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Journal of Cheminformatics, Volume 15
Volume 15, Number 1, December 2023
- Felix Bänsch
, Jonas Schaub
MORTAR: a rich client application for in silico molecule fragmentation. 1 - Henry Heberle, Linlin Zhao, Sebastian Schmidt
XSMILES: interactive visualization for molecules, SMILES and XAI attribution scores. 2 - Olivier J. M. Béquignon
Papyrus: a large-scale curated dataset aimed at bioactivity predictions. 3 - Shunsuke Tamura, Tomoyuki Miyao, Jürgen Bajorath:
Large-scale prediction of activity cliffs using machine and deep learning methods of increasing complexity. 4 - Dane R. Letourneau
New algorithms demonstrate untargeted detection of chemically meaningful changing units and formula assignment for HRMS data of polymeric mixtures in the open-source constellation web application. 7 - Jonghwan Choi, Sangmin Seo, Sanghyun Park:
COMA: efficient structure-constrained molecular generation using contractive and margin losses. 8 - David H. Kenney, Randy C. Paffenroth, Michael T. Timko
Dimensionally reduced machine learning model for predicting single component octanol-water partition coefficients. 9 - Salomé Rieder
Development of an open-source software for isomer enumeration. 10 - Vladimir Kondratyev, Marian Dryzhakov, Timur Gimadiev, Dmitriy Slutskiy:
Generative model based on junction tree variational autoencoder for HOMO value prediction and molecular optimization. 11 - Mingchen Li, Liqi Kang, Yi Xiong, Yu Guang Wang, Guisheng Fan, Pan Tan
SESNet: sequence-structure feature-integrated deep learning method for data-efficient protein engineering. 12 - Chu-I Yang, Yi-Pei Li
Explainable uncertainty quantifications for deep learning-based molecular property prediction. 13 - Egon L. Willighagen
Two years of explicit CiTO annotations. 14 - Rajarshi Guha, Barbara Zdrazil
A look back at a pilot of the citation typing ontology. 15 - Heval Atas Güvenilir
How to approach machine learning-based prediction of drug/compound-target interactions. 16 - Gao-Peng Ren, Yi-Jian Yin, Ke-Jun Wu
Force field-inspired molecular representation learning for property prediction. 17 - Manuel S. Sellner, Amr H. Mahmoud, Markus A. Lill
Efficient virtual high-content screening using a distance-aware transformer model. 18 - Samuel Tovey, Fabian Zills
MDSuite: comprehensive post-processing tool for particle simulations. 19 - Paulo Neves
Global reactivity models are impactful in industrial synthesis applications. 20 - Phyo Phyo Kyaw Zin:
Paths to cheminformatics: Q&A with Phyo Phyo Kyaw Zin. 21 - Linde Schoenmaker
UnCorrupt SMILES: a novel approach to de novo design. 22 - Felix Bänsch
Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C10E4/water mixture with lamellar bilayer formation. 23 - Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Adriaan P. IJzerman, Gerard J. P. van Westen
DrugEx v3: scaffold-constrained drug design with graph transformer-based reinforcement learning. 24 - Andrius Merkys
Graph isomorphism-based algorithm for cross-checking chemical and crystallographic descriptions. 25 - Umit V. Ucak, Islambek Ashyrmamatov
Reconstruction of lossless molecular representations from fingerprints. 26 - Yuanbing Song, Jinghua Chen, Wenju Wang
Double-head transformer neural network for molecular property prediction. 27 - Jim Boelrijk
Predicting RP-LC retention indices of structurally unknown chemicals from mass spectrometry data. 28 - Chengyou Liu, Yan Sun, Rebecca L. Davis, Silvia T. Cardona, Pingzhao Hu:
ABT-MPNN: an atom-bond transformer-based message-passing neural network for molecular property prediction. 29 - Paulo Neves, Kelly McClure, Jonas Verhoeven, Natalia Dyubankova, Ramil I. Nugmanov, Andrey Gedich, Sairam Menon, Zhicai Shi, Jörg K. Wegner:
Correction: Global reactivity models are impactful in industrial synthesis applications. 30 - Ammar Ammar
PSnpBind-ML: predicting the effect of binding site mutations on protein-ligand binding affinity. 31 - Mahnoor Zulfiqar, Luiz M. R. Gadelha Jr.
MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry. 32 - Mengdie Xu, Xinwei Zhao, Jingyu Wang, Wei Feng, Naifeng Wen, Chunyu Wang, Junjie Wang, Yun Liu, Lingling Zhao:
DFFNDDS: prediction of synergistic drug combinations with dual feature fusion networks. 33 - Aileen Bahl, Celine Ibrahim, Kristina Plate
PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping. 34 - Chaofeng Lou, Hongbin Yang, Hua Deng, Mengting Huang, Weihua Li, Guixia Liu, Philip W. Lee, Yun Tang:
Chemical rules for optimization of chemical mutagenicity via matched molecular pairs analysis and machine learning methods. 35 - Jonathan Lam, Richard J. Lewis
Interpreting vibrational circular dichroism spectra: the Cai•factor for absolute configuration with confidence. 36 - Roman Joeres
GlyLES: Grammar-based Parsing of Glycans from IUPAC-condensed to SMILES. 37 - Yangyang Chen
Deep generative model for drug design from protein target sequence. 38 - Bryan Queme
qHTSWaterfall: 3-dimensional visualization software for quantitative high-throughput screening (qHTS) data. 39 - Sascha Jung, Helge Vatheuer
VSFlow: an open-source ligand-based virtual screening tool. 40 - Marta Pasquini, Marco Stenta:
LinChemIn: SynGraph - a data model and a toolkit to analyze and compare synthetic routes. 41 - Xiaohong Liu, Wei Zhang, Xiaochu Tong, Feisheng Zhong, Zhaojun Li, Zhaoping Xiong, Jiacheng Xiong, Xiaolong Wu, Zunyun Fu, Xiaoqin Tan, Zhiguo Liu, Sulin Zhang, Hualiang Jiang, Xutong Li, Mingyue Zheng:
MolFilterGAN: a progressively augmented generative adversarial network for triaging AI-designed molecules. 42 - Kexin Chen
MetaRF: attention-based random forest for reaction yield prediction with a few trails. 43 - Kostas Blekos, Kostas Chairetakis, Iseult Lynch
Principles and requirements for nanomaterial representations to facilitate machine processing and cooperation with nanoinformatics tools. 44 - Shumpei Nemoto, Tadahaya Mizuno, Hiroyuki Kusuhara:
Investigation of chemical structure recognition by encoder-decoder models in learning progress. 45 - Eva Nittinger, Alex Clark, Anna Gaulton
Biomedical data analyses facilitated by open cheminformatics workflows. 46 - Markus Dablander
Exploring QSAR models for activity-cliff prediction. 47 - Su-Qing Yang, Liu-Xia Zhang, You-Jin Ge, Jin-Wei Zhang, Jian-Xin Hu, Cheng-Ying Shen, Ai-Ping Lu, Tingjun Hou, Dong-Sheng Cao:
In-silico target prediction by ensemble chemogenomic model based on multi-scale information of chemical structures and protein sequences. 48 - Thomas-Martin Dutschmann, Lennart Kinzel, Antonius ter Laak
Large-scale evaluation of k-fold cross-validation ensembles for uncertainty estimation. 49 - Nalini Schaduangrat, Nuttapat Anuwongcharoen, Phasit Charoenkwan, Watshara Shoombuatong:
DeepAR: a novel deep learning-based hybrid framework for the interpretable prediction of androgen receptor antagonists. 50 - Doris Schicker
OWSum: algorithmic odor prediction and insight into structure-odor relationships. 51 - Eleftheria Kontou, Axel Walter, Oliver Alka, Julianus Pfeuffer, Timo Sachsenberg, Omkar S. Mohite
UmetaFlow: an untargeted metabolomics workflow for high-throughput data processing and analysis. 52 - Katharina Dost
Combatting over-specialization bias in growing chemical databases. 53 - Rajarshi Guha, Darrell Velegol:
Harnessing Shannon entropy-based descriptors in machine learning models to enhance the prediction accuracy of molecular properties. 54 - Umit V. Ucak, Islambek Ashyrmamatov
Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization. 55 - Srijit Seal
