• INGENUITY Pathway Analysis

INGENUITY Pathway Analysis

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Ingenuity® Pathway Analysis ( IPA ) 是一款一体化的云端数据分析平台,可实现基因表达、miRNA和SNP微阵列及代谢组学、蛋白质组学和RNA-seq等实验数据的分析和生物学解释,以帮助研究者快速分析理解实验数据。IPA的引用文献已超过13000篇。建议以大课题组或院所形式进行购买。

IPA 所基于的后台是一个高度结构化的 INGENUITY Knowledge Base 数据库。该数据库历经15年的海量知识数据投入;拥有 500 名 phD 阅读文献;对 700 多种权威杂志进行全文阅读,3000 种杂志进行摘要阅读,目前,该数据库存储了 510 万条以上的生物实验发现,130 万种互作信息和 3 万种以上分子信息;此外,还构建了完整的功能疾病分类数据库,绘制了 800 种信号通路、代谢通路等;并与公共数据库进行全面合作,保持每周更新一次。INGENUITY Knowledge Base 为众多以发现和创造为己任的科研工作者们,提供了及时、准确的生物信息学数据服务。


IPA 的作用并不局限于通路分析,也可对基因表达、microRNA、SNP 微阵列等数据;代谢物组学和蛋白质组学的实验数据;以及一些小规模实验数据进行分析,还可以搜索到有关基因、蛋白质、化学品和药物的信息,并能为您创建一个系统的实验交互模型。该软件已在世界顶尖制药公司和科研机构中广泛使用,至今引用该软件发表的高水平科研文献已超过 14000 篇。


INGENUITY Pathway Analysis / IPA 的 QQ 学习交流群:475878928。


Ingenuity® Knowledge Base

  • 来自数千种杂志的生物学信息,内容涵盖蛋白质、基因、SNP、miRNA、复合物、细胞、组织、药物、通路和疾病信息等;

  • 500 名 PhD 每天阅读 300 种权威杂志全文和 3000 种杂志摘要;

  • 超过 500 万条生物学信息、130 万种互作信息、3 万种以上分子信息、800 种信号通路、代谢通路,经过多轮人工质控以及每周更新;

  • 每三个月对分析工具进行算法改进和功能更新,紧贴研究最前沿。


应用

IPA 帮助您揭示以下列领域数据背后的真相:

  • 转录组学: IPA 几乎可以解决所有转录组相关的生物学问题;

  • 生物标记物发现:从实验数据集中识别最相关、最可能的候选生物标志物;

  • miRNA 研究:结合筛选工具和 miRNA-mRNA 数据发现 miRNA 的潜在调控机制;

  • 毒物基因组学: 提供化合物毒性及安全评估信息,提供全面的药理作用、药物代谢途径和毒性作用机制信息;

  • 代谢组学:提供关键的调控信息,帮助理解代谢组数据中从细胞形态学到代谢作用机制的信息;

  • 药物再定位 : 通过药物对不同疾病组织的刺激结果的表达谱分析,发现已知药物的新应用领域;

  • 蛋白质组学:深入了解蛋白表达机制和相关生物学过程;

  • 因果网络分析:找到特定病理学状态下激活的基因,研究其成为候选治疗靶标的可行性。



IPA Advanced Analytics

专有的 Causal Network Analysis 工具

专有的 Causal Network Analytics 工具利用强大的算法可生成多级别的调控网络,对数据集中的基因表达变化做出合理解释。Upstream Regulator Analysis 工具能够发现与数据集中发生改变的靶标直接关联的调节因子(包括转录因子、细胞因子、激酶等),它们的激活或抑制可能导致了所观察到的变化。

用户可以快速浏览与特定疾病或表型最相关的调控网络,随后将最感兴趣或最相关的因果网络优先作为解释数据集中的模式的假说。此外,通过使用分子、疾病、功能或表型等参数对所获得的网络进行优先排序,用户能够发掘在因果网络与研究或治疗领域之间的更远的联系。

