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Synergy between machine learning and natural products cheminformatics: Application to the lead discovery of anthraquinone derivatives

https://doi.org/10.1111/cbdd.14062
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inferredcites →https://doi.org/10.1002/(sici)1098-2299(199903/04)46:3/4<250::aid-ddr9>3.0.co;2-8openalex-snapshot
High-throughput screening in natural product drug discovery in Australia utilising Australia's biodiversity
inferredcites →https://doi.org/10.1002/ail2.17openalex-snapshot
Assessing methods and obstacles in chemical space exploration
inferredcites →https://doi.org/10.1002/anie.201601941openalex-snapshot
From Complex Natural Products to Simple Synthetic Mimetics by Computational De Novo Design
inferredcites →https://doi.org/10.1002/anie.201605707openalex-snapshot
Deorphaning the Macromolecular Targets of the Natural Anticancer Compound Doliculide
inferredcites →https://doi.org/10.1002/cmdc.200900469openalex-snapshot
From Machine Learning to Natural Product Derivatives that Selectively Activate Transcription Factor PPARγ
inferredcites →https://doi.org/10.1002/ejoc.200400751openalex-snapshot
Conformation‐Directed Macrocyclization Reactions
inferredcites →https://doi.org/10.1002/ejoc.201001715openalex-snapshot
Biologically Active Macrocyclic Compounds – from Natural Products to Diversity‐Oriented Synthesis
inferredcites →https://doi.org/10.1002/ijc.11185openalex-snapshot
Signaling pathway for aloe‐emodin‐induced apoptosis in human H460 lung nonsmall carcinoma cell
inferredcites →https://doi.org/10.1002/med.21764openalex-snapshot
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
inferredcites →https://doi.org/10.1002/minf.201300051openalex-snapshot
Quality Issues with Public Domain Chemogenomics Data
inferredcites →https://doi.org/10.1002/minf.201400072openalex-snapshot
Ring‐System‐Based Exhaustive Structure Generation for Inverse‐QSPR/QSAR
inferredcites →https://doi.org/10.1002/minf.201501008openalex-snapshot
Deep Learning in Drug Discovery
inferredcites →https://doi.org/10.1002/minf.202000171openalex-snapshot
Cheminformatics in Natural Product‐based Drug Discovery
inferredcites →https://doi.org/10.1002/prot.26068openalex-snapshot
Predicting new protein conformations from molecular dynamics simulation conformational landscapes and machine learning
inferredcites →https://doi.org/10.1002/widm.1312openalex-snapshot
Causability and explainability of artificial intelligence in medicine
inferredcites →https://doi.org/10.1007/978-3-030-14632-0_1openalex-snapshot
Cheminformatics Explorations of Natural Products
inferredcites →https://doi.org/10.1007/978-3-030-30493-5_67openalex-snapshot
Predictive Power of Time-Series Based Machine Learning Models for DMPK Measurements in Drug Discovery
inferredcites →https://doi.org/10.1007/978-3-319-18305-3_1openalex-snapshot
What Is Machine Learning?
