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Journal of Cheminformatics, Volume 13
Volume 13, Number 1, December 2021
- Rick Helmus, Thomas L. ter Laak, Annemarie P. van Wezel, Pim de Voogt, Emma Schymanski:
patRoon: open source software platform for environmental mass spectrometry based non-target screening. 1 - Maria Sorokina, Peter Merseburger, Kohulan Rajan, Mehmet Aziz Yirik, Christoph Steinbeck:
COCONUT online: Collection of Open Natural Products database. 2 - Ivan Cmelo, Milan Vorsilák, Daniel Svozil:
Profiling and analysis of chemical compounds using pointwise mutual information. 3 - Umit V. Ucak, Taek Kang, Junsu Ko, Juyong Lee:
Substructure-based neural machine translation for retrosynthetic prediction. 4 - Kohulan Rajan, Jan-Mathis Hein, Christoph Steinbeck, Achim Zielesny:
Molecule Set Comparator (MSC): a CDK-based open rich-client tool for molecule set similarity evaluations. 5 - Xujun Zhang, Chao Shen, Xueying Guo, Zhe Wang, Gaoqi Weng, Qing Ye, Gaoang Wang, Qiaojun He, Bo Yang, Dong-Sheng Cao, Tingjun Hou:
ASFP (Artificial Intelligence based Scoring Function Platform): a web server for the development of customized scoring functions. 6 - Jianwen Chen, Shuangjia Zheng, Huiying Zhao, Yuedong Yang:
Structure-aware protein solubility prediction from sequence through graph convolutional network and predicted contact map. 7 - Yu-Chieh Huang, Pierre Tremouilhac, An Nguyen, Nicole Jung, Stefan Bräse:
ChemSpectra: a web-based spectra editor for analytical data. 8 - Agnieszka Gajewicz-Skretna, Supratik Kar, Magdalena Piotrowska, Jerzy Leszczynski:
The kernel-weighted local polynomial regression (KwLPR) approach: an efficient, novel tool for development of QSAR/QSAAR toxicity extrapolation models. 9 - Nicolai Ree, Andreas H. Göller, Jan H. Jensen:
RegioSQM20: improved prediction of the regioselectivity of electrophilic aromatic substitutions. 10 - Beihong Ji, Xibing He, Yuzhao Zhang, Jingchen Zhai, Viet Hoang Man, Shuhan Liu, Junmei Wang:
Incorporating structural similarity into a scoring function to enhance the prediction of binding affinities. 11 - Dejun Jiang, Zhenxing Wu, Chang-Yu Hsieh, Guangyong Chen, Ben Liao, Zhe Wang, Chao Shen, Dong-Sheng Cao, Jian Wu, Tingjun Hou:
Could graph neural networks learn better molecular representation for drug discovery? A comparison study of descriptor-based and graph-based models. 12 - Nicolas Bosc, Eloy Felix, Ricardo Arcila, David Mendez, Martin R. Saunders, Darren V. S. Green, Jason Ochoada, Anang A. Shelat, Eric J. Martin, Preeti Iyer, Ola Engkvist, Andreas Verras, James Duffy, Jeremy N. Burrows, J. Mark F. Gardner, Andrew R. Leach:
MAIP: a web service for predicting blood-stage malaria inhibitors. 13 - Andrew E. Blanchard, Christopher B. Stanley, Debsindhu Bhowmik:
Using GANs with adaptive training data to search for new molecules. 14 - Márcia Barros, André Moitinho, Francisco M. Couto:
Hybrid semantic recommender system for chemical compounds in large-scale datasets. 15 - Rajarshi Guha, Egon L. Willighagen, Barbara Zdrazil, Nina Jeliazkova:
What is the role of cheminformatics in a pandemic? 16 - Leen Kalash, Ian Winfield, Dewi Safitri, Marcel Bermudez, Sabrina Carvalho, Robert C. Glen, Graham Ladds, Andreas Bender:
Structure-based identification of dual ligands at the A2AR and PDE10A with anti-proliferative effects in lung cancer cell-lines. 17 - Annachiara Tinivella, Luca Pinzi, Giulio Rastelli:
Prediction of activity and selectivity profiles of human Carbonic Anhydrase inhibitors using machine learning classification models. 18 - Emma Schymanski, Todor Kondic, Steffen Neumann, Paul A. Thiessen, Jian Zhang, Evan Bolton:
Empowering large chemical knowledge bases for exposomics: PubChemLite meets MetFrag. 19 - Kohulan Rajan, Henning Otto Brinkhaus, Maria Sorokina, Achim Zielesny, Christoph Steinbeck:
DECIMER-Segmentation: Automated extraction of chemical structure depictions from scientific literature. 20 - Tiago Pereira, Maryam Abbasi, Bernardete Ribeiro, Joel P. Arrais:
Diversity oriented Deep Reinforcement Learning for targeted molecule generation. 21 - Bingyin Hu, Anqi Lin, L. Catherine Brinson:
ChemProps: A RESTful API enabled database for composite polymer name standardization. 22 - Janna Hastings, Martin Glauer, Adel Memariani, Fabian Neuhaus, Till Mossakowski:
Learning chemistry: exploring the suitability of machine learning for the task of structure-based chemical ontology classification. 23 - Yongbeom Kwon, Juyong Lee:
MolFinder: an evolutionary algorithm for the global optimization of molecular properties and the extensive exploration of chemical space using SMILES. 24 - Sana Naseem, Yasuyuki Zushi, Deedar Nabi:
Development and evaluation of two-parameter linear free energy models for the prediction of human skin permeability coefficient of neutral organic chemicals. 25 - Jiazhen He, Huifang You, Emil Sandström, Eva Nittinger, Esben Jannik Bjerrum, Christian Tyrchan, Werngard Czechtizky, Ola Engkvist:
Molecular optimization by capturing chemist's intuition using deep neural networks. 26 - Hiroyuki Kuwahara, Xin Gao:
Analysis of the effects of related fingerprints on molecular similarity using an eigenvalue entropy approach. 27 - Surendra Kumar, Mi-Hyun Kim:
SMPLIP-Score: predicting ligand binding affinity from simple and interpretable on-the-fly interaction fingerprint pattern descriptors. 28 - Amit Kumar Halder, M. Natália Dias Soeiro Cordeiro:
QSAR-Co-X: an open source toolkit for multitarget QSAR modelling. 29 - Fan Hu, Jiaxin Jiang, Dongqi Wang, Muchun Zhu, Peng Yin:
Multi-PLI: interpretable multi-task deep learning model for unifying protein-ligand interaction datasets. 30 - Manuel Pastor, José C. Gómez-Tamayo, Ferran Sanz:
Flame: an open source framework for model development, hosting, and usage in production environments. 31 - Ramón Alain Miranda-Quintana, Dávid Bajusz, Anita Rácz, Károly Héberger:
Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 1: Theory and characteristics†. 32 - Ramón Alain Miranda-Quintana, Anita Rácz, Dávid Bajusz, Károly Héberger:
Extended similarity indices: the benefits of comparing more than two objects simultaneously. Part 2: speed, consistency, diversity selection. 33 - Kohulan Rajan, Achim Zielesny, Christoph Steinbeck:
STOUT: SMILES to IUPAC names using neural machine translation. 34 - Andrea Morger, Fredrik Svensson, Staffan Arvidsson McShane, Niharika Gauraha, Ulf Norinder, Ola Spjuth, Andrea Volkamer:
Assessing the calibration in toxicological in vitro models with conformal prediction. 35 - Narumi Watanabe, Yuuto Ohnuki, Yasubumi Sakakibara:
Deep learning integration of molecular and interactome data for protein-compound interaction prediction. 36 - Bakary N'tji Diallo, Michael Glenister, Thommas M. Musyoka, Kevin A. Lobb, Özlem Tastan Bishop:
SANCDB: an update on South African natural compounds and their readily available analogs. 37 - Jakub Galgonek, Jirí Vondrásek:
IDSM ChemWebRDF: SPARQLing small-molecule datasets. 38 - Morgan C. Thomas, Robert T. Smith, Noel M. O'Boyle, Chris de Graaf, Andreas Bender:
Comparison of structure- and ligand-based scoring functions for deep generative models: a GPCR case study. 39 - Jonathan M. Goodman, Igor V. Pletnev, Paul A. Thiessen, Evan Bolton, Stephen R. Heller:
InChI version 1.06: now more than 99.99% reliable. 40 - Mariia Matveieva, Pavel G. Polishchuk:
Benchmarks for interpretation of QSAR models. 41 - Carl E. Belle, Vural Aksakalli, Salvy P. Russo:
A machine learning platform for the discovery of materials. 42 - Andrew T. McNutt, Paul G. Francoeur, Rishal Aggarwal, Tomohide Masuda, Rocco Meli, Matthew Ragoza, Jocelyn Sunseri, David Ryan Koes:
GNINA 1.0: molecular docking with deep learning. 43 - Faraz Shaikh, Hio Kuan Tai, Nirali Desai, Shirley W. I. Siu:
LigTMap: ligand and structure-based target identification and activity prediction for small molecular compounds. 44 - Ondrej Schindler, Tomás Racek, Aleksandra Marsavelski, Jaroslav Koca, Karel Berka, Radka Svobodová Vareková:
Optimized SQE atomic charges for peptides accessible via a web application. 45 - Naruki Yoshikawa, Ryuichi Kubo, Kazuki Z. Yamamoto:
Twitter integration of chemistry software tools. 46 - Dea Gogishvili, Eva Nittinger, Christian Margreitter, Christian Tyrchan:
Nonadditivity in public and inhouse data: implications for drug design. 47 - Mehmet Aziz Yirik, Maria Sorokina, Christoph Steinbeck:
MAYGEN: an open-source chemical structure generator for constitutional isomers based on the orderly generation principle. 48 - Rajarshi Guha, Nina Jeliazkova, Egon L. Willighagen, Barbara Zdrazil:
Reply to "FAIR chemical structure in the Journal of Cheminformatics". 49 - Emma Schymanski, Evan Bolton:
FAIR chemical structures in the Journal of Cheminformatics. 50 - Jan Prívratský, Jirí Novák:
MassSpecBlocks: a web-based tool to create building blocks and sequences of nonribosomal peptides and polyketides for tandem mass spectra analysis. 51 - Ondrej Schindler, Tomás Racek, Aleksandra Marsavelski, Jaroslav Koca, Karel Berka, Radka Svobodová Vareková:
Correction to: Optimized SQE atomic charges for peptides accessible via a web application. 52 - Ruben Pawellek, Jovana Krmar, Adrian Leistner, Nevena Djajic, Biljana Otasevic, Ana Protic, Ulrike Holzgrabe:
Charged aerosol detector response modeling for fatty acids based on experimental settings and molecular features: a machine learning approach. 53 - Candida Manelfi, Marica Gemei, Carmine Talarico, Carmen Cerchia, Anna Fava, Filippo Lunghini, Andrea Rosario Beccari:
"Molecular Anatomy": a new multi-dimensional hierarchical scaffold analysis tool. 54 - Lea Seep, Anne Bonin, Katharina Meier, Holger Diedam, Andreas H. Göller:
Ensemble completeness in conformer sampling: the case of small macrocycles. 55 - Hyuntae Lim, YounJoon Jung:
MLSolvA: solvation free energy prediction from pairwise atomistic interactions by machine learning. 56 - Stefan M. Kohlbacher, Thierry Langer, Thomas Seidel:
QPHAR: quantitative pharmacophore activity relationship: method and validation. 57 - Guannan Liu, Manali Singha, Limeng Pu, Prasanga Neupane, Joseph Feinstein, Hsiao-Chun Wu, J. Ramanujam, Michal Brylinski:
GraphDTI: A robust deep learning predictor of drug-target interactions from multiple heterogeneous data. 58 - Rocco Meli, Andrew Anighoro, Michael J. Bodkin, Garrett M. Morris, Philip C. Biggin:
Learning protein-ligand binding affinity with atomic environment vectors. 59 - Abdul Karim, Matthew Lee, Thomas Balle, Abdul Sattar:
CardioTox net: a robust predictor for hERG channel blockade based on deep learning meta-feature ensembles. 60 - Kohulan Rajan, Achim Zielesny, Christoph Steinbeck:
DECIMER 1.0: deep learning for chemical image recognition using transformers. 61 - Lewis H. Mervin, Maria-Anna Trapotsi, Avid M. Afzal, Ian P. Barrett, Andreas Bender, Ola Engkvist:
Probabilistic Random Forest improves bioactivity predictions close to the classification threshold by taking into account experimental uncertainty. 62 - Jason Y. C. Tam, Tim Lorsbach, Sebastian Schmidt, Jörg Wicker:
Holistic evaluation of biodegradation pathway prediction: assessing multi-step reactions and intermediate products. 63 - Fidele Ntie-Kang, Kiran K. Telukunta, Serge A. T. Fobofou, Victor Chukwudi Osamor, Samuel A. Egieyeh, Marilia Valli, Yannick Djoumbou Feunang, Maria Sorokina, Conrad Stork, Neann Mathai, Paul F. Zierep, Ana L. Chávez-Hernández, Miquel Duran-Frigola, Smith B. Babiaka, Romuald Tematio Fouedjou, Donatus B. Eni, Simeon Akame, Augustine B. Arreyetta-Bawak, Oyere T. Ebob, Jonathan A. Metuge, Boris D. Bekono, Mustafa A. Isa, Raphael Onuku, Daniel M. Shadrack, Thommas M. Musyoka, Vaishali M. Patil, Justin J. J. van der Hooft, Vanderlan da Silva Bolzani, José L. Medina-Franco, Johannes Kirchmair, Tilmann Weber, Özlem Tastan Bishop, Marnix H. Medema, Ludger A. Wessjohann, Jutta Ludwig-Müller:
Computational Applications in Secondary Metabolite Discovery (CAiSMD): an online workshop. 64 - Jeevan Kandel, Hilal Tayara, Kil To Chong:
PUResNet: prediction of protein-ligand binding sites using deep residual neural network. 65 - Stefan Mordalski, Agnieszka Wojtuch, Igor T. Podolak, Rafal Kurczab, Andrzej J. Bojarski:
2D SIFt: a matrix of ligand-receptor interactions. 66 - Péter Árendás, Tibor Furtenbacher, Attila G. Császár:
Selecting lines for spectroscopic (re)measurements to improve the accuracy of absolute energies of rovibronic quantum states. 67 - Feifei Guo, Chunhong Jiang, Yujie Xi, Dan Wang, Yi Zhang, Ning Xie, Yi Guan, Fangbo Zhang, Hongjun Yang:
Investigation of pharmacological mechanism of natural product using pathway fingerprints similarity based on "drug-target-pathway" heterogenous network. 68 - Dingyan Wang, Jie Yu, Lifan Chen, Xutong Li, Hualiang Jiang, Kaixian Chen, Mingyue Zheng, Xiaomin Luo:
A hybrid framework for improving uncertainty quantification in deep learning-based QSAR regression modeling. 69 - Rosa Aghdam, Mahnaz Habibi, Golnaz Taheri:
Using informative features in machine learning based method for COVID-19 drug repurposing. 70 - Maha A. Thafar, Rawan S. Olayan, Somayah Albaradei, Vladimir B. Bajic, Takashi Gojobori, Magbubah Essack, Xin Gao:
DTi2Vec: Drug-target interaction prediction using network embedding and ensemble learning. 71 - Cédric Bouysset, Sébastien Fiorucci:
ProLIF: a library to encode molecular interactions as fingerprints. 72 - Martin Sícho, Xuhan Liu, Daniel Svozil, Gerard J. P. van Westen:
GenUI: interactive and extensible open source software platform for de novo molecular generation and cheminformatics. 73 - Agnieszka Wojtuch, Rafal Jankowski, Sabina Podlewska:
How can SHAP values help to shape metabolic stability of chemical compounds? 74 - Vishwesh Venkatraman:
FP-ADMET: a compendium of fingerprint-based ADMET prediction models. 75 - Jules Leguy, Marta Glavatskikh, Thomas Cauchy, Benoit Da Mota:
Scalable estimator of the diversity for de novo molecular generation resulting in a more robust QM dataset (OD9) and a more efficient molecular optimization. 76 - Ulf Norinder, Ola Spjuth, Fredrik Svensson:
Synergy conformal prediction applied to large-scale bioactivity datasets and in federated learning. 77 - Myriam Guillevic, Aurore Guillevic, Martin K. Vollmer, Paul Schlauri, Matthias Hill, Lukas Emmenegger, Stefan Reimann:
Automated fragment formula annotation for electron ionisation, high resolution mass spectrometry: application to atmospheric measurements of halocarbons. 78 - Jennifer Handsel, Brian Matthews, Nicola J. Knight, Simon J. Coles:
