XGBoost, mordred and RDKit for the prediction of glass transition temperature of polymers by Goh, Kai Leong

“…A total of 12 sets of features were generated by RDKit and Mordred as inputs for XGBoost to predict Tg. The scoring metrics from the Scikit-learn and Numpy libraries showed that the 2D molecular descriptors of Mordred (Mordred-2D) and the Extended-Connectivity Fingerprint with a diameter of 4 bonds (ECFP4) had the best performances. …”
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« Mordre la machine » : Réhabiliter le low-tech contre les big data by Jean-Paul FOURMENTRAUX

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A machine learning approach for predicting the reactivity power of hypervalent iodine compounds by Vaneet Saini, Ramesh Kataria, Shruti Rajput

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Integrated QSAR Models for Prediction of Serotonergic Activity: Machine Learning Unveiling Activity and Selectivity Patterns of Molecular Descriptors by Natalia Łapińska, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

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Curated Database and Preliminary AutoML QSAR Model for 5-HT1A Receptor by Natalia Czub, Adam Pacławski, Jakub Szlęk, Aleksander Mendyk

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Comparing the performances of glass transition temperatures prediction : SMILES vs. Molfile by Goh, Kai Leong

“…For Mordred-2D, SMILES generally performed better than .mol files. …”
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Graph Neural Network and BERT Model for Antimalarial Drug Predictions Using Plasmodium Potential Targets by Medard Edmund Mswahili, Goodwill Erasmo Ndomba, Kyuri Jo, Young-Seob Jeong

“…The performance of BERT-RGCN was further compared with that of Mordred-RGCN to evaluate its effectiveness. The BERT-RGCN and Mordred-RGCN models performed consistently well across different feature combinations, showcasing high accuracy, sensitivity, specificity, MCC, AUROC, and AUPRC values. …”
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Principled Exploration of Bipyridine and Terpyridine Additives to Promote Methylammonium Lead Iodide Perovskite Crystallization by Hartono, Noor Titan Putri, Ani Najeeb, Mansoor, Li, Zhi, Nega, Philip W., Fleming, Clare A., Sun, Xiaohe, Chan, Emory M., Abate, Antonio, Norquist, Alexander J., Schrier, Joshua, Buonassisi, Tonio

“…To combat selection bias and generate hypotheses for future experimental cycles of learning, we featurize candidate additives using Mordred descriptors and compare similarity metrics. …”
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Neural network-based prediction of auto-ignition temperature of ternary mixed liquids by Bingyu Guo, Zehui Cheng, Shuangqi Hu

“…The optimal molecular descriptors were calculated and filtered using Mordred software. Twelve mixing rules were proposed for calculating molecular descriptors of mixtures. …”
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Machine Learning Tool for New Selective Serotonin and Serotonin–Norepinephrine Reuptake Inhibitors by Natalia Łapińska, Jakub Szlęk, Adam Pacławski, Aleksander Mendyk

“…The molecular representation featured two-dimensional Mordred descriptors. For each model, Shapley additive explanations analysis was performed to clarify the influence of the descriptors on the models’ predictions. …”
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Quantitative structure–activity relationship study to predict the antibacterial activity of gemini quaternary ammonium surfactants against Escherichia coli by Setiawan, Ely, Mudasir, Mudasir

“…After optimizing all structures of these compounds using the ab initio 6-311G basis sets at the Hartree–Fock level theory, the molecular descriptors were calculated using the Mordred program. The genetic algorithm (GA) and multiple linear regressions (MLR) were used for generating two QSAR models with different splitting techniques. …”
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New insight into biodegradation mechanism of phenylurea herbicides by cytochrome P450 enzymes: Successive N-demethylation mechanism by Zijian Wang, Zhong Wang, Guoqiang Wang, Qingzhu Zhang, Qiao Wang, Wenxing Wang

“…Two QSAR models are established to predict the energy barriers of the two H-abstraction pathways based on the quantum chemical descriptors and mordred molecular descriptors. The determination coefficient (R2) values of QSAR models are > 0.9, which reveal that the established QSAR models have great predictive capability. …”
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Causality-driven feature selection and domain adaptation for enhancing chemical foundation models in downstream tasks by Eduardo Soares, Victor Yukio Shirasuna, Emilio Vital Brazil, Karen Fiorella Aquino Gutierrez, Renato Cerqueira, Dmitry Zubarev, Kristin Schmidt, Daniel P Sanders

“…Our approach employs a multi-stage feature selection method that identifies physico-chemical features based on their direct causal-effect over specific downstream properties. By employing Mordred descriptors and Markov blanket causal graphs, our approach provides insight into the causal relationships between features and target properties for prediction tasks. …”
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AISMPred: A Machine Learning Approach for Predicting Anti-Inflammatory Small Molecules by Subathra Selvam, Priya Dharshini Balaji, Honglae Sohn, Thirumurthy Madhavan

“…We computed two distinct types of molecular descriptors using PaDEL and Mordred tools. Subsequently, these descriptors were concatenated to form a hybrid feature set. …”
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Pourquoi l’art a-t-il cessé d’être subversif ? by Clemente Padin

“…Personne ne penserait à mordre la main de celui qui le nourrit. La pandémie de la Covid-19 n’a fait qu’aggraver la situation, avec ses pertes d’emplois et d’investissements, et pire encore, l’attitude de nombreux potentats qui tournent le dos aux demandes du peuple, insensibles à la douleur et à l’oppression de leurs frères.…”
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Pakistani Anglophone Young Adult Fiction and the Art of Commodification of Culture: An Insight to Sheba Karim’s The Skunk Girl and Rukhsana Khan’s Wanting Mor by Dr. Asma Iqbal Qazi

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