Merging bioactivity predictions from cell morphology and chemical fingerprint models using similarity to training data. 56 - Zimei Zhang, Gang Wang, Rui Li, Lin Ni, Runze Zhang, Kaiyang Cheng, Qun Ren, Xiangtai Kong, Shengkun Ni, Xiaochu Tong, Li Luo, Dingyan Wang, Xiaojie Lu, Mingyue Zheng, Xutong Li
Tora3D: an autoregressive torsion angle prediction model for molecular 3D conformation generation. 57 - Junren Li
RetroRanker: leveraging reaction changes to improve retrosynthesis prediction through re-ranking. 58 - Andrew E. Blanchard, Debsindhu Bhowmik, Zachary R. Fox, John Gounley
Adaptive language model training for molecular design. 59 - Filippo Lunghini, Anna Fava, Vincenzo Pisapia, Francesco Sacco, Daniela Iaconis, Andrea Rosario Beccari:
ProfhEX: AI-based platform for small molecules liability profiling. 60 - Jakub Galgonek, Jirí Vondrásek:
A comparison of approaches to accessing existing biological and chemical relational databases via SPARQL. 61 - Charles Tapley Hoyt
Improving reproducibility and reusability in the Journal of Cheminformatics. 62 - Xujun Zhang
TB-IECS: an accurate machine learning-based scoring function for virtual screening. 63 - Michael A. Cunningham, Danielle Pins, Zoltán Dezso, Maricel Torrent, Aparna Vasanthakumar, Abhishek Pandey:
PINNED: identifying characteristics of druggable human proteins using an interpretable neural network. 64 - Jun-Xuan Jin
Force field-inspired transformer network assisted crystal density prediction for energetic materials. 65 - Parker Ladd Bremer, Gert Wohlgemuth, Oliver Fiehn:
The BinDiscover database: a biology-focused meta-analysis tool for 156,000 GC-TOF MS metabolome samples. 66 - Kenza Amara, Raquel Rodríguez-Pérez, José Jiménez-Luna:
Explaining compound activity predictions with a substructure-aware loss for graph neural networks. 67 - Umit V. Ucak, Islambek Ashyrmamatov, Juyong Lee
Correction: Reconstruction of lossless molecular representations from fingerprints. 68 - Pawan Panwar
PyL3dMD: Python LAMMPS 3D molecular descriptors package. 69 - Umit V. Ucak, Islambek Ashyrmamatov, Juyong Lee
Correction: Improving the quality of chemical language model outcomes with atom-in-SMILES tokenization. 70 - Hyun Woo Kim, Chen Zhang, Raphael Reher, Mingxun Wang, Kelsey L. Alexander, Louis-Félix Nothias
DeepSAT: Learning Molecular Structures from Nuclear Magnetic Resonance Data. 71 - Baiqing Li
A deep learning framework for accurate reaction prediction and its application on high-throughput experimentation data. 72 - Davide Boldini, Francesca Grisoni, Daniel Kuhn, Lukas Friedrich, Stephan A. Sieber:
Practical guidelines for the use of gradient boosting for molecular property prediction. 73 - Marina Gorostiola González
3DDPDs: describing protein dynamics for proteochemometric bioactivity prediction. A case for (mutant) G protein-coupled receptors. 74 - Yumeng Zhang, Janosch Menke
Similarity-based pairing improves efficiency of siamese neural networks for regression tasks and uncertainty quantification. 75 - Yitian Wang, Jiacheng Xiong, Fu Xiao, Wei Zhang, Kaiyang Cheng, Jingxin Rao, Buying Niu, Xiaochu Tong, Ning Qu, Runze Zhang, Dingyan Wang, Kaixian Chen, Xutong Li
LogD7.4 prediction enhanced by transferring knowledge from chromatographic retention time, microscopic pKa and logP. 76 - Bongsung Bae, Haelee Bae, Hojung Nam
LOGICS: Learning optimal generative distribution for designing de novo chemical structures. 77 - Rita Lasfar, Gergely Tóth:
Patch seriation to visualize data and model parameters. 78 - Rodrigo Ochoa
pyPept: a python library to generate atomistic 2D and 3D representations of peptides. 79 - Gerard Baquer, Lluc Sementé, Pere Ràfols, Lucía Martín-Saiz