Translating the InChI: adapting neural machine translation to predict IUPAC names from a chemical identifier. 79 - Giovanni Cincilla, Simone Masoni, Jascha Blobel:
Individual and collective human intelligence in drug design: evaluating the search strategy. 80 - Chao Shen, Xueping Hu, Junbo Gao, Xujun Zhang, Haiyang Zhong, Zhe Wang, Lei Xu, Yu Kang, Dong-Sheng Cao, Tingjun Hou:
The impact of cross-docked poses on performance of machine learning classifier for protein-ligand binding pose prediction. 81 - Alice Capecchi, Jean-Louis Reymond:
Classifying natural products from plants, fungi or bacteria using the COCONUT database and machine learning. 82 - Kyrylo Klimenko, Gonçalo V. S. M. Carrera:
QSPR modeling of selectivity at infinite dilution of ionic liquids. 83 - Florian Huber, Sven van der Burg, Justin J. J. van der Hooft, Lars Ridder:
MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra. 84 - Xuhan Liu, Kai Ye, Herman W. T. van Vlijmen, Michael T. M. Emmerich, Adriaan P. IJzerman, Gerard J. P. van Westen:
DrugEx v2: de novo design of drug molecules by Pareto-based multi-objective reinforcement learning in polypharmacology. 85 - Zi-Yi Yang, Li Fu, Ai-Ping Lu, Shao Liu, Tingjun Hou, Dong-Sheng Cao:
Semi-automated workflow for molecular pair analysis and QSAR-assisted transformation space expansion. 86 - Shuangjia Zheng, Zengrong Lei, Haitao Ai, Hongming Chen, Daiguo Deng, Yuedong Yang:
Deep scaffold hopping with multimodal transformer neural networks. 87 - Francois Berenger, Koji Tsuda:
Molecular generation by Fast Assembly of (Deep)SMILES fragments. 88 - Jeff Guo, Jon Paul Janet, Matthias R. Bauer, Eva Nittinger, Kathryn A. Giblin, Kostas Papadopoulos, Alexey Voronov, Atanas Patronov, Ola Engkvist, Christian Margreitter:
DockStream: a docking wrapper to enhance de novo molecular design. 89 - Merveille K. I. Eguida, Didier Rognan:
Unexpected similarity between HIV-1 reverse transcriptase and tumor necrosis factor binding sites revealed by computer vision. 90 - Bryan Dafniet, Natacha Cerisier, Batiste Boezio, Anaelle Clary, Pierre Ducrot, Thierry Dorval, Arnaud Gohier, David Brown, Karine Audouze, Olivier Taboureau:
Development of a chemogenomics library for phenotypic screening. 91 - Scott S. Kolmar, Christopher M. Grulke:
The effect of noise on the predictive limit of QSAR models. 92 - Jiarui Chen, Yain-Whar Si, Chon-Wai Un, Shirley W. I. Siu:
Chemical toxicity prediction based on semi-supervised learning and graph convolutional neural network. 93 - Daiki Erikawa, Nobuaki Yasuo, Masakazu Sekijima:
MERMAID: an open source automated hit-to-lead method based on deep reinforcement learning. 94 - Xinyu Bai, Yuxin Yin:
Exploration and augmentation of pharmacological space via adversarial auto-encoder model for facilitating kinase-centric drug development. 95 - Jaak Simm, Lina Humbeck, Adam Zalewski, Noé Sturm, Wouter Heyndrickx, Yves Moreau, Bernd Beck, Ansgar Schuffenhauer:
Splitting chemical structure data sets for federated privacy-preserving machine learning. 96 - Zenan Zhai, Christian Druckenbrodt, Camilo Thorne, Saber A. Akhondi, Dat Quoc Nguyen, Trevor Cohn, Karin Verspoor:
ChemTables: a dataset for semantic classification on tables in chemical patents. 97 - Zhuyifan Ye, Defang Ouyang:
Prediction of small-molecule compound solubility in organic solvents by machine learning algorithms. 98 - Errol L. G. Samuel, Secondra L. Holmes, Damian W. Young:
Processing binding data using an open-source workflow. 99 - David Ferro-Costas, Irea Mosquera-Lois, Antonio Fernández-Ramos:
TorsiFlex: an automatic generator of torsional conformers. Application to the twenty proteinogenic amino acids. 100
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