inferredcites →https://doi.org/10.1007/s00011-017-1096-5openalex-snapshot
Nature is the best source of anti-inflammatory drugs: indexing natural products for their anti-inflammatory bioactivity
inferredcites →https://doi.org/10.1007/s00894-017-3384-yopenalex-snapshot
Ensemble-based virtual screening: identification of a potential allosteric inhibitor of Bcr-Abl
inferredcites →https://doi.org/10.1007/s10295-006-0107-2openalex-snapshot
Drug discovery from natural products
inferredcites →https://doi.org/10.1007/s10822-007-9125-zopenalex-snapshot
Estimating the domain of applicability for machine learning QSAR models: a study on aqueous solubility of drug discovery molecules
inferredcites →https://doi.org/10.1007/s10822-018-0146-6openalex-snapshot
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges
inferredcites →https://doi.org/10.1007/s11095-015-1629-yopenalex-snapshot
In Silico Predictions of Human Skin Permeability using Nonlinear Quantitative Structure–Property Relationship Models
inferredcites →https://doi.org/10.1007/s12094-006-0048-2openalex-snapshot
High throughput screening in drug discovery
inferredcites →https://doi.org/10.1016/b978-0-12-802104-0.00012-3openalex-snapshot
Other Plant Metabolites
inferredcites →https://doi.org/10.1016/b978-0-444-63504-4.00020-7openalex-snapshot
Metabolic Engineering to Synthetic Biology of Secondary Metabolites Production
inferredcites →https://doi.org/10.1016/bs.armc.2017.08.004openalex-snapshot
High-Throughput Screening
inferredcites →https://doi.org/10.1016/bs.mie.2018.09.022openalex-snapshot
Hit-to-Lead: Hit Validation and Assessment
inferredcites →https://doi.org/10.1016/j.biotechadv.2015.08.001openalex-snapshot
Discovery and resupply of pharmacologically active plant-derived natural products: A review
inferredcites →https://doi.org/10.1016/j.bmc.2006.06.024openalex-snapshot
Drug Guru: A computer software program for drug design using medicinal chemistry rules
inferredcites →https://doi.org/10.1016/j.bmc.2008.07.067openalex-snapshot
New QSPR study for the prediction of aqueous solubility of drug-like compounds
inferredcites →https://doi.org/10.1016/j.bpj.2020.01.012openalex-snapshot
Classifying Drugs by their Arrhythmogenic Risk Using Machine Learning
inferredcites →https://doi.org/10.1016/j.brainres.2003.08.042openalex-snapshot
Differential involvement of spinal protein kinase C and protein kinase A in neuropathic and inflammatory pain in mice
inferredcites →https://doi.org/10.1016/j.canlet.2009.09.016openalex-snapshot
Aloe-emodin induces apoptosis of human nasopharyngeal carcinoma cells via caspase-8-mediated activation of the mitochondrial death pathway
inferredcites →https://doi.org/10.1016/j.chemolab.2009.01.010openalex-snapshot
Development of a fast and accurate method of 13C NMR chemical shift prediction
inferredcites →https://doi.org/10.1016/j.cmpb.2018.08.011openalex-snapshot
BE-DTI’: Ensemble framework for drug target interaction prediction using dimensionality reduction and active learning
inferredcites →https://doi.org/10.1016/j.ddtec.2020.06.001openalex-snapshot
Practical considerations for active machine learning in drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2017.08.010openalex-snapshot
From machine learning to deep learning: progress in machine intelligence for rational drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2018.05.010openalex-snapshot
Machine learning in chemoinformatics and drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2019.10.014openalex-snapshot
A drug-likeness toolbox facilitates ADMET study in drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2020.01.020openalex-snapshot
Exploring chemical space using natural language processing methodologies for drug discovery
inferredcites →https://doi.org/10.1016/j.drudis.2020.07.005openalex-snapshot
Advancing computer-aided drug discovery (CADD) by big data and data-driven machine learning modeling
inferredcites →https://doi.org/10.1016/j.ejphar.2014.05.028openalex-snapshot
Antiviral activity of aloe-emodin against influenza A virus via galectin-3 up-regulation
inferredcites →https://doi.org/10.1016/j.ejps.2015.04.026openalex-snapshot
QSAR based docking studies of marine algal anticancer compounds as inhibitors of protein kinase B (PKBβ)
inferredcites →https://doi.org/10.1016/j.jep.2008.11.008openalex-snapshot
Anti-angiogenic effects of rhubarb and its anthraquinone derivatives
inferredcites →https://doi.org/10.1016/j.jmgm.2007.12.002openalex-snapshot
