Model, analyze, and understand the complex biological and chemical systems at the core of life science research with IPA
Peer Reviewed and Widely Adopted
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Market Leading Pathway Analysis
Unlock the insights buried in experimental data by quickly identifying relationships, mechanisms, functions, and pathways of relevance.
Predictive Causal Analytics
Powerful causal analytics at your fingertips help you to build a more complete regulatory picture and a better understanding of the biology underlying a given gene expression study.
NGS/RNA-Seq Data Analysis
Get a better understanding of the isoform-specific biology resulting from RNA-Seq experiments.
Quickly analyze your data to identify key insights with IPA
Transcriptomics
IPA can help with almost any transcriptomics-related question or application
Biomarker Discovery
Identifies the most promising and relevant biomarker candidates within experimental datasets
microRNA Research
Combines filtering tools and microRNA-mRNA content to provide insight into the biological effects of microRNAs
Toxicogenomics
Delivers a focused toxicity and safety assessment of candidate compounds, and provides a more complete understanding of pharmacological response, drug mechanism of action, and mechanism of toxicity
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
Drug Repositioning
Expression profiling of approved drugs and comparison to profiles of diseased tissue can lead to discovery of new uses for these already approved entities
Proteomics
Perform a comprehensive analysis of your proteomics for a deep understanding of proteins and related biological processes
Target Discovery
Genes that are shown to be activated in a pathological condition may serve as promising targets for therapeutic development efforts
The Ingenuity Knowledge Base
IPA has a broad set of features that allow you to quickly understand and visualize your data
*Available for an additional cost.
IPA is useful in a wide range of applications at gaining valuable insight into your genomics data
Biomarker Discovery
Identify the most promising and relevant biomarker candidates most relevant to the study within the experimental data.
Metabolomics
Contextualize your metabolomics data with rich pathway and process information from the Ingenuity Knowledge Base.
MicroRNA Research
Identify the most biologically relevant targets in your microRNA research.
Proteomics
Answer the biological questions the researchers you had in mind when you designed your proteomic experiment.
Toxicogenomics
Generate a focused toxicity and safety assessment of candidate compounds that are being examined using toxicogenomics approaches.
Causal Network Analysis
Build a more complete regulatory picture and a better understanding of the biology underlying a given gene expression study.
Explore Our Webinars and see how the scientific community has used IPA to create novel discoveries
IPA 2013 Spring Release [48:24 minutes]
Presented by Dr. Stuart Tugendreich, Scientific Director, IPA
The 2013 IPA Spring Release is here! Powerful new functionality enables you to upload, find, and compare datasets, and understand causal connections between diseases, genes, and networks of upstream regulators. Stuart Tugendriech, PhD, Scientific Director, IPA from Ingenuity Systems gives an overview of the new IPA capabilities in the release, as well as a use case utilizing the new features and how IPA helps to Discover Causal Connections. Faster.
Ingenuity Knowledge-Based Tools for Comprehensive Interpretation of Variant & Gene Expression Data [56:16 minutes]
Presented by Jean-Noel Billaud and Megan Laurance
Ingenuity Staff Scientists Jean-Noel Billaud and Megan Laurance present strategies for integrated analysis and interpretation of variant and gene expression data generated from cell lines representative of 2
breast cancer subtypes: Claudin-Low and Luminal. These subtypes represent different disease entities associated with specific molecular alterations and histo-clinical features. Interrogating these samples at both the variant and transcript level with Ingenuity's Variant Analysis and IPA software presents a powerful approach to drawing clear molecular
paths from variants and gene expression changes to phenotypes relevant to these disease subtypes including Epithelial-to-Mesenchymal Transition and Metastasis.
A Bioinformatician's Guide to Lung Cancer: Wnt7a Signaling and Beyond [40:13 minutes]
Presented by Dr. Michael Edwards, Assistant Professor at the University of Colorado Health Sciences, Denver.
This webinar discusses an important antitumor pathway in lung cancer (Wnt7a signaling) as a framework to explain the bioinformatic analysis process using IPA. Topics covered include biological function and pathway analysis, network construction, and identifying and interpreting upstream regulators.
IPA and Coronary Artery Disease: A Case Study from Harvard [36:23 minutes]
Presented by Dr. Jochen Danny Muehlschlegel, M.D., Harvard Medical School
See how IPA was used for the discovery of novel pathways of affected genes in coronary artery disease. Cardiopulmonary bypass (CPB) with cardioplegic arrest is associated with ischemia leading to metabolic substrate depletion, reperfusion injury, apoptosis and necrosis. The study hypothesized that human left ventricular (LV) myocardium responds differently to the stress of (CPB) depending on the presence or absence of coronary artery disease (CAD). Therefore, they assessed differences in gene expression in patients undergoing aortic valve replacement (AVR) with (CPB) prior to and after cardioplegic arrest using whole-genome transcriptional profiling.
