Reproducible Cheminformatics through Visual Workflows
Quick prototyping, data pipelining, model deployment, and interactive data apps.
Accelerate the R&D process through reproducible data analytics
eQuick & Easy Prototyping
Data available at every step.
Collaborate with Domain Experts
Create data apps for collaboration.
- Example workflow: Experts exploring molecular properties of interesting compounds
- Webinar: Interactive web applications
- Blog: Training a machine learning model and predictive web application in three steps
Deploy Workflows with KNIME Business Hub
Productionize data science applications and services
Deploy workflows across the enterprise as analytical services or applications. KNIME Business Hub lets you share data and workflows, manage permissions, and track workflow revisions as well as automate and schedule workflow execution. Enterprises can respond efficiently to constantly changing demands by scaling workflow execution. Meet compute demands elastically and automatically with cloud offerings on AWS and Azure.
- Use case: Scaling model building processes to train 300k models for bioactivity prediction
- Workflow: Create an automated database report by scheduled execution of this workflow on KNIME Business Hub.
Future proof, no lock in, transparent pricing
KNIME Business Hub has transparent pricing with no hidden costs for additional features. The underlying open source KNIME Analytics Platform sets no limitations on the amount of data, number of nodes, or ML techniques, and it's free to download.
- No limitations on using open source KNIME Analytics Platform, ever!
- Even if you discontinue the KNIME Business Hub license, workflows can still be used in KNIME Analytics Platform without any limitations
Mix & Match Technologies
Due to the open nature of KNIME, you have extreme freedom in using any data source, technology, or tool - all in a single workflow.
Cheminformatics with KNIME & Extensions
With KNIME and its dedicated Cheminformatics Extensions you can choose from a wide range of cheminformatics functionality and create workflows. For example: finding chemical scaffolds using maximum common substructure, R-group decomposition, or multiobjective optimization.
Access Diverse Data
Access simple text formats, semantic data, or specific formats like SDF, RXN, SMILES, and MOL. Automatically retrieve data from public resources, or connect to AWS S3, Azure, and GCP. Connect to databases and data warehouses to integrate data from Oracle, Microsoft SQL, Hadoop, Google BigQuery, and more.
Data Science Technologies
Build machine learning models for classification, regression, dimensionality reduction, or clustering. Integrate with Tensorflow, Keras, H2O, and others. Use your favourite packages in R or Python and combine with other KNIME functionality in one reproducible workflow.
