR, proteomics, metabolomics, genotyping) by quickly identifying relationships, mechanisms, functions, and pathways of relevance.
- Predict the causes and effect of changes in gene expression by understanding upstream transcription factor activation/inhibition and whether downstream biological processes and diseases are increased or decreased.
- Quickly move beyond statistical analysis of high-throughput experimental data to novel biological insights, and the design of validation studies.
- Utilize powerful biological filters to quickly focus in on the results most relevant to your experimental model or experimental conditions.
Easily search the scientific literature and find insights most relevant to your experimental model or question
- Find information extracted by experts from the full text of the scientific literature, including Findings about genes, drugs, biomarkers, chemicals, cellular and disease processes, and signaling and metabolic pathways.
- Easily understand and interpret literature information through innovative, customizable, publication-quality graphical layouts that highlight key relationships and novel connections.
- Have confidence in your hypotheses and conclusions with the support of the unsurpassed accuracy and breadth of biological and chemical Findings in IPA.
Build dynamic pathway models to extend your understanding of your research systems
- Quickly and easily build your own pathway models and analyze your own experimental data.
- Understand the impact of new published research on your experiments through easy dynamic pathway modeling and frequent content updates.
- Explore beyond the constraints of "canonical" pathway views with a range of interactive tools for modeling upstream and downstream relationships, shortest path, and other relationships.
- Constrain the hypothesis space upfront by using contextual details to create relevant models that narrow in on pathway members by species, tissue and cell content, or disease.
- Complete the experiment to experiment workflow by leveraging reagent information within IPA.
Share your research and collaborate with your colleagues
- Share your customized pathways and analysis results with internal and external collaborators through interactive emails, lists, analysis summaries, and pathways.
- Share your project space to allow for on-going project collaboration.
- Create powerful, interactive, custom pathways to clearly represent your experimental models.
- Generate dynamic reports that describe the broader biological and therapeutic relevance of your pathways or gene lists.
Join your peers in using the most highly-referenced pathway solution
- Join the growing community of thousands of researchers in hundreds of pharmaceutical, biotech, government and academic institutions who use IPA every day to accelerate their research.
- Publish your research with the support of the most frequently cited pathway solution in the scientific peer-reviewed literature.
Capabilities
Analyze and Interpret Data
IPA significantly decreases the time it takes to get from data generation to biological insight. It is the fastest and most trusted way to analyze and interpret data – which is critical for identifying novel insights and publishing research.
IPA can be used for various large-scale technologies, including gene expression and SNP microarrays; RNA-Seq, microRNA, and proteomics experiments; and smaller-scale experiments that generate gene lists. Researchers can quickly narrow in on what is most important in a data set and discover relationships that may not have been studied in a particular context yet. IPA's user interface is intuitive to biologists because it was designed by biologists, with biological workflows and questions in mind.
IPA Core Analysis
IPA delivers a rapid assessment of the signaling and metabolic pathways, molecular networks, and biological processes that are most significantly perturbed in the dataset of interest. IPA predicts which transcription factors could be responsible for gene expression and whether those transcription factors are activated or inhibited. IPA also helps 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 key components of the IPA Core Analysis are:
- Signaling and Metabolic Pathways Analysis
- Cellular and Disease Process Analysis
- Molecular Network Analysis
- Contextual Data Analysis
- Transcription Factor Analysis
- Downstream Effects Analysis
These capabilities enable researchers to:
- Analyze data in the context of molecular mechanisms
- Relate molecular events to higher-order cellular and disease processes
- Relate molecular changes to organismal physiology and pathophysiology
- Visualize time course and dose response effects
- Interpret and integrate data from multiple platforms (e.g., genomics, proteomics, genotyping, miRNA) and with mixed identifiers
- Quickly focus on analysis results that are most closely aligned with your experimental model or question
- Compare affected pathways and phenotypes across platform, time, dose, or patient population
- Predict the activation or inhibition of transcription factors
- Predict the direction of downstream effects on biological processes and diseases
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IPA-Tox uses Toxicity Functions in combination with Toxicity Lists to link experimental data to clinical pathology endpoints, understand pharmacological response, and support mechanism of action and mechanism of toxicity hypothesis generation.
