Browsing Bergen Open Research Archive by Author "Chen, Ya"
Now showing items 1-5 of 5
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Hit Dexter 2.0: Machine-Learning Models for the Prediction of Frequent Hitters
Stork, Conrad; Chen, Ya; Sicho, Martin; Kirchmair, Johannes (Journal article; Peer reviewed, 2019)Assay interference caused by small molecules continues to pose a significant challenge for early drug discovery. A number of rule-based and similarity-based approaches have been derived that allow the flagging of potentially ... -
Natural products against acute respiratory infections: Strategies and lessons learned
Langeder, Julia; Grienke, Ulrike; Chen, Ya; Kirchmair, Johannes; Rollinger, Judith; Schmidtke, Michaela (Peer reviewed; Journal article, 2020)Ethnopharmacological relevance: A wide variety of traditional herbal remedies have been used throughout history for the treatment of symptoms related to acute respiratory infections (ARIs). Aim of the review: The present ... -
NP-scout: Machine learning approach for the quantification and visualization of the natural product-likeness of small molecules
Chen, Ya; Stork, Conrad; Hirte, Steffen; Kirchmair, Johannes (Peer reviewed; Journal article, 2019)Natural products (NPs) remain the most prolific resource for the development of small-molecule drugs. Here we report a new machine learning approach that allows the identification of natural products with high accuracy. ... -
Scope of 3D shape-based approaches in predicting the macromolecular targets of structurally complex small molecules including natural products and macrocyclic ligands
Chen, Ya; Mathai, Neann Sarah; Kirchmair, Johannes (Journal article; Peer reviewed, 2020)A plethora of similarity-based, network-based, machine learning, docking and hybrid approaches for predicting the macromolecular targets of small molecules are available today and recognized as valuable tools for providing ... -
Validation strategies for target prediction methods
Mathai, Neann Sarah; Chen, Ya; Kirchmair, Johannes (Peer reviewed; Journal article, 2020)Computational methods for target prediction, based on molecular similarity and network-based approaches, machine learning, docking and others, have evolved as valuable and powerful tools to aid the challenging task of mode ...