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What is Signals Translational?

Utilizing visual analytics offered by TIBCO Spotfire®, PerkinElmer Signals Translational provides a robust array of tools aimed at streamlining the harmonization, management, searching, aggregation, and analysis of large datasets for translational research, all while maintaining scalability. This platform, powered by TIBCO Spotfire®, plays a vital role in advancing precision medicine initiatives by delivering an exceptional solution for discovering biomarkers and stratifying patients effectively. Within Signals Translational, the Linear Mixed Effect App (LME) equips researchers with the capability to assess the impact of various factors on specific phenotypes, facilitating adjustments associated with random variables during their analyses. Additionally, it aids in pinpointing genes that significantly influence the progression of cancer stages, regardless of the patients' backgrounds. Importantly, the LME models are particularly adept at handling challenges like missing values and outliers, positioning them as a reliable option for uncovering potential biomarkers. As a result, the incorporation of these sophisticated analytics tools significantly boosts the effectiveness of translational research, paving the way for the identification of critical biomarkers that can enhance personalized treatment strategies. This innovative approach not only streamlines research processes but also fosters collaboration among researchers aiming to improve patient outcomes through more tailored therapeutic interventions.

What is BioSymetrics?

We integrate clinical insights and experimental findings using machine learning methodologies to investigate the complexities of human diseases and advance the field of precision medicine. Our pioneering Contingent AI™ technology adeptly navigates the complex interconnections within the data, resulting in valuable insights. To mitigate biases in our data, we enhance our machine learning algorithms by refining decisions made during the initial stages of data pre-processing and feature engineering. Employing zebrafish, cellular models, and a variety of phenotypic animal models, we validate in silico predictions through rigorous in vivo experimentation, complemented by genetic modifications executed both in vitro and in vivo to facilitate better translation of results. Through the application of active learning and computer vision techniques on validated models concentrating on cardiac, central nervous system, and rare diseases, we efficiently incorporate fresh data into our machine learning systems. This ongoing refinement process not only amplifies the precision of our predictions but also positions us as leaders in the evolving landscape of precision medicine research. By continuously adapting our methodologies, we ensure our work remains relevant and impactful in addressing the challenges posed by human diseases.

Media

Media

Integrations Supported

Signals Research Suite

Integrations Supported

Signals Research Suite

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

PerkinElmer

Date Founded

1937

Company Location

United States

Company Website

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

Company Facts

Organization Name

BioSymetrics

Company Location

United States

Company Website

www.biosymetrics.com/platform

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