BioProfiler 工具

BioProfiler 通过搜索 INGENUITY® Knowledge Base,生成疾病、表型和生物过程(如细胞凋亡)的分子描述,并列出与描述条目相关的所有基因和化合物。直观和全面的结果展示,使用户能够针对手头的研究对象,对基因和化合物进行发现、筛选和优先排序。用户可以针对感兴趣的分子,找到具有因果关联性的基因,筛选特定的遗传学证据或种属,并探索其与相似疾病或表型之间的关联。然后,利用 IPA 的各项功能,对已揭示的数据进行信号通路上下游的分析。


IPA 重要说明书-含算法


相关链接

本网站内的 IPA 教程

IPA 登录

IPA 相关文献

IPA 官网培训课程通知

PATHWAY ANALYSIS OVERVIEW VIDEO 

QIAGEN 生信产品介绍


官网产品功能介绍

IPA has a broad set of features that allow you to quickly understand and visualize your data

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Comparison Analysis

Quickly visualize trends and similarities across analyses using heat maps for Canonical Pathway, Downstream Effects, Upstream regulators and Causal Network Analyses. Prioritize by score, hierarchical cluster or trend.

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Human and Mouse Isoform View

Understand the structure and function of both human and mouse isoforms (splice variants). For each gene, toggle between human or mouse RefSeq and Ensembl to visualize associated isoforms on the Isoform View.

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Regulator Effects

Provides insights into your data by integrating Upstream Regulator results with Downstream Effects results to create causal hypotheses that explain what may be occurring upstream to cause particular phenotypic or functional outcomes downstream.

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Causal Network Analysis

The new Causal Network Analysis provides a comprehensive approach to identifying upstream molecules that control the expression of the genes in your datasets. Expanding beyond "direct" or "single hop" relationships between the upstream regulator and the target molecules in the dataset, Causal Networks uncovers networks of regulators that connect to the dataset targets. Focus on the networks that are of highest relevance by scoring the resulting causal networks against molecules or diseases/functions of interest.

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Disease View

Provides details associated with the disease or biological function such as molecules associated with that disease or function, known drug targets, drugs known to target those molecules, and more.

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Interactive Disease and Functions Nodes

Interactive visual exploration of causality between molecules and disease, function, or phenotypes from a network or My Pathway.

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BioProfiler

Quickly profile a disease or phenotype by understanding its associated genes and compounds. Identify genes known to be causally relevant as potential targets or identify targets of toxicity, associated known drugs, biomarkers and pathways.

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Upstream Regulator Analysis

Predict upstream molecules, including microRNA and transcription factors, which may be causing the observed gene expression changes.

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Mechanistic Networks

Automatically generate plausible signaling cascades describing potential mechanism of action leading to observed gene expression changes.

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Downstream Effects Analysis

Identify whether significant downstream biological processes are increased or decreased based on gene expression results.

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Pathway Analysis, Canonical Pathways, Overlapping Pathways, Pathway Import and scoring

Pathway Analysis, Canonical Pathways, Overlapping Pathways, Pathway Import and scoring. Determine most significantly affected pathways.

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Network Analysis

Build and explore transcriptional networks, microRNA-mRNA target networks, phosphorylation cascades and Protein-Protein or Protein-DNA interaction networks. 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.  edit and expand networks based on the molecular relationships most relevant to the project.

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MicroRNA Target Filter

Reduce the number of steps it takes to confidently, quickly, and easily identify mRNA targets by letting you examine microRNA-mRNA pairings, explore the related biological context, and filter based on relevant biological information as well as the expression information.  The microRNA Target Filter in IPA provides insights into the biological effects of microRNAs, using experimentally validated interactions from TarBase and miRecords, as well as predicted microRNA-mRNA interactions from TargetScan. Additionally, IPA includes a large number of microRNA-related findings from the peer-reviewed literature.

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Tox Lists and Tox Functions

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.

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Molecule Activity Predictor (MAP)

Interrogate sub-networks and Canonical Pathways and generate hypotheses by selecting a molecule of interest, indicating up or down regulation, and simulating directional consequences of downstream molecules and the inferred activity upstream in the network or pathway

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Isoform View

Quickly move beyond statistical analysis of high-throughput RNA-Seq data to understand the biological implications of your data.  Identify significantly regulated isoforms in your experiment and determine their potential impact using information about functional protein domains and isoform-specific literature

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Gene and ChemView

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.

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Biomarker Filter

Rapidly identify the best biomarker candidates based on biological characteristics most relevant to the discovery study.

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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.




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