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What is Qlucore Omics Explorer?

Qlucore Omics Explorer is crafted to be intuitive, removing the need for specialized bioinformatics expertise when analyzing and exploring your Omics and NGS datasets. This software acts as a self-service platform for next-generation bioinformatics in various sectors including life sciences, biotechnology, and educational institutions. It boasts a powerful and flexible visualization-based data analysis tool that utilizes advanced statistical techniques, providing immediate results and facilitating the quick exploration of large datasets. Designed to fit into the workflows specific to your research, it significantly improves the productivity of your investigations. By integrating real-time visualization with complex statistical methods and adjustable selection options, you can rapidly assess your results. Users are empowered to define their own workflows and starting points, which allows for a personalized exploration that meets their specific needs. This degree of control lets researchers customize their analyses, ensuring that the software can easily adapt to a wide range of experimental frameworks. Ultimately, this makes Qlucore Omics Explorer a versatile and essential tool for advancing research projects across diverse fields.

What is GeoMx Digital Spatial Profiler (DSP)?

Effectively tackle the challenges posed by tissue heterogeneity and the complex nature of microenvironments through the use of the GeoMx Digital Spatial Profiler (DSP), which is distinguished as the most adaptable and robust spatial multi-omic platform designed for the analysis of both FFPE and fresh frozen tissue samples. Unlike other spatial biology tools, GeoMx provides a non-destructive method for profiling RNA and protein expression across diverse tissue compartments and cell populations, all facilitated by an automated and scalable workflow that integrates seamlessly with traditional histology staining techniques. You have the capability to spatially profile the complete transcriptome alongside more than 570 protein targets, either individually or in combination, utilizing sample inputs like whole tissue sections, tissue microarrays (TMAs), or organoids. Opting for GeoMx DSP places you at the leading edge of spatial biology, enhancing your efforts in biomarker discovery and hypothesis validation. This platform empowers you to accurately delineate relevant boundaries, allowing for biology-driven profiling that zeroes in on the tissue microenvironments and cell types that are most critical to your research endeavors. By employing this groundbreaking method, your analyses not only become more comprehensive but also finely tuned to the specific biological questions you aim to address. Ultimately, this paves the way for deeper insights and more impactful findings in your field of study.

Media

Media

Integrations Supported

Additional information not provided

Integrations Supported

Additional information not provided

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Qlucore

Date Founded

2007

Company Location

Sweden

Company Website

www.qlucore.com/omics-explorer

Company Facts

Organization Name

nanoString

Company Location

United States

Company Website

nanostring.com/products/geomx-digital-spatial-profiler/geomx-dsp-overview/

Categories and Features

Data Visualization

Analytics
Content Management
Dashboard Creation
Filtered Views
OLAP
Relational Display
Simulation Models
Visual Discovery

Categories and Features

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