rMSIfragment: improving MALDI-MSI lipidomics through automated in-source fragment annotation. 80 - Agnieszka Wojtuch, Tomasz Danel
Extended study on atomic featurization in graph neural networks for molecular property prediction. 81 - Karla Gonzalez-Ponce
School of cheminformatics in Latin America. 82 - Maud Parrot, Hamza Tajmouati, Vinicius Barros Ribeiro da Silva, Brian Ross Atwood, Robin Fourcade, Yann Gaston-Mathé, Nicolas Do Huu, Quentin Perron:
Integrating synthetic accessibility with AI-based generative drug design. 83 - Thomas E. Hadfield, Jack Scantlebury, Charlotte M. Deane:
Exploring the ability of machine learning-based virtual screening models to identify the functional groups responsible for binding. 84 - Christopher Secker, Konstantin Fackeldey, Marcus Weber, Sourav Ray, Christoph Gorgulla, Christof Schütte:
Novel multi-objective affinity approach allows to identify pH-specific μ-opioid receptor agonists. 85 - Prasannavenkatesh Durai
Iterative machine learning-based chemical similarity search to identify novel chemical inhibitors. 86 - Ximin Hu, Derek Mar, Nozomi Suzuki, Bowei Zhang, Katherine T. Peter, David A. C. Beck, Edward P. Kolodziej:
Mass-Suite: a novel open-source python package for high-resolution mass spectrometry data analysis. 87 - Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu:
Probabilistic generative transformer language models for generative design of molecules. 88 - Alan Kerstjens
A molecule perturbation software library and its application to study the effects of molecular design constraints. 89 - Jackson J. Alcázar
Reliable and accurate prediction of basic pKa values in nitrogen compounds: the pKa shift in supramolecular systems as a case study. 90 - Chao Hu, Song Li
ScaffoldGVAE: scaffold generation and hopping of drug molecules via a variational autoencoder based on multi-view graph neural networks. 91 - Nathaniel Charest:
Paths to cheminformatics: Q&A with Nathaniel Charest. 92 - Ann M. Richard:
Paths to cheminformatics: Q&A with Ann M. Richard. 93 - Mehrdad Jalali
MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal-organic frameworks utilizing graph convolutional networks. 94 - Jorge Medina, Andrew D. White:
Bloom filters for molecules. 95 - Alberto Gil Pichardo, Andrés Sánchez-Ruiz
Analysis of metabolites in human gut: illuminating the design of gut-targeted drugs. 96 - Nan Song, Ruihan Dong
Pmf-cpi: assessing drug selectivity with a pretrained multi-functional model for compound-protein interactions. 97 - Venkata Chandrasekhar
Cheminformatics Microservice: unifying access to open cheminformatics toolkits. 98 - Arash Tayyebi
Prediction of organic compound aqueous solubility using machine learning: a comparison study of descriptor-based and fingerprints-based models. 99 - Daniela Gaytán-Hernández, Ana L. Chávez-Hernández, Edgar López-López, Jazmín Miranda-Salas, Fernanda I. Saldívar-González, José L. Medina-Franco:
Art driven by visual representations of chemical space. 100 - Zachary Fralish
DeepDelta: predicting ADMET improvements of molecular derivatives with deep learning. 101 - Guzel Minibaeva, Aleksandra Ivanova, Pavel G. Polishchuk:
EasyDock: customizable and scalable docking tool. 102 - Shihang Wang
DeepSA: a deep-learning driven predictor of compound synthesis accessibility. 103 - Sean Li
Determining the parent and associated fragment formulae in mass spectrometry via the parent subformula graph. 104 - Tianzhixi Yin, Gihan Panapitiya, Elizabeth D. Coda, Emily Saldanha
Evaluating uncertainty-based active learning for accelerating the generalization of molecular property prediction. 105 - Gil Alon
