3D-e-Chem Virtual Machine
A freely available Virtual Machine encompassing tools, databases, and workflows for cheminformaticians, including new resources developed for ligand binding site comparisons and GPCR research.
Efficient exploitation of the massive amount of modern-day life science data
Many new protein targets have been discovered recently and it has been shown that clinical efficacy is often the result of polypharmacological action of drug molecules (the interaction with more than one protein target). But exploitation of this insight is hampered because we can not efficiently integrate large volumes of heterogeneous data from different disciplines. The data needs to be properly integrated in order to extract useful information that is manageable and applicable in various life science disciplines. This project will develop technologies to improve the integration of ligand and protein data for structure-based prediction of protein-ligand selectivity and polypharmacology.
Unlocking large volumes of knowledge locked in natural text
Integrating data publishing principles in scientific workflows
Fusible evolutionary deep neural network mixture learning from distributed data for robust medical...
Sequence validation in the DNA barcoding project
Bringing concepts from distributed computing and bioinformatics to the field of computational...
Managing and exploiting growing data resources in chemical design
Open discovery and exchange for all
Better biomarkers through datasharing
Capitalizing on the growth of scientific knowledge on food
The Virtual Laboratory for Plant Breeding
A freely available Virtual Machine encompassing tools, databases, and workflows for cheminformaticians, including new resources developed for ligand binding site comparisons and GPCR research.
If you are working in the KNIME worflow platform and need data about your favorite kinase receptor ligand interaction, then these nodes are for you.
A node for the KNIME workflow systems that allows you to retrieve data about your favorite G protein-coupled receptors from gpcrdb.org.
A 3D viewer for large molecules for the KNIME workflow system.
Want to write your own KNIME node Then use the KNIME node archetype to generate a node skeleton repository with sample code.
A node for the KNIME workflow systems that allows you to compare different binding sites in proteins with each other.
A plugin for the KNIME workflow system that adds a Pharmacophore data type and nodes to read, write, and align them.
A node for the KNIME workflow system that allows you to use the PLANTS protein-ligand docking algorithm.
Want to write your own KNIME node wrapping a Python library. Then use the KNIME Python node archetype to generate a node skeleton repository with sample code
If you are developing a KNIME node which calls some Python code, then the KNIME Python wrapper can help you.
A node for the KNIME workflow systems that allows you to use the Silicos-it software to filter or align molecules.
A node for the KNIME workflow systems that allows you to identify which residue position in a big protein sequence alignment is specific to ligand binding.
Allows you to test KNIME nodes automatically using JUnit.
SyGMa provides fast and lightweight predictions of human metabolites to support discovery scientists design better and safer drugs