Enhance Usability of Multimodal, Multiomic Data
Seamlessly unify complex, multimodal datasets and empower researchers
with AI-driven tools designed to expedite discoveries
Resource
Connect 'omics, clinical, and histology data into a single repository enhancing discoverability and usability
Automate data harmonization using AI-powered transformations, drastically reducing the time spent on manual data wrangling
.svg)
Discovery
Empower researchers with user-friendly, natural language interfaces that enable complex data navigation without the need for coding expertise
“As research organizations access more data from EHRs to genetic sequencing to imaging, research datasets are getting larger and more disparate. Researchers lose precious time and resources trying to connect patient data from these disparate systems into a unified patient view. Our partnership with Manifold on a modern technology infrastructure is enabling us to respond to far more research requests with less manual effort and cost.”
Comprehensive Cancer Center
Simplify data exploration with an intuitive interface for browsing and searching research data in the semantic space of disease types, histologies, and biomarkers
Easily build cohorts, assess feasibility, cross-tab outcomes with treatments, and analyze data using an AI-powered natural language interface.
Create and publish data dashboards for a variety of purposes, from enabling self-service data discovery to monitoring data quality.
Collaborate seamlessly with other researchers by integrating data, transformations, notes, and comments in our platform.
Work with data on a modern data stack already mapped to controlled vocabularies like ICDO3, NAACR, AJCC and annotated with COSMIC, ClinVar, and PharmGKB.
Rapidly integrate your source data the optimized data model, abstract structured information from unstructured EMR notes and images, and automatically improve your data quality.
Query for specific variants in seconds and transform raw sequencing data using bioinformatics pipelines for alignment, variant calling, and annotation.
Leverage purpose-built user interfaces tailored specifically for researchers, offering a seamless alternative to navigating traditional database queries, tables, and columns.
Interact with data through natural language chat interfaces, eliminating the need for complex coding and queries.
Resources
.png)
The Role of a Secure Trusted Research Environment in Meeting NIH’s Updated Guidance to Genomic Data Sharing Policy
As the research community continues to rely on data shared by the National Institutes of Health (NIH), ensuring the security of that data continues to be an important requirement. Last year, the NIH issued an implementation update to the NIH Genomic Data Sharing Policy (GDS Policy), which outlines requirements for researchers accessing, storing, or processing large-scale human and non-human genomic data generated from NIH-funded research. The update was designed to continue to promote responsible data management and access under the GDS Policy and ensure the broad and responsible sharing of NIH genomic data for research that advances human health.
The Role of a Secure Trusted Research Environment in Meeting NIH’s Updated Guidance to Genomic Data Sharing Policy
As the research community continues to rely on data shared by the National Institutes of Health (NIH), ensuring the security of that data continues to be an important requirement. Last year, the NIH issued an implementation update to the NIH Genomic Data Sharing Policy (GDS Policy), which outlines requirements for researchers accessing, storing, or processing large-scale human and non-human genomic data generated from NIH-funded research. The update was designed to continue to promote responsible data management and access under the GDS Policy and ensure the broad and responsible sharing of NIH genomic data for research that advances human health.
%20(1540%20x%20513%20px).png)
Enhancing Access and Usability of Multimodal Data: Building a Cancer-Specific Data System to Accelerate Research at Indiana University
The landscape of cancer research is rapidly evolving with the integration of multimodal data, including tissue analysis, clinical records, genomic sequencing, and imaging. By harnessing this rich array of cancer-specific data, researchers gain a comprehensive understanding of disease, leading to more accurate diagnoses and personalized treatments.
Enhancing Access and Usability of Multimodal Data: Building a Cancer-Specific Data System to Accelerate Research at Indiana University
The landscape of cancer research is rapidly evolving with the integration of multimodal data, including tissue analysis, clinical records, genomic sequencing, and imaging. By harnessing this rich array of cancer-specific data, researchers gain a comprehensive understanding of disease, leading to more accurate diagnoses and personalized treatments.
Accelerating Clinical Research: Harnessing Multi-modal Data, AI, and Secure Collaboration
Join experts from Indiana University, Manifold, and Snowflake for an on-demand eWebinar where you'll learn how to break down data silos, integrate and analyze large-scale clinical and multi-modal data, and collaborate securely with both internal teams and external institutions. Discover how to leverage AI to automate data operations and surface insights faster, enabling more efficient and impactful research.
Accelerating Clinical Research: Harnessing Multi-modal Data, AI, and Secure Collaboration
Join experts from Indiana University, Manifold, and Snowflake for an on-demand eWebinar where you'll learn how to break down data silos, integrate and analyze large-scale clinical and multi-modal data, and collaborate securely with both internal teams and external institutions. Discover how to leverage AI to automate data operations and surface insights faster, enabling more efficient and impactful research.