Pinned Repositories
AutoDock-Vina
AutoDock Vina
c-feldmann.github.io
chembl_extraction
compchemkit
Classes and functions useful for chemoinformatics.
lassohighlight
Tool to add substructure highlighting to molecules drawn with RDKit
lilly_medchem_smarts
Lilly MedChem Rules define molecular pattern associated with promiscuous behavior, encoded in a custom format understood only by corresponding ruby code.This repo aims to translate those pattern to SMARTS so that they can be used independently.
QuickGOProteinAnnotation
Tool to retrieve predefined protein functions
rdkit_heatmaps
A package to draw custom heatmaps on molecular depictions of RDKit
simple_activity_landscapes
UniProtClient
A Python-package for convenient access to information provided by UniProt.
c-feldmann's Repositories
c-feldmann/rdkit_heatmaps
A package to draw custom heatmaps on molecular depictions of RDKit
c-feldmann/lassohighlight
Tool to add substructure highlighting to molecules drawn with RDKit
c-feldmann/UniProtClient
A Python-package for convenient access to information provided by UniProt.
c-feldmann/AutoDock-Vina
AutoDock Vina
c-feldmann/c-feldmann.github.io
c-feldmann/chembl_extraction
c-feldmann/compchemkit
Classes and functions useful for chemoinformatics.
c-feldmann/lilly_medchem_smarts
Lilly MedChem Rules define molecular pattern associated with promiscuous behavior, encoded in a custom format understood only by corresponding ruby code.This repo aims to translate those pattern to SMARTS so that they can be used independently.
c-feldmann/pdbpython
The scope of this module is downloading or reading PDB-Files and subsequently parsing them
c-feldmann/QuickGOProteinAnnotation
Tool to retrieve predefined protein functions
c-feldmann/simple_activity_landscapes
c-feldmann/psi4_examples
Examles for Psi4
c-feldmann/pymoo
NSGA2, NSGA3, R-NSGA3, MOEAD, Genetic Algorithms (GA), Differential Evolution (DE), CMAES, PSO
c-feldmann/scikit-mol
scikit-learn classes for molecular vectorization using RDKit
c-feldmann/sklearn_x_rdkit
tool to prepare rdkit fingerprints for sklearn input