A support vector machines approach for virtual screening of active compounds of single and multiple mechanisms from large libraries at an improved hit-rate and enrichment factor
inferredcites →https://doi.org/10.1016/j.jmgm.2014.10.011openalex-snapshot
Principal Component Analysis reveals correlation of cavities evolution and functional motions in proteins
inferredcites →https://doi.org/10.1016/j.jmgm.2016.08.001openalex-snapshot
Chemogenomics knowledgebase and systems pharmacology for hallucinogen target identification—Salvinorin A as a case study
inferredcites →https://doi.org/10.1016/j.lfs.2011.09.008openalex-snapshot
Aloe-emodin as antiproliferative and differentiating agent on human U937 monoblastic leukemia cells
inferredcites →https://doi.org/10.1016/j.saa.2017.02.014openalex-snapshot
Aloe emodin, an anthroquinone from Aloe vera acts as an anti aggregatory agent to the thermally aggregated hemoglobin
inferredcites →https://doi.org/10.1016/j.tim.2007.04.001openalex-snapshot
New aspects of natural products in drug discovery
inferredcites →https://doi.org/10.1016/j.vascn.2013.08.001openalex-snapshot
A high content screening assay to predict human drug-induced liver injury during drug discovery
inferredcites →https://doi.org/10.1016/s0014-2999(01)01467-4openalex-snapshot
Effects and mechanisms of aloe-emodin on cell death in human lung squamous cell carcinoma
inferredcites →https://doi.org/10.1016/s0024-3205(02)01900-8openalex-snapshot
The antiproliferative activity of aloe-emodin is through p53-dependent and p21-dependent apoptotic pathway in human hepatoma cell lines
inferredcites →https://doi.org/10.1016/s0165-1218(96)90105-6openalex-snapshot
Genotoxicity of the laxative drug components emodin, aloe-emodin and danthron in mammalian cells: Topoisomerase II mediated?
inferredcites →https://doi.org/10.1017/s0140525x16001837openalex-snapshot
Building machines that learn and think like people
inferredcites →https://doi.org/10.1017/s0953756202006342openalex-snapshot
Endophytic fungi: a source of novel biologically active secondary metabolites
inferredcites →https://doi.org/10.1021/ac025516aopenalex-snapshot
High-Throughput Analysis of Natural Product Compound Libraries by Parallel LC−MS Evaporative Light Scattering Detection
inferredcites →https://doi.org/10.1021/ac025534sopenalex-snapshot
High-Throughput Method for the Production and Analysis of Large Natural Product Libraries for Drug Discovery
inferredcites →https://doi.org/10.1021/acs.jcim.0c00293openalex-snapshot
Prediction of Natural Product Classes Using Machine Learning and 13C NMR Spectroscopic Data
inferredcites →https://doi.org/10.1021/acs.jcim.0c00675openalex-snapshot
ZINC20─A Free Ultralarge-Scale Chemical Database for Ligand Discovery
inferredcites →https://doi.org/10.1021/acs.jcim.1c00260openalex-snapshot
Discovery of Natural Products Targeting NQO1 via an Approach Combining Network-Based Inference and Identification of Privileged Substructures
inferredcites →https://doi.org/10.1021/acs.jcim.7b00341openalex-snapshot
Data Resources for the Computer-Guided Discovery of Bioactive Natural Products
inferredcites →https://doi.org/10.1021/acs.jcim.8b00524openalex-snapshot
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inferredcites →https://doi.org/10.1021/acs.jcim.9b00367openalex-snapshot
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inferredcites →https://doi.org/10.1021/acs.jcim.9b00645openalex-snapshot
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inferredcites →https://doi.org/10.1021/acs.jctc.6b00201openalex-snapshot
Prediction of Protein–Ligand Binding Poses via a Combination of Induced Fit Docking and Metadynamics Simulations
inferredcites →https://doi.org/10.1021/acs.jmedchem.7b01120openalex-snapshot
Importance of Rigidity in Designing Small Molecule Drugs To Tackle Protein–Protein Interactions (PPIs) through Stabilization of Desired Conformers
inferredcites →https://doi.org/10.1021/acs.jnatprod.0c01076openalex-snapshot
Development of an NMR-Based Platform for the Direct Structural Annotation of Complex Natural Products Mixtures
inferredcites →https://doi.org/10.1021/acs.jnatprod.5b01055openalex-snapshot
Natural Products as Sources of New Drugs from 1981 to 2014
inferredcites →https://doi.org/10.1021/acs.jnatprod.9b01285openalex-snapshot
Natural Products as Sources of New Drugs over the Nearly Four Decades from 01/1981 to 09/2019
