Refine
Year of publication
Document Type
- Article (38)
- Other (28)
- Conference Proceeding (23)
- Preprint (6)
- Book (2)
- Course Material (2)
Language
- English (99) (remove)
Keywords
- OCSR (3)
- CDK (2)
- Dissipative Particle Dynamics (2)
- AI (1)
- Chemical image depiction (1)
- Chemical space (1)
- Chemical structure depictions (1)
- Cheminformatics (1)
- Chemistry Development Kit (1)
- Chemistry Development Kit, CDK, Molecule fragmentation, In silico fragmentation, Scaffolds, Functional groups, Glycosidic moieties, Rich client, Graphical user interface, GUI (1)
An automated pipeline for comprehensive calculation of intermolecular interaction energies based on molecular force-fields using the Tinker molecular modelling package is presented. Starting with non-optimized chemically intuitive monomer structures, the pipeline allows the approximation of global minimum energy monomers and dimers, configuration sampling for various monomer-monomer distances, estimation of coordination numbers by molecular dynamics simulations, and the evaluation of differential pair interaction energies. The latter are used to derive Flory-Huggins parameters and isotropic particle-particle repulsions for Dissipative Particle Dynamics (DPD). The computational results for force fields MM3, MMFF94, OPLSAA and AMOEBA09 are analyzed with Density Functional Theory (DFT) calculations and DPD simulations for a mixture of the non-ionic polyoxyethylene alkyl ether surfactant C10E4 with water to demonstrate the usefulness of the approach.
CIP is an open-source high-level function library for (non-linear) curve fitting and data smoothing (with cubic splines), clustering (k-medoids, ART-2a) and machine learning (multiple linear/polynomial regression, feed-forward perceptron-type shallow and deep neural networks and support vector machines). In addition it provides several heuristics for the selection of training and test data or methods to estimate the relevance of data input components. CIP is built on top of the computing platform Mathematica to exploit its algorithmic and graphical capabilities.
CIP is an open-source high-level function library for (non-linear) curve fitting and data smoothing (with cubic splines), clustering (k-medoids, ART-2a) and machine learning (multiple linear/polynomial regression, feed-forward perceptron-type shallow and deep neural networks and support vector machines). In addition it provides several heuristics for the selection of training and test data or methods to estimate the relevance of data input components. CIP is built on top of the computing platform Mathematica to exploit its algorithmic and graphical capabilities.
Creating chemo- & bioinformatics workflows, further developments within the CDK-Taverna Project
(2008)
The translation of images of chemical structures into machine-readable representations of the depicted molecules is known as optical chemical structure recognition (OCSR). There has been a lot of progress over the last three decades in this field, but the development of systems for the recognition of complex hand-drawn structure depictions is still at the beginning. Currently, there is no data for the systematic evaluation of OCSR methods on hand-drawn structures available. Here we present DECIMER - Hand-drawn molecule images, a standardised, openly available benchmark dataset of 5088 hand-drawn depictions of diversely picked chemical structures. Every structure depiction in the dataset is mapped to a machine-readable representation of the underlying molecule. The dataset is openly available and published under the CC-BY 4.0 licence which applies very few limitations. We hope that it will contribute to the further development of the field.