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Description

In recent years, high-performance computing has become a more accessible resource for a greater number of researchers within the scientific community than ever before. The combination of quality open-source software and affordable hardware has significantly contributed to the widespread adoption of Beowulf class clusters and clusters of workstations. Among various parallel computational approaches, message-passing has emerged as a particularly effective model. This paradigm is particularly well-suited for distributed memory architectures and is extensively utilized in today's most demanding scientific and engineering applications related to modeling, simulation, design, and signal processing. Nonetheless, the landscape of portable message-passing parallel programming was once fraught with challenges due to the numerous incompatible options developers faced. Thankfully, this situation has dramatically improved since the MPI Forum introduced its standard specification, which has streamlined the process for developers. As a result, researchers can now focus more on their scientific inquiries rather than grappling with programming complexities.

Description

Signals Inventa, which was previously referred to as Signals Lead Discovery, represents an advanced data management solution designed for the evaluation of scientific findings. Utilizing the cutting-edge Signals Data Factory technology from PerkinElmer, it allows users to seamlessly access and analyze all scientific data gathered throughout the research and development process. Regardless of your project, Signals Inventa aids in determining which tests yield the most promising outcomes, guides decisions on future developments, and identifies areas for further testing, among many other capabilities. The platform ensures that data is standardized, organized, and primed for exploration. Additionally, Signals Inventa enhances scientific insight through various analytical techniques such as R-group decomposition, chemical clustering, matched molecular pair analysis, the identification of maximum chemical substructures, as well as blast searches across both internal and external databases, and sequence alignment. This comprehensive approach not only streamlines data analysis but also fosters innovative discoveries in the field.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

C
C++
Fortran
NumPy
Python
Signals Research Suite

Integrations

C
C++
Fortran
NumPy
Python
Signals Research Suite

Pricing Details

Free
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

MPI for Python

Website

mpi4py.readthedocs.io/en/stable/

Vendor Details

Company Name

PerkinElmer Informatics

Founded

1937

Country

United States

Website

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

Product Features

Product Features

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