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.7b00346openalex-snapshot
druGAN: An Advanced Generative Adversarial Autoencoder Model for de Novo Generation of New Molecules with Desired Molecular Properties in Silico
inferredcites →https://doi.org/10.1021/acs.molpharmaceut.8b00110openalex-snapshot
Prediction of Human Cytochrome P450 Inhibition Using a Multitask Deep Autoencoder Neural Network
inferredcites →https://doi.org/10.1021/acscentsci.0c00229openalex-snapshot
Deep Docking: A Deep Learning Platform for Augmentation of Structure Based Drug Discovery
inferredcites →https://doi.org/10.1021/acschembio.8b00389openalex-snapshot
NCI Program for Natural Product Discovery: A Publicly-Accessible Library of Natural Product Fractions for High-Throughput Screening
inferredcites →https://doi.org/10.1021/acsomega.0c00442openalex-snapshot
Variational Autoencoder for Generation of Antimicrobial Peptides
inferredcites →https://doi.org/10.1021/cb5001636openalex-snapshot
Increasing Chemical Space Coverage by Combining Empirical and Computational Fragment Screens
inferredcites →https://doi.org/10.1021/cc0000388openalex-snapshot
Chemography: The Art of Navigating in Chemical Space
inferredcites →https://doi.org/10.1021/cc000097lopenalex-snapshot
Scaffold Architecture and Pharmacophoric Properties of Natural Products and Trade Drugs: Application in the Design of Natural Product-Based Combinatorial Libraries
inferredcites →https://doi.org/10.1021/ci0003303openalex-snapshot
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inferredcites →https://doi.org/10.1021/ci0200467openalex-snapshot
Property Distributions: Differences between Drugs, Natural Products, and Molecules from Combinatorial Chemistry
inferredcites →https://doi.org/10.1021/ci025554vopenalex-snapshot
DISE: Directed Sphere Exclusion
inferredcites →https://doi.org/10.1021/ci025620topenalex-snapshot
Active Learning with Support Vector Machines in the Drug Discovery Process
inferredcites →https://doi.org/10.1021/ci050352vopenalex-snapshot
Assessing the Scaffold Diversity of Screening Libraries
inferredcites →https://doi.org/10.1021/ci1002087openalex-snapshot
Natural Product-Like Virtual Libraries: Recursive Atom-Based Enumeration
inferredcites →https://doi.org/10.1021/ci100503yopenalex-snapshot
Novel Method for Pharmacophore Analysis by Examining the Joint Pharmacophore Space
inferredcites →https://doi.org/10.1021/ci2001428openalex-snapshot
Scaffold Diversity of Exemplified Medicinal Chemistry Space
inferredcites →https://doi.org/10.1021/ci300535xopenalex-snapshot
Visualization and Virtual Screening of the Chemical Universe Database GDB-17
inferredcites →https://doi.org/10.1021/ci400382ropenalex-snapshot
Development and Evaluation of an Integrated Virtual Screening Strategy by Combining Molecular Docking and Pharmacophore Searching Based on Multiple Protein Structures
inferredcites →https://doi.org/10.1021/ci500747nopenalex-snapshot
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inferredcites →https://doi.org/10.1021/ci700286xopenalex-snapshot
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inferredcites →https://doi.org/10.1021/ci800272aopenalex-snapshot
Searching Fragment Spaces with Feature Trees
inferredcites →https://doi.org/10.1021/ci990087bopenalex-snapshot
Mining and Visualizing Large Anticancer Drug Discovery Databases
inferredcites →https://doi.org/10.1021/jacs.9b13786openalex-snapshot
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inferredcites →https://doi.org/10.1021/jm010283lopenalex-snapshot
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inferredcites →https://doi.org/10.1021/jm9602928openalex-snapshot
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inferredcites →https://doi.org/10.1021/jp212634zopenalex-snapshot
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inferredcites →https://doi.org/10.1021/mp0700413openalex-snapshot
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inferredcites →https://doi.org/10.1021/mp100465qopenalex-snapshot
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inferredcites →https://doi.org/10.1021/np800184gopenalex-snapshot
Marine Natural Product Libraries for High-Throughput Screening and Rapid Drug Discovery
inferredcites →https://doi.org/10.1021/np9007359openalex-snapshot
Automated High-Throughput System to Fractionate Plant Natural Products for Drug Discovery
inferredcites →https://doi.org/10.1034/j.1600-0773.2000.d01-79.xopenalex-snapshot
