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Description

Efficiently merge the multiomic information of patients with their health records to provide more tailored care solutions. Implement specialized data repositories to facilitate extensive analyses and foster collaborative research initiatives on a population-wide scale. Expedite research processes by leveraging adaptable workflows and comprehensive computational tools. Ensure the safeguarding of patient privacy through adherence to HIPAA standards, complete with robust data access and logging mechanisms. AWS HealthOmics empowers healthcare and life science organizations, along with their software collaborators, to securely store, retrieve, and analyze diverse omics data, such as genomic and transcriptomic information, ultimately yielding valuable insights that enhance health outcomes and propel scientific advancements. Manage and evaluate omics data for extensive patient cohorts to discern how variations in omics relate to phenotypic expressions within the population. Develop consistent and accountable clinical multiomics workflows designed to minimize turnaround times while boosting efficiency. Seamlessly incorporate multiomic assessments into clinical trials aimed at evaluating new therapeutic candidates, thereby enhancing the overall drug development process. By harnessing these innovative approaches, organizations can ensure a deeper understanding of patient health and contribute to groundbreaking research findings.

Description

By leveraging visual analytics through TIBCO Spotfire®, PerkinElmer Signals Translational offers a comprehensive suite of tools designed to harmonize, manage, search, aggregate, and analyze extensive datasets consistently for translational research, all while ensuring scalability. This platform, driven by TIBCO Spotfire®, supports precision medicine initiatives by providing an unparalleled solution for biomarker discovery and patient stratification. The Linear Mixed Effect App (LME) within Signals Translational empowers researchers to evaluate the influence of various factors on specific phenotypes, allowing for adjustments related to random variables during analysis. Furthermore, it enables the identification of genes significantly affecting cancer stage progression, irrespective of patient origins. Notably, the LME models excel at addressing issues such as missing values and outliers, making them a robust choice for discovering potential biomarkers. Consequently, the integration of these advanced analytics tools enhances the efficacy of translational research in identifying key biomarkers that can lead to more personalized treatment approaches.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

AWS AI Services
Amazon Web Services (AWS)
Signals Research Suite

Integrations

AWS AI Services
Amazon Web Services (AWS)
Signals Research Suite

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

Amazon

Founded

1994

Country

United States

Website

aws.amazon.com/healthomics/

Vendor Details

Company Name

PerkinElmer

Founded

1937

Country

United States

Website

perkinelmerinformatics.com/products/clinical-translational/signals-translational/

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