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features
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support

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Description

We combine clinical and experimental data through machine learning techniques to explore human disease biology and promote the development of precision medicine. Our innovative Contingent AI™ technology comprehends the intricate relationships present in the data, yielding advanced insights. To combat data bias, we refine our machine learning models based on decisions made during the pre-processing and feature engineering phases. We utilize zebrafish, cellular, and various phenotypic animal models to test and confirm in silico predictions through in vivo experiments, along with genetic modifications conducted both in vitro and in vivo to enhance translation. By employing active learning and computer vision on validated models that focus on cardiac, central nervous system, and rare disorders, we swiftly integrate new data into our machine learning frameworks, allowing for continuous improvement and adaptation in our methodologies. This iterative process not only enhances the accuracy of our predictions but also enables us to stay at the forefront of research in precision medicine.

Description

alvaDesc is a cheminformatics tool designed for the computation and examination of molecular descriptors, fingerprints, and structural patterns, catering to QSAR, QSPR, read-across, and machine learning needs. It is capable of calculating over 5,000 molecular descriptors across various dimensions (0D–3D), which encompass constitutional, topological, geometrical, electronic, physicochemical, and fragment-based categories. In addition, the software produces molecular fingerprints and structural pattern counts that facilitate similarity analysis, clustering, and classification tasks. It comes equipped with integrated tools that allow for descriptor filtering and correlation analysis, ensuring that the modeling process is both robust and reproducible. Furthermore, alvaDesc offers seamless integration with KNIME and Python, making it easy to link with external data analysis and machine learning workflows. Its widespread use in both academic and industrial research is bolstered by comprehensive documentation and an array of scientific publications, which contribute to its reputation as a reliable resource in the field. Moreover, users appreciate its user-friendly interface that enhances the overall experience while conducting complex cheminformatics tasks.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

KNIME Analytics Platform
Python
alvaBuilder
alvaModel

Integrations

KNIME Analytics Platform
Python
alvaBuilder
alvaModel

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

BioSymetrics

Country

United States

Website

www.biosymetrics.com/platform

Vendor Details

Company Name

Alvascience

Founded

2018

Country

Italy

Website

www.alvascience.com

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