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Description

ESMC represents the newest advancement in the ESM series of protein language models, pushing the boundaries of representation learning within the field of protein biology. With training on billions of evolutionary sequences, it adeptly captures representations that encapsulate a mechanistic understanding of protein structure and function. The model utilizes a transformer architecture, focusing on sequences as its primary modality, and is trained on a vast dataset comprising up to 6 billion proteins. ESMC is tailored for various protein science applications, such as predicting structures, annotating functions, designing proteins, and exploring evolutionary connections among proteins. Additionally, it possesses the capability to create novel proteins based on partial sequences, structures, or functional constraints, thereby enabling researchers to investigate innovative avenues in protein design and biological discovery. Accessible through the Biohub Platform, ESMC can be utilized via an API and the ESM Python package, which includes quickstart resources for installation, API key generation, and platform connectivity, ensuring a seamless experience for users. This comprehensive accessibility encourages a broader engagement with protein research and enhances collaborative efforts in the scientific community.

Description

Efficiently address tissue heterogeneity and the intricacies of microenvironments using the GeoMx Digital Spatial Profiler (DSP), which stands out as the most versatile and powerful spatial multi-omic platform for examining both FFPE and fresh frozen tissue sections. Unique among spatial biology platforms, GeoMx allows for non-destructive profiling of RNA and protein expression across various tissue compartments and cell populations, supported by an automated and scalable workflow that seamlessly integrates with conventional histology staining. You can spatially profile the entire transcriptome along with over 570 protein targets, either separately or concurrently, utilizing sample inputs such as whole tissue sections, tissue microarrays (TMAs), or organoids. By choosing GeoMx DSP, you position yourself at the forefront of spatial biology for effective biomarker discovery and hypothesis validation. With the ability to determine the relevant boundaries, you can rely on biology-driven profiling that enables you to focus on the tissue microenvironments and cell types that hold the most significance for your research. This innovative approach ensures that your analyses are both comprehensive and tailored to the specific biological contexts of interest.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Biohub
Python

Integrations

Biohub
Python

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

Biohub

Founded

2016

Country

United States

Website

biohub.ai/models/esmc

Vendor Details

Company Name

nanoString

Country

United States

Website

nanostring.com/products/geomx-digital-spatial-profiler/geomx-dsp-overview/

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