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bigRing-AI-powered platform for knowledge graphs.

AI-powered insights through causal diagrams.

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bigRing

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Overview of bigRing

bigRing is an innovative AI-powered platform designed to integrate data from various sources and apply causal diagrams to uncover complex cause-effect relationships. It primarily supports R&D processes, particularly in biomedicine, by simplifying complex data analysis, enhancing collaboration, and enabling efficient decision-making. A key feature is its ability to create a unified knowledge graph enriched with causal relationships, which can aid in personalized medicine, target identification, and drug discovery. For example, bigRing has been used to map biochemical reactions from the KEGG database, integrating this data with proprietary information to improve drug development. It also enables real-time analysis of complex datasets, reducing cognitive load for researchers, and improving team collaboration by preserving knowledge across teams.

Key Functions of bigRing

  • Data Integration

    Example Example

    Mapping biochemical reactions from the KEGG database onto a bigRing graph model.

    Example Scenario

    A pharmaceutical company uses bigRing to integrate and analyze data from public databases and internal research to accelerate the process of identifying drug targets. bigRing simplifies the integration of these diverse datasets, enabling the team to focus on discovering actionable insights rather than dealing with data compatibility issues.

  • Causal Relationship Analysis

    Example Example

    Using the bigRing Causality Model™ to identify explicit cause-effect relationships in drug interactions.

    Example Scenario

    A research team studying the effects of ethanol on liver cancer uses bigRing’s causal mechanism to accurately map out how ethanol upregulates cancer pathways. This explicit causation modeling helps them identify more precise therapeutic targets and improve treatment recommendations.

  • Real-Time Data Analysis

    Example Example

    bigRing’s Cognit tool for real-time filtering and sorting of datasets.

    Example Scenario

    A hospital utilizes bigRing to analyze patient data in real-time to customize treatment plans. With the platform’s real-time analysis, the medical team can adjust parameters, highlight specific causal pathways, and improve the precision of treatments tailored to individual patients.

Ideal User Groups for bigRing

  • Pharmaceutical and Biotech Companies

    These organizations benefit from bigRing’s ability to integrate diverse data sources and identify causal relationships. By streamlining the drug discovery process, bigRing helps these companies reduce time to market and costs associated with R&D, while enhancing precision in target validation and drug development.

  • Academic and Research Institutions

    Research teams that work on cutting-edge scientific discoveries in the biomedical field can use bigRing to collaborate more effectively and navigate complex datasets. The platform supports interdisciplinary collaboration and peer review, fostering innovation in areas such as personalized medicine and genomics.

How to Use bigRing

  • Visit aichatonline.org for a free trial without login, also no need for ChatGPT Plus.

    This is the first step for exploring bigRing’s AI-powered platform. You can start with a free trial, no registration required, and no premium services are necessary.

  • Select data sources or knowledge areas.

    Once inside, choose the relevant data or knowledge fields for your research or problem-solving needs. The system supports multiple data formats and sources including structured, semi-structured, and unstructured data.

  • Build or import a causal diagram.

    Use bigRing’s causal diagrams to map relationships between data points. You can either build diagrams from scratch or import existing data models for enhanced analysis.

  • Analyze data and run simulations.

    Run advanced real-time analysis on the knowledge graphs, utilizing bigRing’s AI capabilities to uncover insights and generate actionable outcomes.

  • Collaborate and iterate.

    Collaborate with team members by sharing insights and updating the causal diagrams. The platform allows continuous improvement through feedback and co-creation with stakeholders.

  • Data Integration
  • Real-Time Insights
  • Drug Discovery
  • Target Validation
  • Causal Analysis

bigRing Q&A

  • What is bigRing?

    bigRing is an AI-powered platform that integrates complex datasets and visualizes relationships using causal diagrams. It helps researchers and professionals accelerate problem-solving, especially in biomedical R&D, by simplifying the understanding of complex systems.

  • How does bigRing help in biomedical research?

    bigRing enhances biomedical R&D by supporting data integration and analysis, particularly in drug discovery and personalized medicine. Its causal diagrams help identify and validate biological targets, accelerating discoveries and reducing research timelines.

  • Is coding required to use bigRing?

    No, bigRing is a no-code platform, meaning it does not require users to have programming expertise. The system’s intuitive interface and automated workflows allow even non-programmers to utilize its full range of capabilities.

  • How does bigRing ensure data security?

    bigRing uses strong encryption, role-based access control, and complies with privacy regulations like GDPR. Data is stored securely on cloud or on-premise servers, with regular security audits to maintain safety and integrity.

  • What types of data can bigRing integrate?

    bigRing can integrate structured, semi-structured, and unstructured data from various sources including public datasets, scientific literature, proprietary databases, and clinical trial data.