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Publication search results
found 257 matches
- 2025
- Phasit Charoenkwan, Nalini Schaduangrat, Le Thi Phan, Balachandran Manavalan, Watshara Shoombuatong:
M3S-ALG: Improved and robust prediction of allergenicity of chemical compounds by using a novel multi-step stacking strategy. Future Gener. Comput. Syst. 162: 107455 (2025) - 2024
- Yusuf Alaca, Berkay Emin, Akif Akgul:
A comparative study of deep learning models and classification algorithms for chemical compound identification and Tox21 prediction. Comput. Chem. Eng. 189: 108805 (2024) - Arnau Comajuncosa-Creus, Aksel Lenes, Miguel Sánchez-Palomino, Dylan Dalton, Patrick Aloy:
Stereochemically-aware bioactivity descriptors for uncharacterized chemical compounds. J. Cheminformatics 16(1): 70 (2024) - Ganna Gryn'ova, Tristan Bereau, Carolin Müller, Pascal Friederich, Rebecca C. Wade, Ariane Nunes-Alves, Thereza A. Soares, Kenneth M. Merz Jr.:
EDITORIAL: Chemical Compound Space Exploration by Multiscale High-Throughput Screening and Machine Learning. J. Chem. Inf. Model. 64(15): 5737-5738 (2024) - Yuto Matsumoto, Hiroaki Gotoh:
Compound Classification and Consideration of Correlation with Chemical Descriptors from Articles on Antioxidant Capacity Using Natural Language Processing. J. Chem. Inf. Model. 64(1): 119-127 (2024) - Zijing Tian, Yan Dai, Feng Hu, Zihao Shen, Hongling Xu, Hongwen Zhang, Jinhang Xu, Yuting Hu, Yanyan Diao, Honglin Li:
Enhancing Chemical Reaction Monitoring with a Deep Learning Model for NMR Spectra Image Matching to Target Compounds. J. Chem. Inf. Model. 64(14): 5624-5633 (2024) - Do Hoang Tu, Tran Van Lang, Pham Cong Xuyen, Le Mau Long:
Predicting the activity of chemical compounds based on machine learning approaches. CoRR abs/2401.01004 (2024) - 2023
- Rafael Vieira, Kally Alves de Sousa, Givaldo Souza da Silva, Dulce Helena Siqueira Silva, Ian Castro-Gamboa:
CHEIC: Chemical Image Classificator. An intelligent system for identification of volatiles compounds with potential for respiratory diseases using Deep Learning. Expert Syst. Appl. 234: 121178 (2023) - Yan Xiang, Yu-Hang Tang, Zheng Gong, Hongyi Liu, Liang Wu, Guang Lin, Huai Sun:
Efficient Exploration of Chemical Compound Space Using Active Learning for Prediction of Thermodynamic Properties of Alkane Molecules. J. Chem. Inf. Model. 63(21): 6515-6524 (2023) - Miruna T. Cretu, Alessandra Toniato, Amol Thakkar, Amin A Debabeche, Teodoro Laino, Alain C. Vaucher:
Standardizing chemical compounds with language models. Mach. Learn. Sci. Technol. 4(3): 35014 (2023) - Javier López-Ibáñez, Florencio Pazos, Monica Chagoyen:
MBROLE3: improved functional enrichment of chemical compounds for metabolomics data analysis. Nucleic Acids Res. 51(W1): 305-309 (2023) - Johannes Passig, Julian Schade, Ellen Iva Rosewig, Michael Pütz, Martin Seipenbusch, Sven Ehlert, Heinrich Ruser, Thomas Adam, Andreas Walte, Ralf Zimmermann:
Real-time Detection of Chemical Compounds in Dust Particles Using a Single-Particle Mass Spectrometer and its Potential for Safety Applications. SENSORS 2023: 1-4 - Jaiveer Gill, Ratul Chakraborty, Reetham Gubba, Amy Liu, Shrey Jain, Chirag Iyer, Obaid Khwaja, Saurav Kumar:
Unsupervised Learning of Molecular Embeddings for Enhanced Clustering and Emergent Properties for Chemical Compounds. CoRR abs/2310.18367 (2023) - Yun-Wen Mao, Roman V. Krems:
Efficient interpolation of molecular properties across chemical compound space with low-dimensional descriptors. CoRR abs/2311.15207 (2023) - 2022
- Fan Zhang, Jianshen Zhu, Rachaya Chiewvanichakorn, Aleksandar Shurbevski, Hiroshi Nagamochi, Tatsuya Akutsu:
A new approach to the design of acyclic chemical compounds using skeleton trees and integer linear programming. Appl. Intell. 52(15): 17058-17072 (2022) - Yuliya Shapovalova, Tom Heskes, Tjeerd Dijkstra:
Non-parametric synergy modeling of chemical compounds with Gaussian processes. BMC Bioinform. 23(1): 14 (2022) - Eleni Pitsillou, Julia Liang, Raymond C. Beh, Jacqueline Prestedge, Seda Catak, Andrew Hung, Tom C. Karagiannis:
Identification of novel bioactive compounds from Olea europaea by evaluation of chemical compounds in the OliveNet™ library: in silico bioactivity and molecular modelling, and in vitro validation of hERG activity. Comput. Biol. Medicine 142: 105247 (2022) - Jorge I. Martínez-Araya, Rafael Islas:
Analysis in silico of chemical reactivity employing the local hyper-softness in some classic aromatic compounds, boron aromatic clusters and all-metal aromatic clusters. J. Comput. Chem. 43(1): 29-42 (2022) - Bas van Beek, Juliette Zito, Lucas Visscher, Ivan Infante:
CAT: A Compound Attachment Tool for the Construction of Composite Chemical Compounds. J. Chem. Inf. Model. 62(22): 5525-5535 (2022) - Ryuichiro Ishitani, Toshiki Kataoka, Kentaro Rikimaru:
Molecular Design Method Using a Reversible Tree Representation of Chemical Compounds and Deep Reinforcement Learning. J. Chem. Inf. Model. 62(17): 4032-4048 (2022) - Jianshen Zhu, Naveed Ahmed Azam, Fan Zhang, Aleksandar Shurbevski, Kazuya Haraguchi, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A Novel Method for Inferring Chemical Compounds With Prescribed Topological Substructures Based on Integer Programming. IEEE ACM Trans. Comput. Biol. Bioinform. 19(6): 3233-3245 (2022) - Medard Edmund Mswahili, Junha Hwang, Young-Seob Jeong, YoungJin Kim:
Graph Neural Network Models for Chemical Compound Activeness Prediction For COVID-19 Drugs Discovery using Lipinski's Descriptors. AI4I 2022: 20-21 - Chenru Duan, Aditya Nandy, Gianmarco Terrones, David W. Kastner, Heather J. Kulik:
Rapid Exploration of a 32.5M Compound Chemical Space with Active Learning to Discover Density Functional Approximation Insensitive and Synthetically Accessible Transitional Metal Chromophores. CoRR abs/2208.05444 (2022) - Tanish Jain, Praveen Kumar Pandian Shanmuganathan:
In Silico Prediction of Blood-Brain Barrier Permeability of Chemical Compounds through Molecular Feature Modeling. CoRR abs/2208.09484 (2022) - 2021
- Dimitar G. Yonchev:
Development of Computational Methods for Rationalizing Chemical Lead Optimization and Compound Design. University of Bonn, Germany, 2021 - Naveed Ahmed Azam, Jianshen Zhu, Yanming Sun, Yu Shi, Aleksandar Shurbevski, Liang Zhao, Hiroshi Nagamochi, Tatsuya Akutsu:
A novel method for inference of acyclic chemical compounds with bounded branch-height based on artificial neural networks and integer programming. Algorithms Mol. Biol. 16(1): 18 (2021) - Javier López-Ibáñez, Florencio Pazos, Monica Chagoyen:
Predicting biological pathways of chemical compounds with a profile-inspired approach. BMC Bioinform. 22(1): 320 (2021) - Zhaorui Zuo, Penglei Wang, Xiaowei Chen, Li Tian, Hui Ge, Dahong Qian:
SWnet: a deep learning model for drug response prediction from cancer genomic signatures and compound chemical structures. BMC Bioinform. 22(1): 434 (2021) - Neelam Sharma, Sumeet Patiyal, Anjali Dhall, Naorem Leimarembi Devi, Gajendra P. S. Raghava:
ChAlPred: A web server for prediction of allergenicity of chemical compounds. Comput. Biol. Medicine 136: 104746 (2021) - Márcia Barros, André Moitinho, Francisco M. Couto:
Hybrid semantic recommender system for chemical compounds in large-scale datasets. J. Cheminformatics 13(1): 15 (2021)
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