The Role of microRNAs in Kidneys of Hypertensive Patients [23:09 minutes]
Presented by Aimee Jackson, Ph.D.
MicroRNAs are small, non-coding RNAs that function as central regulators of gene expression and development. These regulatory molecules have been implicated in a wide range of normal and pathological activities, including embryonic development, cancer, inflammation, cardiovascular disease and viral infections. We explored the possibility that microRNA dysfunction in the kidney might contribute to hypertension, a significant health issue. We analyzed mRNA and microRNA expression profiling data from kidneys of untreated hypertensive patients and normotensive patients to identify microRNAs, microRNA targets, and gene networks that are dysregulated in hypertension. The results of these analyses identify microRNAs and their targets that could be biomarkers or therapeutic targets for hypertension.
Differential Expression of Focus Genes Associated Feed Efficiency [41:26 minutes]
Presented by Dr. Walter Bottje, Professor, Dept. of Poultry Science, University of Arkansas
Global RNA expression in breast muscle obtained from a male broiler line phenotyped for high or low feed efficiency (FE) was investigated using microarray analysis. By using an overlay function of IPA in which canonical pathways can be projected onto a set of genes, differentially expressed focus genes were identified. We selected 130 out of 260 possible canonical pathways in the IPA program that would likely be associated with normal metabolic activities and did not select those that were obviously tissue or disease specific. The results of this study provide additional insight into gene expression in muscle associated with the phenotypic expression of feed efficiency in broilers.
Scientific Webinar What You Should Know About Your 'Omics Data [58:11 minutes]
Presented by Tim Bonnert, PhD, Ingenuity Systems
Learn how you can now predict the cause and effect of changes in gene expression and predict the activation or inhibition of upstream molecules, such as cytokines, kinases, microRNA, receptors and many more! Included in the webinar will be an example of the biological analysis and interpretation of a gene expression data set from a study of Docetaxel Resistance in the Breast Cancer Cell Line MCF-7.
Distinct Gene Expression Profile of Regulatory T Cells in Prostate Cancer [45:00 minutes]
Presented by Simo Arredouani, Assistant Professor of Surgery at Harvard Medical School
The inhibitory role of regulatory T-cells (Tregs) in cancer is now well established. Furthermore, inhibition of Treg function has been shown both experimentally and clinically to improve the immune response towards a variety of cancers. Developing new and more effective strategies interfering with the function of Tregs in cancer requires a deep understanding of Treg suppressor machinery, and a thorough dissection of the molecular elements that orchestrate their differentiation from T cells.
A Combined Biological and Bioinformatic Analysis of Primary and Metastatic Tissues from NGS Ewing's Sarcoma Patients [58:00 minutes]
Presented by Jean-Noel Billaud, Ph.D., Ingenuity Systems and and Sylvain Foissac, Ph.D., Integromics
The Ewing's Sarcoma family of tumors is a category of cancers that predominantly affects teenagers between the ages of 10 to 20. Learn how Ingenuity Systems' IPA software and Integromics' SeqSolve software were used to investigate Ewing's Sarcoma patient samples generated from Helicos' NGS technology. We will present a combined bioinformatic and biological analysis of Ewing's Sarcoma patient samples, focusing on the differences between primary and metastatic tissues. IPA was used to analyze the significantly regulated genes and Integromics' NGS SeqSolve software was used to prepare the RNA-Seq data. IPA's new transcription factor analysis tool and downstream effects map were used to help narrow down targets and visualize the biological networks.
Using IPA to Analyze Illumina RNA-Seq Data Reveals Abundance-Specific Biological Signatures in Alzheimer's Disease [33:44 minutes]
Presented by Darryl Gietzen, Ph.D., Ingenuity Systems
This webinar discusses how IPA was used to interpret Alzheimer's disease biology by comparing Illumina RNA-Seq data from Alzheimer's disease (AD) and normal brain samples. This analysis revealed very specific biological changes in certain classes of transcript expression, demonstrating how the unique benefits of RNA-Seq can help characterize disease changes.
A diverse group of researchers are using IPA to understand and interpret complex biological systems. Meet a few and learn more about how they are using IPA.
"I'm excited to leverage the new Molecular Activity Predictor (MAP) and Causal Network Analysis in Ingenuity's IPA. The powerful analytic capability for insilico data prediction to infer upstream activity in the network or pathway in IPA allows me to go beyond my own knowledge to further understand the biology."
"In our study, we coupled analysis with Ingenuity's IPA and microarray data to evaluate the impact of exercise and muscle aging by measuring the variation in the products being made. The analysis determined that the genetic regulators of age-related genes were distinct and unrelated to the regulators of exercise-influenced genes. Using IPA, we were able to capture the relevant networks more easily and with far less cost than traditional methods."
