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Description

Proteins, which are remarkably complex machines, play a crucial role not only in the biological functions of your body but also in every living organism's processes. They serve as the fundamental units of life. As of now, there are approximately 100 million identified proteins, with discoveries being made regularly. Each protein possesses a distinctive three-dimensional shape that is essential to its functionality and purpose. However, determining a protein's precise structure is often a costly and lengthy endeavor, resulting in an understanding of only a small percentage of the proteins recognized by science. Addressing this growing disparity and developing methods to predict the structures of millions of yet-to-be-discovered proteins could significantly advance our ability to combat diseases, expedite the discovery of new treatments, and potentially unveil the secrets of life's mechanisms. The implications of such advancements could transform both medicine and our understanding of biology.

Description

The simplest method for pulling data points from unstructured text involves simultaneously scanning research documents, prospectuses, and customer feedback to identify, track, and assess significant, user-defined data metrics. You can access over 100 distinct data points to enhance your investment and risk management strategies effectively. By searching and assembling customized datasets from EDGAR and various public or private resources, you can optimize your deal underwriting process. Additionally, this approach can streamline the legal workflows within capital markets and structured finance. Instantly retrieve over 100 data points to help categorize, compare, and collaborate with your clients more effectively. Deconstructing unstructured text from sources like PubMed and clinical trial data allows you to break down information into categories such as diseases, genes, proteins, and symptoms, ensuring that all your research is consolidated in one location. You can incorporate research from any source into your workspaces effortlessly with our convenient Chrome plug-in, which also enables the transformation of digital PDFs into machine-readable formats. Furthermore, you will receive outputs in JSON and HTML formats that include a detailed section hierarchy, as well as the removal of watermarks, multi-level tables, lists, headers, and footers, making your data more accessible and manageable than ever before. This comprehensive solution not only simplifies data extraction but also enhances your overall analytical capabilities.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Complete
Gemini Robotics
Google Chrome
WeatherNext

Integrations

Complete
Gemini Robotics
Google Chrome
WeatherNext

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

DeepMind

Founded

2010

Country

United Kingdom

Website

deepmind.com/research/case-studies/alphafold

Vendor Details

Company Name

NLMatics

Founded

2019

Country

United States

Website

www.nlmatics.com

Product Features

Product Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

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