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What is ResoluteAI?

ResoluteAI provides a robust platform that enables users to conduct simultaneous searches across a wide range of aggregated scientific, regulatory, and business databases. Its interactive analytics and downloadable visualizations empower users to establish connections that could lead to groundbreaking discoveries. Nebula, the enterprise search solution from ResoluteAI designed specifically for the scientific sector, harnesses structured metadata along with advanced AI tools to enhance institutional knowledge. This innovative system integrates a variety of technologies, including natural language processing, optical character recognition, image recognition, and transcription, facilitating the discovery and retrieval of proprietary information with ease. By using Nebula, researchers can uncover the hidden value in their studies, experiments, market insights, and acquired assets. With the advantage of structured metadata from unstructured text, users gain access to features such as semantic expansion, conceptual search, and document similarity search, ensuring a thorough investigation of their data. This groundbreaking platform revolutionizes the way scientific information is accessed and leveraged, leading to improved research outcomes and fostering collaboration within the scientific community. Moreover, its user-friendly interface and powerful search capabilities make it an essential tool for researchers aiming to push the boundaries of knowledge.

What is ESMFold2?

Building upon its predecessor, ESMFold, ESMFold2 sets a new standard in the realm of single-sequence structure prediction while also enabling the design of novel functional proteins by delving into the latent space of the ESMC model. This sophisticated model can accurately predict high-resolution, all-atom 3D structures of biomolecular complexes directly from amino acid sequences and incorporates multiple sequence alignments to enhance accuracy for challenging targets. Designed to predict structures using both sequence and structural modalities, it utilizes ESM representations that power a sequence of looped folding layers, while a diffusion model converts pairwise representations into atomic-resolution results. ESMFold2 stands out in its ability to forecast protein structures from amino acid sequences, providing comprehensive structural information, including exact all-atom coordinates for backbone and side chains, as well as confidence metrics and optional distogram predictions for thorough structural analysis. In addition, its groundbreaking methodology deepens the understanding of protein folding dynamics and their functional implications, positioning it as an indispensable tool for researchers engaging in this area of study. Ultimately, ESMFold2 not only advances structural biology but also opens new avenues for the development of protein-based applications.

Media

Media

Integrations Supported

Biohub
Python

Integrations Supported

Biohub
Python

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

Free
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

ResoluteAI

Date Founded

2015

Company Location

United States

Company Website

www.resolute.ai/

Company Facts

Organization Name

Biohub

Date Founded

2016

Company Location

United States

Company Website

biohub.ai/models/esmfold2

Categories and Features

Data Discovery

Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics

Market Research

Benchmarking
Compensation Management
Data Management
Email / Online
Face-to-Face
Panel Management
Paper-Based
Phone-Based
Sample Management
Statistical Analysis
Survey Management

Natural Language Processing

Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization

Categories and Features

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