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Description
Ask Paper provides a streamlined way to quickly read and gather insights from academic papers. Users can upload documents either through a URL link or by directly uploading a PDF file, enabling them to pose questions in natural language regarding the content of the paper. This innovative tool utilizes advanced neural network technology, designed to comprehend language intricacies by predicting subsequent words in text sequences. By inputting the paper's details along with your inquiries, it generates likely responses based on its extensive training. To get started, simply create an account on Discord and join our dedicated server. For those requiring additional assistance, guest login options are available, offering the ability to receive helpful instructions via email on effectively navigating the tool. With Ask Paper, you can enhance your research efficiency significantly.
Description
ESMFold2 builds upon its predecessor, ESMFold, by establishing a new benchmark in single-sequence structure prediction and facilitating the creation of novel functional proteins via exploration of the latent space within the ESMC model. This advanced model is capable of forecasting high-resolution, all-atom 3D structures of biomolecular complexes straight from the amino acid sequence, and it allows for the incorporation of multiple sequence alignments to improve accuracy on difficult targets. Tailored for predicting structures through both sequence and structure modalities, it employs ESM representations that drive a series of looped folding layers while a diffusion model translates pairwise representations into atomic-resolution outcomes. ESMFold2 excels in predicting protein structures from amino acid sequences, providing detailed structural data, including precise all-atom coordinates for both backbone and side chains, along with confidence metrics and optional distogram predictions for in-depth structural evaluation. Furthermore, its innovative approach enhances the understanding of protein folding dynamics and functional implications, making it a valuable tool for researchers in the field.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Biohub
No
Python
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Vendor Details
Company Name
AskPaper
Website
www.askpaper.ai/
Vendor Details
Company Name
Biohub
Founded
2016
Country
United States
Website
biohub.ai/models/esmfold2