Continuous symmetry and chirality measures: approximate algorithms for large molecular structures. 106 - Daniel Domingo-Fernández, Yojana Gadiya
Exploring the known chemical space of the plant kingdom: insights into taxonomic patterns, knowledge gaps, and bioactive regions. 107 - Mehrdad Jalali
Correction: MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal-organic frameworks utilizing graph convolutional networks. 108 - Chong Zhou, Wei Liu, Xiyue Song, Mengling Yang, Xiaowang Peng:
YoDe-Segmentation: automated noise-free retrieval of molecular structures from scientific publications. 111 - Koichi Handa, Morgan C. Thomas, Michiharu Kageyama, Takeshi Iijima, Andreas Bender:
On the difficulty of validating molecular generative models realistically: a case study on public and proprietary data. 112 - Daniel Probst
An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification. 113 - Herman Rull, Markus Fischer, Stefan Kuhn:
NMR shift prediction from small data quantities. 114 - Hong-Quan Xu, Huan Xiao, Jin-Hui Bu, Yan-Feng Hong, Yu-Hong Liu, Zi-Yue Tao, Shu-Fan Ding, Yi-Tong Xia, E. Wu, Zhen Yan, Wei Zhang, Gong-Xing Chen, Feng Zhu
EMNPD: a comprehensive endophytic microorganism natural products database for prompt the discovery of new bioactive substances. 115 - Etienne Lehembre, Johanna Giovannini, Damien Geslin, Alban Lepailleur, Jean Luc Lamotte, David Auber, Abdelkader Ouali, Bruno Crémilleux, Albrecht Zimmermann, Bertrand Cuissart, Ronan Bureau
Towards a partial order graph for interactive pharmacophore exploration: extraction of pharmacophores activity delta. 116 - Ibrahim Roshan Kunnakkattu
PDBe CCDUtils: an RDKit-based toolkit for handling and analysing small molecules in the Protein Data Bank. 117 - Long Chen, Rining Wu
HybridGCN for protein solubility prediction with adaptive weighting of multiple features. 118 - Gregory A. Landrum, Maximilian Beckers, Jessica Lanini, Nadine Schneider, Nikolaus Stiefl, Sereina Riniker:
SIMPD: an algorithm for generating simulated time splits for validating machine learning approaches. 119 - Yugo Shimizu, Masateru Ohta
AI-driven molecular generation of not-patented pharmaceutical compounds using world open patent data. 120 - Maria H. Rasmussen, Chenru Duan, Heather J. Kulik, Jan H. Jensen:
Uncertain of uncertainties? A comparison of uncertainty quantification metrics for chemical data sets. 121 - Jasmin Hack, Moritz Jordan, Alina Schmitt, Melissa Raru, Hannes Sönke Zorn, Alex Seyfarth, Isabel Eulenberger, Robert Geitner:
Ilm-NMR-P31: an open-access 31P nuclear magnetic resonance database and data-driven prediction of 31P NMR shifts. 122 - Antanas Vaitkus
A workflow for deriving chemical entities from crystallographic data and its application to the Crystallography Open Database. 123 - Benoit Baillif
Applying atomistic neural networks to bias conformer ensembles towards bioactive-like conformations. 124 - Ansar Naseem, Fahad Alturise
BBB-PEP-prediction: improved computational model for identification of blood-brain barrier peptides using blending position relative composition specific features and ensemble modeling. - Sven Marcel Stefan
HD_BPMDS: a curated binary pattern multitarget dataset of Huntington's disease-targeting agents. - Wen-feng Shen, He-wei Tang, Jia-bo Li, Xiang Li, Si Chen
Multimodal data fusion for supervised learning-based identification of USP7 inhibitors: a systematic comparison. - Grzegorz Skoraczynski
Critical assessment of synthetic accessibility scores in computer-assisted synthesis planning.
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