Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Yes
API Access
Has API
No
Integrations
Biohub
No
Python
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
Pricing Details
No price information available.
Free Trial
No
Free Version
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
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
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
Yes
In Person
Yes
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/