IPA-Biomarker identifies the most biologically relevant and promising molecular biomarker candidates from datasets generated at every step of the drug discovery process.
IPA-Metabolomics overcomes the metabolomics data analysis challenge by providing the critical context necessary to gain biological insight into cell physiology and metabolism from metabolite data.
Data Upload Wizard
Quickly upload data from multiple formats without time-consuming data formatting steps. Compare or analyze datasets from multiple experimental platforms with mixed gene and protein identifiers.
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Analysis Summaries
Creates an automated, focused, and summarized output of analysis results that can easily be emailed as an interactive PDF document.
Supported Species:
IPA supports the upload and analysis of human, mouse, rat, and canine identifiers, plus chemical identifiers. Additionally, IPA supports analysis of molecular data for the following species through ortholog mapping of Entrez Gene IDs:
- Arabidopsis thaliana (plant)
- Bos taurus (bovine)
- Caenorhabditis elegans (c. elegans)
- Canis lupus familiaris (canine)
- Danio rerio (zebrafish)
- Drosophila melanogaster (fruit fly)
- Gallus gallus (chicken)
- Macaca mulatta (Rhesus Monkey)
- Pan troglodytes (chimpanzee)
- Saccharomyces cerevisiae (yeast)
- Schizosaccharo-myces pombe (yeast)
Researchers can now avoid the time-consuming and manual mapping process formerly needed for analyzing data sets from these animal models. Predicted pathway modeling of data generated from these species enables biological interpretation. IPA supports the mapping of Entrez Gene ID's,GenBank, Refseq, and GenPept ID's. In addition, microarray ID mapping is supported for a subset of the new species.
Learn more about supported species, identifiers, and platforms here.
Search and Explore Biological and Chemical
Knowledge
IPA's Search & Explore capabilities offer researchers access to the most current Findings available on genes, drugs, chemicals, protein families, normal cellular and disease processes, and signaling and metabolic pathways. Use IPA's extensive repository of biological and chemical knowledge to get up to speed in a new area of research, or generate targeted search results and then act on those results to build interactive graphical representations of in vivo or in vitro experimental systems.
Search
Use Search to look for information on genes and chemicals, their impact on diseases and cellular processes, and their role in pathways. You can also access isoform-specific biology to explore each human locus.
- Build interactive pathways representing the key genes, chemicals, and processes in experimental systems of interest
- Validate experimental assumptions
- Generate testable hypotheses by using molecule or relationship filters to leverage only the Findings related to your experimental model
- Understand the biological effects of chemicals or microRNA interactions
- Determine which protein domains are impacted by splicing events, and review effect of isoform-specific differences on biological function and disease
Search for genes, proteins, metabolites, or chemicals that are:
- Clinical Biomarkers
- Localized to a specific cell compartment
- Targeted by FDA approved drugs or clinical candidates
- Involved in a particular disease or process
- Members of a specific protein or chemical family
- Most relevant by running combinations of searches to rapidly generate lists of genes with biological characteristics
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Use Reagent Viewbeta to locate reagent information for genes and proteins in your experimental system
- Design validation experiments to test hypotheses within specific experimental parameters
- Find reagents by application, species, or vendor
- Link directly to vendor websites for more information or to order
» Download our one pager to see how to get started!
ChemView
ChemView provides access to chemical content describing therapeutic information, target protein, toxicity, bioavailability, LD50, PK/PD, metabolism, CAS number, synonyms (including systematic name and brand names for drugs), chemical formula, and SMILES notation.
- Find novel intervention points in pathways by identifying chemical reagents or compounds that affect the activity of key players in pathways, networks, and cellular processes.