Aloe-Emodin Quinone Pretreatment Reduces Acute Liver Injury Induced by Carbon Tetrachloride
inferredcites →https://doi.org/10.1038/nature09454openalex-snapshot
Clinical efficacy of a RAF inhibitor needs broad target blockade in BRAF-mutant melanoma
inferredcites →https://doi.org/10.1038/nbt1284openalex-snapshot
Relating protein pharmacology by ligand chemistry
inferredcites →https://doi.org/10.1038/nchem.1243openalex-snapshot
Quantifying the chemical beauty of drugs
inferredcites →https://doi.org/10.1038/nchem.2479openalex-snapshot
Counting on natural products for drug design
inferredcites →https://doi.org/10.1038/nchembio.180openalex-snapshot
Quantifying biogenic bias in screening libraries
inferredcites →https://doi.org/10.1038/nrd2590openalex-snapshot
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inferredcites →https://doi.org/10.1038/nrd2796openalex-snapshot
The influence of lead discovery strategies on the properties of drug candidates
inferredcites →https://doi.org/10.1038/nrd3368openalex-snapshot
Impact of high-throughput screening in biomedical research
inferredcites →https://doi.org/10.1038/nrd4510openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41423-020-00559-7openalex-snapshot
Expression of leukotriene B4 receptor 1 defines functionally distinct DCs that control allergic skin inflammation
inferredcites →https://doi.org/10.1038/s41570-018-0066-yopenalex-snapshot
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inferredcites →https://doi.org/10.1038/s41573-019-0024-5openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41573-020-00114-zopenalex-snapshot
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inferredcites →https://doi.org/10.1038/s41573-020-00117-wopenalex-snapshot
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inferredcites →https://doi.org/10.1038/s41586-019-0917-9openalex-snapshot
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inferredcites →https://doi.org/10.1038/s41587-019-0224-xopenalex-snapshot
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inferredcites →https://doi.org/10.1038/srep25462openalex-snapshot
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inferredcites →https://doi.org/10.1038/srep34972openalex-snapshot
Correction: Corrigendum: In silico identification of anti-cancer compounds and plants from traditional Chinese medicine database
inferredcites →https://doi.org/10.1039/b715668popenalex-snapshot
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inferredcites →https://doi.org/10.1039/c0md00020eopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c1sc00152copenalex-snapshot
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inferredcites →https://doi.org/10.1039/c3np70063aopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c4np00134fopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c6np00025hopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c7ob02193copenalex-snapshot
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inferredcites →https://doi.org/10.1039/c8fo01569dopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c9cp06303jopenalex-snapshot
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inferredcites →https://doi.org/10.1039/c9sc00616hopenalex-snapshot
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inferredcites →https://doi.org/10.1039/d0md00315hopenalex-snapshot
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inferredcites →https://doi.org/10.1039/d0md00429dopenalex-snapshot
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inferredcites →https://doi.org/10.1039/d0np00043dopenalex-snapshot
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inferredcites →https://doi.org/10.1055/s-0028-1088397openalex-snapshot
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inferredcites →https://doi.org/10.1055/s-0042-102460openalex-snapshot
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inferredcites →https://doi.org/10.1073/pnas.1208978109openalex-snapshot
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inferredcites →https://doi.org/10.1073/pnas.1507743112openalex-snapshot
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inferredcites →https://doi.org/10.1073/pnas.1914677117openalex-snapshot
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inferredcites →https://doi.org/10.1074/jbc.m411221200openalex-snapshot
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inferredcites →https://doi.org/10.1080/09513590701200850openalex-snapshot
