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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 Signals Inventa?

Signals Inventa, formerly known as Signals Lead Discovery, is an innovative data management system that facilitates the assessment of scientific research results. It leverages the state-of-the-art Signals Data Factory technology from PerkinElmer, enabling users to effortlessly access and scrutinize all scientific data collected during the research and development phases. No matter the nature of your project, Signals Inventa supports the identification of tests that produce the most encouraging results, informs strategies for subsequent developments, and pinpoints opportunities for additional testing, among various other functions. The platform guarantees that data is uniform, systematically arranged, and ready for in-depth exploration. Furthermore, Signals Inventa amplifies scientific insights through a range of analytical methods, including R-group decomposition, chemical clustering, matched molecular pair analysis, the discovery of maximum chemical substructures, as well as conducting blast searches across both internal and external databases, alongside sequence alignment techniques. This holistic methodology not only simplifies data analysis but also encourages groundbreaking discoveries in the scientific domain, ultimately enhancing the research process and outcomes.

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

PerkinElmer Informatics

Date Founded

1937

Company Location

United States

Company Website

perkinelmerinformatics.com/products/research/signals-inventa/

Categories and Features

Categories and Features

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