- Utilize chemical content to build pathways and working models representing compound mechanism of toxicity and mechanism of action.
- Include chemicals when generating networks and analyzing datasets.
- Add chemicals to custom pathways.
- Access drug and chemical information such as drug manufacturer, clinical trial, and link to NCT website for each trial displayed.
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Dynamic Signaling & Metabolic
Pathways
Use Ingenuity's extensive library of well-characterized signaling and metabolic pathways as a starting point for exploration and a bridge between novel discovery and known biology. Layer in novel insights, custom SBML pathways imported into IPA, drugs, and 'omics data.
- Explore beyond the boundaries of well-characterized signaling and metabolic pathways to incorporate the molecular relationships that are the most relevant to the experimental system being studied.
- Customize pathways using IPA's extensive molecular interaction content.
- Understand chemical effects on genes; find upstream activators, and downstream transcriptional targets of pathways.
- Understand experimentally demonstrated and predicted microRNA-mRNA relationships and explore biological roles and potential impacts.
- Drill down to the Findings curated from the scientific literature.
- Layer in expression, proteomic, and copy number data.
- Browse pathway libraries by function to quickly identify pathways most relevant to your biological question.
- Utilize descriptive pathway summaries to quickly clarify a pathway's relevance and identify key biological processes that are downstream of a pathway.
- Generate Pathway Reports that provide a broader understanding of the biological and therapeutic relevance of a pathway.
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My Pathways & Lists
Build custom libraries of pathways representing disease mechanisms, drug mechanism of action and mechanism of toxicity. Create custom, literature-supported signaling pathways with proteins of interest. Store collections of custom pathways and lists for subsequent core, IPA-Tox®, IPA-Biomarker®, or IPA-Metabolomics® analyses.
- Use the Build tools to edit and expand networks based on the molecular relationships most relevant to the project:
- Transcriptional networks
- Phosphorylation cascades
- Protein-Protein or Protein-DNA interaction networks
- microRNA-mRNA target networks
- Chemical effects on proteins
- Use Search results as building blocks for custom pathways
- Identify cross-talk between biological processes and pathways
- Understand whether gene lists and signatures are tightly connected at the molecular level
Path Explorer
Find relevant regulatory paths and physical interactions between genes of interest.
- Find biological paths that connect one set of genes to another.
- Identify regulatory events that lead from signaling events to transcriptional effects.
- Understand toxicity responses by exploring connections between drugs or targets and related genes or chemicals.
Communicate and Collaborate
IPA's tools and pathways are a quick and valuable way to share hypotheses and insights with other research teams and collaborators. Integrate knowledge from multiple sites and data repositories and easily share findings of interest in order to streamline the workflow and communicate more easily with colleagues.
Share
Facilitate teamwork between groups and the downstream dissemination of information by easily inviting specific collaborators to review and integrate analysis results, dataset files, analysis summaries, hypotheses, and pathways using Collaboration Workspaces. Advanced read/write protections ensure original work remains protected.
Report
Export results, tables of annotations, bibliographies, interactive analysis summaries, Pathway and List Reports, and high-resolution images to include in reports and presentations. Reference export management allows you to export references into EndNote or other formats.
Path Designer
Transform your networks and pathways in IPA into publication-quality pathway graphics rich with color, customized text and fonts, biological icons, organelles, and custom backgrounds.
- Expand and explore pathways using the high quality content stored in IPA.
- Complete your entire workflow - from data analysis to data sharing and publication - within IPA.
- Quickly create custom graphics with an intuitive and easy-to-use interface.
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Interactive Pathways
Insert fully referenced pathways that provide access to the underlying biological information into e-mails or presentations.
Integrate with in-house software applications or 3rd party software tools
The IPA Integration Module enables life science researchers to access the high quality, detail-rich biological and chemical knowledge in IPA directly from their internal websites, applications, and gene catalogues, as well as from internal research reports, e-mails and other shared documents that are part of their daily research workflows. This easy-to-implement module increases the utility of internal web sites, search portals, and research reports by providing direct links to the content and analysis capabilities in IPA.
