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What is Tellurium?

Tellurium is a highly adaptable Python package that amalgamates several essential tools needed for performing simulation studies in systems biology and a variety of other domains. It provides users with access to the powerful high-performance simulation engine known as libRoadrunner, enabling efficient computations. Users have the option to construct their models using Antimony, a simplified and human-readable format derived from SBML, with an accompanying tutorial available for those interested in mastering the language's specifics. Tellurium maintains compatibility with all major standards, such as SBML, SED-ML, and COMBINE archives, ensuring broad usability. It can be accessed through intuitive GUI environments like Spyder, PyCharm, or Jupyter Notebooks, including platforms like CoLab, which not only enhances productivity but also supports interactive editing capabilities. Installation is user-friendly and can be easily performed via the standard pip method, with a one-click installer available for Windows users that establishes a comprehensive environment tailored for systems biology modeling. The ongoing development of Tellurium is enriched by the contributions of numerous open-source developers, which guarantees that the tool remains current and beneficial for researchers. With its extensive features and user-centric design, Tellurium proves to be an invaluable asset for anyone engaged in simulation studies across diverse scientific disciplines, fostering innovation and collaboration in research efforts.

What is Modelbit?

Continue to follow your regular practices while using Jupyter Notebooks or any Python environment. Simply call modelbi.deploy to initiate your model, enabling Modelbit to handle it alongside all related dependencies in a production setting. Machine learning models deployed through Modelbit can be easily accessed from your data warehouse, just like calling a SQL function. Furthermore, these models are available as a REST endpoint directly from your application, providing additional flexibility. Modelbit seamlessly integrates with your git repository, whether it be GitHub, GitLab, or a bespoke solution. It accommodates code review processes, CI/CD pipelines, pull requests, and merge requests, allowing you to weave your complete git workflow into your Python machine learning models. This platform also boasts smooth integration with tools such as Hex, DeepNote, Noteable, and more, making it simple to migrate your model straight from your favorite cloud notebook into a live environment. If you struggle with VPC configurations and IAM roles, you can quickly redeploy your SageMaker models to Modelbit without hassle. By leveraging the models you have already created, you can benefit from Modelbit's platform and enhance your machine learning deployment process significantly. In essence, Modelbit not only simplifies deployment but also optimizes your entire workflow for greater efficiency and productivity.

Media

Media

Integrations Supported

Integrations Supported

Amazon Redshift
Databricks
Deepnote
GitHub
GitLab
Google Colab
Jupyter Notebook
PyTorch
Snowflake
TensorFlow

API Availability

API Availability

Pricing Information

$15.00/month/user
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

24 Hour Support

Customer Service / Support

Web-Based Support

Training Options

Webinars
Online Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Tellurium

Date Founded

2010

Company Location

United States

Company Website

tellurium.analogmachine.org

Company Facts

Organization Name

Modelbit

Date Founded

2022

Company Location

United States

Company Website

www.modelbit.com

Categories and Features

Automated Testing

Move & Copy
Parameterized Testing
Requirements-Based Testing
Supports Parallel Execution
Test Script Reviews

Categories and Features

AI/ML Model Training

Not specified

Machine Learning

Not specified

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