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inferredcites →https://doi.org/10.1080/17460441.2021.1909567openalex-snapshot
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inferredcites →https://doi.org/10.1093/bib/bbv042openalex-snapshot
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inferredcites →https://doi.org/10.1093/bioinformatics/16.8.747openalex-snapshot
PASS: prediction of activity spectra for biologically active substances
inferredcites →https://doi.org/10.1093/bioinformatics/btv334openalex-snapshot
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inferredcites →https://doi.org/10.1093/bioinformatics/btx638openalex-snapshot
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inferredcites →https://doi.org/10.1093/nar/gkl999openalex-snapshot
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inferredcites →https://doi.org/10.1096/fj.202000041ropenalex-snapshot
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inferredcites →https://doi.org/10.1101/2020.07.29.227959openalex-snapshot
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inferredcites →https://doi.org/10.1109/iccisci.2012.6297272openalex-snapshot
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inferredcites →https://doi.org/10.1109/tmi.2011.2134865openalex-snapshot
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inferredcites →https://doi.org/10.1111/cbdd.12448openalex-snapshot
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inferredcites →https://doi.org/10.1111/cbdd.13674openalex-snapshot
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inferredcites →https://doi.org/10.1111/cbdd.13788openalex-snapshot
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inferredcites →https://doi.org/10.1124/dmd.104.000356openalex-snapshot
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inferredcites →https://doi.org/10.1126/sciadv.aap7885openalex-snapshot
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inferredcites →https://doi.org/10.1126/science.1168243openalex-snapshot
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inferredcites →https://doi.org/10.1126/science.1192788openalex-snapshot
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inferredcites →https://doi.org/10.1177/1087057108319644openalex-snapshot
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inferredcites →https://doi.org/10.1177/1087057109335678openalex-snapshot
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inferredcites →https://doi.org/10.1177/1087057111433459openalex-snapshot
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inferredcites →https://doi.org/10.1177/2472555220942765openalex-snapshot
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Virtual Screening on Natural Products for Discovering Active Compounds and Target Information
inferredcites →https://doi.org/10.2174/092986709787002655openalex-snapshot
Self-Organizing Maps in Drug Discovery: Compound Library Design, Scaffold-Hopping, Repurposing
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inferredcites →https://doi.org/10.2174/1570163054064684openalex-snapshot
QSAR Modeling of Carcinogenic Risk Using Discriminant Analysis and Topological Molecular Descriptors
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inferredcites →https://doi.org/10.2174/1876396001003010194openalex-snapshot
Physicochemical Properties of Natural Based Products versus Synthetic Chemicals~!2010-03-18~!2010-04-26~!2010-06-09~!
inferredcites →https://doi.org/10.2217/pgs.13.162openalex-snapshot
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inferredcites →https://doi.org/10.3389/fgene.2018.00477openalex-snapshot
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NP-Scout: Machine Learning Approach for the Quantification and Visualization of the Natural Product-Likeness of Small Molecules
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Incoming claims: where this work appears in other papers’ reference lists and arguments.

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Additional file 1 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
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Additional file 2 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
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Additional file 3 of Consensus holistic virtual screening for drug discovery: a novel machine learning model approach
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.