Click here to read more, or download the whitepaper. |
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Content
IPA leverages the Ingenuity® Knowledge Base, a repository of biological interactions and functional annotations created from millions of individually modeled relationships between proteins, RNAs, genes, isoforms, metabolites, complexes, cells, tissues, drugs, and diseases. These modeled relationships, or Findings, include rich contextual details, link to the original article, and are manually reviewed for accuracy. The Ingenuity Knowledge Base provides you with a reliable resource for searching relevant and substantiated knowledge from the literature, and for interpreting experimental results in the context of larger biological systems.
The knowledge used by IPA is unique because of its:
- Unparalleled Structure and Contextual Details
Ingenuity structures all of the biological and chemical content in the Ingenuity Knowledge Base using the Ingenuity® Ontology. By structuring the content, we enable computation and inferencing, ensure semantic and linguistic consistency, and support the integration and mapping of content from multiple sources. Unlike other ontologies, the Ingenuity Ontology is comprehensive. This level of detail helps us capture relevant contextual details from the literature such as species specificity, cell type/tissue context, site and type of mutations, direction of change, post-translational modification sites, epigenetic modifications, and experimental methods used. These contextual details are what make our Findings different from other solutions that only report on simple "A to B" relationships. Ingenuity Findings ensure that you can access knowledge and generate hypotheses that are highly relevant to your specific experimental system.
- Expert review process for trusted information
All information in the Ingenuity Knowledge Base is manually reviewed by experts for accuracy and detail, and follows strict quality control processes.
- Broad and Timely Content
The Ingenuity Knowledge Base is updated weekly to include information published as recently as the prior week. It is the largest knowledge base of its kind, including modeled relationships between proteins, genes, complexes, cells, tissues, drugs, pathways, and diseases. It includes information from a wide range of published biomedical literature, textbooks, reviews, internally curated knowledge (such as pathways), and a variety of trusted third party sources and databases.
You can learn more about the Ingenuity Knowledge Base by clicking here.
Biological and Chemical Information
The Ingenuity Knowledge Base includes modeled relationships between chemicals, proteins, genes, mutations, complexes, cells, cellular components, tissues, drugs, cellular processes, diseases and clinical phenotypes, allowing you to integrate a wide variety of information in a single place. IPA includes relationships that have been manually curated from the literature (Ingenuity® Expert Findings) as well as information that has been manually reviewed and automatically extracted from the literature (Ingenuity® ExpertAssist Findings). IPA allows you to filter and choose which information you’d prefer to use.
In addition to these Findings, IPA includes manually reviewed content from selected third party sources (Ingenuity® Supported Third Party Information), including:
- Entrez Gene
- RefSeq
- OMIM
- GWAS Database
- Gene Ontology
- Human Metabolome Database (HMDB)
- GNF Tissue Expression Body Atlas
- NCI-60 Cell Line Expression Atlas
- KEGG metabolic pathway information
- LIGAND enzyme/substrate reactions
- BIND, DIP, MINT, MIPS, BIOGRID, INTACT, COGNIA protein-protein interactions
- TarBase
- TargetScan
- miRecords
- Clinicaltrials.gov
- Drugs@FDA
- Mosby’s Drug Consult
- Goodman & Gilman’s Pharmacological Basis of Therapeutics
- DrugBank
- Hazardous Substance Database (HSDB)
- Chemical Carcinogenesis Research Information System database (CCRIS)
IPA also contains information that has been manually curated by Ingenuity scientists (Ingenuity® Expert Knowledge) and that describes:
- FDA approved drugs and clinical candidates
- Cell Signaling, Metabolic, and Disease Pathways
- Toxicity Lists and Pathways
- Predicted and experimentally demonstrated microRNA targets
To learn more about the types of findings and content sources in the Ingenuity Knowledge Base, please click here.
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