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ORCIDJournal of Cheminformatics, Volume 16
Volume 16, Number 1, December 2024
- Soyeon Lee, Sunyong Yoo:
InterDILI: interpretable prediction of drug-induced liver injury through permutation feature importance and attention mechanism. 1 - Debby D. Wang, Wenhui Wu, Ran Wang:
Structure-based, deep-learning models for protein-ligand binding affinity prediction. 2 - Lukasz Maziarka, Dawid Majchrowski, Tomasz Danel, Piotr Gainski, Jacek Tabor, Igor T. Podolak, Pawel M. Morkisz, Stanislaw Jastrzebski:
Relative molecule self-attention transformer. 3 - Yaxin Gu, Yimeng Wang, Keyun Zhu, Weihua Li, Guixia Liu, Yun Tang:
DBPP-Predictor: a novel strategy for prediction of chemical drug-likeness based on property profiles. 4 - Sadettin Y. Ugurlu, David W. McDonald, Huangshu Lei, Alan M. Jones, Shu Li, Henry H. Y. Tong, Mark S. Butler, Shan He:
Cobdock: an accurate and practical machine learning-based consensus blind docking method. 5 - Barbara Zdrazil
, Rajarshi Guha, Karina Martínez-Mayorga, Nina Jeliazkova:
Are new ideas harder to find? A note on incremental research and Journal of Cheminformatics' Scientific Contribution Statement. 6 - Tinghao Zhang, Shaohua Sun, Runzhou Wang, Ting Li, Bicheng Gan, Yuezhou Zhang:
BioisoIdentifier: an online free tool to investigate local structural replacements from PDB. 7 - Sadjad Fakouri Baygi, Dinesh Kumar Barupal:
IDSL_MINT: a deep learning framework to predict molecular fingerprints from mass spectra. 8 - Paula Carracedo-Reboredo, Eider Aranzamendi, Shan He, Sonia Arrasate, Cristian R. Munteanu, Carlos Fernandez-Lozano, Nuria Sotomayor, Esther Lete, Humberto González Díaz:
MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products. 9 - Wei-Cheng Huang, Wei-Ting Lin, Ming-Shiu Hung, Jinq-Chyi Lee, Chun-Wei Tung:
Decrypting orphan GPCR drug discovery via multitask learning. 10 - Lung-Yi Chen, Yi-Pei Li:
Enhancing chemical synthesis: a two-stage deep neural network for predicting feasible reaction conditions. 11 - Anuj Gahlawat, Anjali Singh, Hardeep Sandhu, Prabha Garg:
CRAFT: a web-integrated cavity prediction tool based on flow transfer algorithm. 12 - Jiangxia Wu, Yihao Chen, Jingxing Wu, Duancheng Zhao, Jindi Huang, MuJie Lin, Ling Wang:
Large-scale comparison of machine learning methods for profiling prediction of kinase inhibitors. 13 - Jonghyun Lee, Dae Won Jun, Ildae Song, Yun Kim:
DLM-DTI: a dual language model for the prediction of drug-target interaction with hint-based learning. 14 - Derek Long, Liam Eade, Matthew P. Sullivan, Katharina Dost, Samuel M. Meier-Menches, David C. Goldstone, Christian G. Hartinger, Jörg S. Wicker, Katerina Taskova:
AdductHunter: identifying protein-metal complex adducts in mass spectra. 15 - Alexander S. Behr, Hendrik Borgelt, Norbert Kockmann:
Ontologies4Cat: investigating the landscape of ontologies for catalysis research data management. 16 - Kamel Mansouri, José T. Moreira-Filho, Charles N. Lowe, Nathaniel Charest, Todd Martin, Valery Tkachenko, Richard S. Judson, Mike Conway, Nicole C. Kleinstreuer, Antony J. Williams:
Free and open-source QSAR-ready workflow for automated standardization of chemical structures in support of QSAR modeling. 19 - Candida Manelfi, Valerio Tazzari, Filippo Lunghini, Carmen Cerchia, Anna Fava, Alessandro Pedretti, Pieter F. W. Stouten, Giulio Vistoli, Andrea Rosario Beccari:
"DompeKeys": a set of novel substructure-based descriptors for efficient chemical space mapping, development and structural interpretation of machine learning models, and indexing of large databases. 21 - Runhan Shi, Gufeng Yu, Xiaohong Huo, Yang Yang:
Prediction of chemical reaction yields with large-scale multi-view pre-training. 22 - Olivier Beyens, Hans De Winter:
Preventing lipophilic aggregation in cosolvent molecular dynamics simulations with hydrophobic probes using Plumed Automatic Restraining Tool (PART). 23 - Adrià Cereto-Massagué, Santiago Garcia-Vallvé, Gerard Pujadas:
Correction: DecoyFinder, a tool for finding decoy molecules. 24 - Jongmin Han, Youngchun Kwon, Youn-Suk Choi, Seokho Kang:
Improving chemical reaction yield prediction using pre-trained graph neural networks. 25 - Marie Oestreich, Iva Ewert, Matthias Becker:
Small molecule autoencoders: architecture engineering to optimize latent space utility and sustainability. 26 - Karina Beatriz Jimenes Vargas, Alejandro Pazos, Cristian R. Munteanu, Yunierkis Pérez-Castillo, Eduardo Tejera:
Prediction of compound-target interaction using several artificial intelligence algorithms and comparison with a consensus-based strategy. 27 - Sabrina Jaeger-Honz, Karsten Klein, Falk Schreiber:
Systematic analysis, aggregation and visualisation of interaction fingerprints for molecular dynamics simulation data. 28 - Bowen Tang, Zhangming Niu, Xiaofeng Wang, Junjie Huang, Chao Ma, Jing Peng, Yinghui Jiang, Ruiquan Ge, Hongyu Hu, Luhao Lin, Guang Yang:
Automated molecular structure segmentation from documents using ChemSAM. 29 - Tsuyoshi Esaki, Tomoki Yonezawa, Kazuyoshi Ikeda:
A new workflow for the effective curation of membrane permeability data from open ADME information. 30 - Alex K. Chew, Matthew Sender, Zachary Kaplan, Anand Chandrasekaran, Jackson Chief Elk, Andrea R. Browning, H. Shaun Kwak, Mathew D. Halls, Mohammad Atif Faiz Afzal:
Advancing material property prediction: using physics-informed machine learning models for viscosity. 31 - Anna Carbery, Martin Buttenschoen, Rachael Skyner, Frank von Delft, Charlotte M. Deane:
Learnt representations of proteins can be used for accurate prediction of small molecule binding sites on experimentally determined and predicted protein structures. 32 - Lingling Shen, Jian Fang, Lulu Liu, Fei Yang, Jeremy L. Jenkins, Peter S. Kutchukian, He Wang:
Pocket Crafter: a 3D generative modeling based workflow for the rapid generation of hit molecules in drug discovery. 33 - Matteo Krüger, Ashmi Mishra, Peter Spichtinger, Ulrich Pöschl, Thomas Berkemeier:
A numerical compass for experiment design in chemical kinetics and molecular property estimation. 34 - Davide Boldini, Davide Ballabio, Viviana Consonni, Roberto Todeschini, Francesca Grisoni, Stephan A. Sieber:
Effectiveness of molecular fingerprints for exploring the chemical space of natural products. 35 - Thomas E. Lockwood, Alexander Angeloski:
DGet! An open source deuteration calculator for mass spectrometry data. 36 - Maarten R. Dobbelaere, István Lengyel, Christian V. Stevens, Kevin M. Van Geem:
Rxn-INSIGHT: fast chemical reaction analysis using bond-electron matrices. 37 - Wenjia Qian, Xiaorui Wang, Yu Kang, Peichen Pan, Tingjun Hou, Chang-Yu Hsieh:
A general model for predicting enzyme functions based on enzymatic reactions. 38 - Peter B. R. Hartog, Fabian Krüger, Samuel Genheden, Igor V. Tetko:
Using test-time augmentation to investigate explainable AI: inconsistencies between method, model and human intuition. 39 - Klaudia Caba, Viet-Khoa Tran-Nguyen, Taufiq Rahman, Pedro J. Ballester:
Comprehensive machine learning boosts structure-based virtual screening for PARP1 inhibitors. 40 - Xinwei Zhao, Junqing Xu, Youyuan Shui, Mengdie Xu, Jie Hu, Xiaoyan Liu, Kai Che, Junjie Wang, Yun Liu:
PermuteDDS: a permutable feature fusion network for drug-drug synergy prediction. 41 - Michael Blakey, Samantha Kanza, Jeremy G. Frey:
Zombie cheminformatics: extraction and conversion of Wiswesser Line Notation (WLN) from chemical documents. 42 - Sébastien J. J. Guesné, Thierry Hanser, Stéphane Werner, Samuel Boobier, Shaylyn Scott:
Mind your prevalence! 43 - Ming Du, Xingran Xie, Jing Luo, Jin Li:
Meta-learning-based Inductive logistic matrix completion for prediction of kinase inhibitors. 44 - Satnam Singh, Gina Zeh, Jessica Freiherr, Thilo Bauer, Isik Türkmen, Andreas Grasskamp:
Classification of substances by health hazard using deep neural networks and molecular electron densities. 45
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