"We've recently seen that genes associated with critical cellular functions are often regulated post-transcriptionally. Ingenuity's Upstream Regulator in IPA allows for the identification of these important regulators from expression data sets and is going to completely change the field of bioinformatics by identifying these potential regulators and not limiting the analysis to just the transcriptome."
Ingenuity offers online training with our product technicians and web semimars presented by notable third parties, sign up below!
Getting Started with IPA [27:00 minutes]
This video is recommended for all new or beginning users. It introduces IPA and will show you how to upload and run an analysis to identify the functions, pathways, and networks most relevant to your data.
Online Training
Data Upload and Analysis
This session dives more deeply into data upload and analysis in IPA. You’ll see how to rapidly understand biological processes most perturbed in your dataset, or across multiple timepoints or doses. You’ll also get an introduction to functional analysis, significance calculations, and how IPA can help you understand the cause and effect of gene expression changes in your experiment.
Data Upload: Part 1 Data Upload
- Thursday, May 2, 10:00 AM PDT
- Monday, May 13, 10:00 AM CEST
- Thursday, May 16, 10:00 AM PDT
- Thursday, May 30, 7:00 AM PDT
- Monday, June 10, 10:00 AM CEST
- Thursday, June 13, 10:00 AM PDT
- Thursday, June 27, 10:00 AM PDT
Data Upload: Part 2 Result Interpretation
- Thursday, April 25, 10:00 AM PDT
- Thursday, May 9, 7:00 AM PDT
- Monday, May 20, 10:00 AM CEST
- Thursday, May 23, 10:00 AM PDT
- Thursday, June 6, 10:00 AM PDT
- Monday, June 17, 10:00 AM CEST
- Thursday, June 20, 7:00 AM PDT
Search and Explore
Explore how IPA’s knowledge and discovery tools allow you to relate the most recent literature findings to your experimental data, create interactive and customized pathways using tools such as species/tissue highlights and complex searches, and help in hypothesis generation.
Support Documents
The Basics
- new IPA Spring Release Overview
- new IPA Product Datasheet
- new IPA Advanced Analytics Flyer
- new 2013 IPA Spring Release Slides with Mouse Welding Case Study
- IPA-Tox Datasheet
- Guidelines for Citing IPA in Publications
- new File Format Specs for Uploading Data with Metadata
IPA White Papers – Explore IPA's capabilities
- new Maximizing the Value of NGS and Gene Expression Experiments: Strategies to Streamline Data Analysis and Interpretation for Actionable Research Outcomes
- new Summary of Maximizing the Value of NGS and Gene Expression Experiments: Strategies to Streamline Data Analysis and Interpretation for Actionable Research Outcomes
- A Novel Approach to Predicting Upstream Regulators
- Ingenuity Upstream Regulator Analysis in IPA
- Ingenuity Downstream Effects Analysis in IPA
- Using a Novel microRNA Target Filter to Prioritize Candidate Melanoma Biomarkers
- Best Practices for Assessing Toxicity throughout the Drug Discovery Process: Toxicogenomics
- Analysis of Metabolomics Data Including Cross-Platform Integration with Transcriptomics Data from a Diabetic Mouse Model
- IPA Network Generation Algorithm
- Calculating and Interpreting the p-values for Functions, Pathways and Lists in IPA
Applying IPA
- new Feature Highlight – BioProfiler
- new Feature Highlight – Molecule Activity Predictor (MAP)
- new Feature Highlight – Causal Network Analysis
- Feature Highlight – Mechanistic Networks
- Feature Highlight
Upstream Regulator and Downstream Effects Analysis
- Feature Highlight – Overlapping Canonical Pathways
- Feature Highlight – Human Isoform View with Expression Overlay
- Feature Highlight – microRNA Target Filter
SCIENTIFIC POSTERS
- Using IPA to explore microRNA impacts on molecular mechanisms of disease
- Using RNA-Seq Data to Gain Insight into Disease Mechanisms in IPA
- In Silico Approaches Inform Drug Repurposing Strategies for the Treatment of Infectious Disease
- Network Analysis Suggests Regulation of Cancer-relevant Pathways by the Tumor Suppressive miR-365
- Insights into the EMT Process via Integrated Analysis of RNA-Seq Data Generated from Claudin-Low and Luminal Breast Cancer Cell Lines
IPA VIDEOS
- Discover Causal Connections. Faster. IPA Winter Release 2012 [35:41 minutes]
- How to Unlock the Biological Meaning of Complex 'Omics Data [3:27 minutes]
- new IPA Spring Release 2013 [48:25 minutes]
- IPA Winter Release 2012 [4:29 minutes]
- IPA Summer Release 2012 [4:32 minutes]
- IPA Spring Release 2012 [3:48 minutes]
- IPA Downstream Effects Analysis [2:40 minutes]
- IPA Transcription Factor Analysis [2:56 minutes]
