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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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