Results 11 to 20 of about 6,104,936 (275)

Fast and effective molecular property prediction with transferability map [PDF]

Communications Chemistry
Effective transfer learning for molecular property prediction has shown considerable strength in addressing insufficient labeled molecules. Many existing methods either disregard the quantitative relationship between source and target properties, risking
Shaolun Yao, Jie Song, Lingxiang Jia, Lechao Cheng, Zipeng Zhong, Mingli Song, Zunlei Feng   +6 more
doaj   +3 more sources

Analyzing Learned Molecular Representations for Property Prediction [PDF]

Journal of Chemical Information and Modeling, 2019
Advancements in neural machinery have led to a wide range of algorithmic solutions for molecular property prediction. Two classes of models in particular have yielded promising results: neural networks applied to computed molecular fingerprints or expert-crafted descriptors, and graph convolutional neural networks that construct a learned molecular ...
Kevin Yang, Kyle Swanson, Wengong Jin, Connor W. Coley, Philipp Eiden, Hua Gao, Angel Guzman-Perez, Timothy Hopper, Brian Kelley, Miriam Mathea, Andrew Palmer, Volker Settels, Tommi S. Jaakkola, Klavs F. Jensen, Regina Barzilay   +14 more
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Improving VAE based molecular representations for compound property prediction [PDF]

Journal of Cheminformatics, 2022
Collecting labeled data for many important tasks in chemoinformatics is time consuming and requires expensive experiments. In recent years, machine learning has been used to learn rich representations of molecules using large scale unlabeled molecular ...
Ani Tevosyan, Lusine Khondkaryan, Hrant Khachatrian, Gohar Tadevosyan, Lilit Apresyan, Nelly Babayan, Helga Stopper, Zaven Navoyan   +7 more
doaj   +3 more sources

Molecular-Property Prediction with Sparsity [PDF]

, 2022
Machine learning models for molecular-property prediction typically work with molecular representations in the form of fingerprints, descriptors, or graphs. In case of fingerprints and descriptors, molecular representations usually comprise thousands of features, which causes the curse of dimensionality for many tabular models.
Sanjar, Adilov
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PEMP: Leveraging Physics Properties to Enhance Molecular Property Prediction

Proceedings of the 31st ACM International Conference on Information & Knowledge Management, 2022
9 pages.
Yuancheng Sun, Yimeng Chen, Weizhi Ma, Wenhao Huang 0001, Kang Liu 0001, Zhiming Ma, Wei-Ying Ma, Yanyan Lan   +7 more
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Fingerprint-enhanced hierarchical molecular graph neural networks for property prediction

Journal of Pharmaceutical Analysis
Accurate prediction of molecular properties is crucial for selecting compounds with ideal properties and reducing the costs and risks of trials. Traditional methods based on manually crafted features and graph-based methods have shown promising results ...
Shuo Liu, Mengyun Chen, Xiaojun Yao, Huanxiang Liu   +3 more
doaj   +2 more sources

Enhancing molecular property prediction with quantized GNN models [PDF]

Journal of Cheminformatics
Efficient and reliable prediction of molecular properties, such as water solubility, hydration free energy, lipophilicity, and quantum mechanical properties, is essential for rational compound design in the chemical and pharmaceutical industries.
Areen Rasool, Jamshaid Ul Rahman, Rongin Uwitije   +2 more
doaj   +2 more sources

A hierarchical interaction message net for accurate molecular property prediction [PDF]

Communications Chemistry
Discovering molecules with desirable molecular properties, including ADMET profiles, is of great importance in drug discovery. Existing approaches typically employ deep learning models, such as Graph Neural Networks and Transformers, to predict these ...
Huiyang Hong, Xinkai Wu, Hongyu Sun, Chaoyang Xie, Qi Wang, Yuquan Li   +5 more
doaj   +2 more sources

Molecular property prediction in the ultra‐low data regime [PDF]

Communications Chemistry
Data scarcity remains a major obstacle to effective machine learning in molecular property prediction and design, affecting diverse domains such as pharmaceuticals, solvents, polymers, and energy carriers.
Basem A. Eraqi, Dmitrii Khizbullin, Shashank S. Nagaraja, S. Mani Sarathy   +3 more
doaj   +2 more sources

Impact of Domain Knowledge and Multi-Modality on Intelligent Molecular Property Prediction: A Systematic Survey

Big Data Mining and Analytics
The precise prediction of molecular properties is essential for advancements in drug development, particularly in virtual screening and compound optimization.
Taojie Kuang, Pengfei Liu, Zhixiang Ren
doaj   +3 more sources