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Journal of cheminformatics

Showing results (711-720 of 1,363) with videos related to

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Journal of Cheminformatics|June 9, 2015
Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?Dávid Bajusz, Anita Rácz, Károly Héberger
Journal of Cheminformatics|August 28, 2025
AdapTor: Adaptive Topological Regression for quantitative structure-activity relationship modelingYixiang Mao, Souparno Ghosh, Ranadip Pal
Journal of Cheminformatics|August 28, 2025
Comment on "Advancing material property prediction: using physics-informed machine learning models for viscosity"Maximilian Fleck, Samir Darouich, Marcelle B M Spera, et al.
Journal of Cheminformatics|August 29, 2025
FusionCLM: enhanced molecular property prediction via knowledge fusion of chemical language modelsYutong Lu, Yan Yi Li, Yan Sun, et al.
Journal of Cheminformatics|September 3, 2025
MetaboGNN: predicting liver metabolic stability with graph neural networks and cross-species dataJun Hyeong Park, Ri Han, Junbo Jang, et al.
Journal of Cheminformatics|May 25, 2021
InChI version 1.06: now more than 99.99% reliableJonathan M Goodman, Igor Pletnev, Paul Thiessen, et al.
Journal of Cheminformatics|August 10, 2021
QPHAR: quantitative pharmacophore activity relationship: method and validationStefan M Kohlbacher, Thierry Langer, Thomas Seidel
Journal of Cheminformatics|February 7, 2023
Force field-inspired molecular representation learning for property predictionGao-Peng Ren, Yi-Jian Yin, Ke-Jun Wu, et al.
Journal of Cheminformatics|February 24, 2023
Reconstruction of lossless molecular representations from fingerprintsUmit V Ucak, Islambek Ashyrmamatov, Juyong Lee
Journal of Cheminformatics|November 8, 2016
Multi-level meta-workflows: new concept for regularly occurring tasks in quantum chemistryJunaid Arshad, Alexander Hoffmann, Sandra Gesing, et al.
Pageof 137

Showing results (711-720 of 1,363) with videos related to

Sort By:
Pageof 137
Journal of Cheminformatics|June 9, 2015
Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations?Dávid Bajusz, Anita Rácz, Károly Héberger
Journal of Cheminformatics|August 28, 2025
AdapTor: Adaptive Topological Regression for quantitative structure-activity relationship modelingYixiang Mao, Souparno Ghosh, Ranadip Pal
Journal of Cheminformatics|August 28, 2025
Comment on "Advancing material property prediction: using physics-informed machine learning models for viscosity"Maximilian Fleck, Samir Darouich, Marcelle B M Spera, et al.
Journal of Cheminformatics|August 29, 2025
FusionCLM: enhanced molecular property prediction via knowledge fusion of chemical language modelsYutong Lu, Yan Yi Li, Yan Sun, et al.
Journal of Cheminformatics|September 3, 2025
MetaboGNN: predicting liver metabolic stability with graph neural networks and cross-species dataJun Hyeong Park, Ri Han, Junbo Jang, et al.
Journal of Cheminformatics|May 25, 2021
InChI version 1.06: now more than 99.99% reliableJonathan M Goodman, Igor Pletnev, Paul Thiessen, et al.
Journal of Cheminformatics|August 10, 2021
QPHAR: quantitative pharmacophore activity relationship: method and validationStefan M Kohlbacher, Thierry Langer, Thomas Seidel
Journal of Cheminformatics|February 7, 2023
Force field-inspired molecular representation learning for property predictionGao-Peng Ren, Yi-Jian Yin, Ke-Jun Wu, et al.
Journal of Cheminformatics|February 24, 2023
Reconstruction of lossless molecular representations from fingerprintsUmit V Ucak, Islambek Ashyrmamatov, Juyong Lee
Journal of Cheminformatics|November 8, 2016
Multi-level meta-workflows: new concept for regularly occurring tasks in quantum chemistryJunaid Arshad, Alexander Hoffmann, Sandra Gesing, et al.
Pageof 137