Journal of Cheminformatics
@jcheminf
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Tweets from Editors-in-Chiefs Rajarshi Guha & Barbara Zdrazil & Publishing Editor Maggie Zhang.
Joined August 2016
We are looking for 2 new Associate Editors who share the vision for our journal to support the Editors-in-Chief in handling manuscripts & contributing to the development of the journal:
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"The published role of artificial intelligence in drug discovery and development: a bibliometric and social network analysis from 1990 to 2023"
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"Application of 3D atom pair map in an attention model for enhanced drug virtual screening"
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"Predicting inhibitors of OATP1B1 via heterogeneous OATP-ligand interaction graph neural network (HOLIgraph)"
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"Prediction of blood–brain barrier and Caco-2 permeability through the Enalos Cloud Platform: combining contrastive learning and atom-attention message passing neural networks"
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"Leveraging AI to explore structural contexts of post-translational modifications in drug binding"
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"Improving the accuracy of prediction models for small datasets of Cytochrome P450 inhibition with deep learning"
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"LAGNet: better electron density prediction for LCAO-based data and drug-like substances"
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"E-GuARD: expert-guided augmentation for the robust detection of compounds interfering with biological assays"
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"SMILES all around: structure to SMILES conversion for transition metal complexes"
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"Translating community-wide spectral library into actionable chemical knowledge: a proof of concept with monoterpene indole alkaloids"
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"Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands"
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"Visualising lead optimisation series using reduced graphs"
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Journal of Cheminformatics just launched a new special collection on "Evaluating AI and machine learning models in cheminformatics: benchmarking techniques and case studies" guested-edited by G. Colmenarejo, S. Lobentanzer & O. Méndez-Lucio
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"High-throughput screening data generation, scoring and FAIRification: a case study on nanomaterials"
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"Molecular property prediction using pretrained-BERT and Bayesian active learning: a data-efficient approach to drug design"
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"GESim: ultrafast graph-based molecular similarity calculation via von Neumann graph entropy"
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"Learning motif features and topological structure of molecules for metabolic pathway prediction"
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"Prediction of the water solubility by a graph convolutional-based neural network on a highly curated dataset"
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"Activity cliff-aware reinforcement learning for de novo drug design"
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