On the public citation graph
Virtual Screening Using Binary Kernel Discrimination: Analysis of Pesticide Data
0 signed · 60 inferred · view as graph
Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.
Is this your work? Sign in with ORCID and put your name on the
claims that are yours.
Reference health. See whether every reference in this work resolves to a
known work and none has been retracted — and get a dated CiteStamped
badge you can embed.
What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1002/prot.10115openalex-snapshot
Principles of docking: An overview of search algorithms and a guide to scoring functions
inferredcites →https://doi.org/10.1002/qsar.19890080207openalex-snapshot
Comparison of Fragment Weighting Schemes for Substructural Analysis
inferredcites →https://doi.org/10.1016/s1359-6446(97)01163-xopenalex-snapshot
Virtual screening—an overview
inferredcites →https://doi.org/10.1016/s1367-5931(00)00219-2openalex-snapshot
Visual and computational analysis of structure–activity relationships in high-throughput screening data
inferredcites →https://doi.org/10.1017/cbo9780511801389openalex-snapshot
An Introduction to Support Vector Machines and Other Kernel-based Learning Methods
inferredcites →https://doi.org/10.1021/ci000397qopenalex-snapshot
Prediction of Biological Activity for High-Throughput Screening Using Binary Kernel Discrimination
inferredcites →https://doi.org/10.1021/ci025569topenalex-snapshot
Similarity Metrics for Ligands Reflecting the Similarity of the Target Proteins
inferredcites →https://doi.org/10.1021/ci025586iopenalex-snapshot
Comparison of Ranking Methods for Virtual Screening in Lead-Discovery Programs
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/ci034220iopenalex-snapshot
Detection and Classification of Organophosphate Nerve Agent Simulants Using Support Vector Machines with Multiarray Sensors
inferredcites →https://doi.org/10.1021/ci034231bopenalex-snapshot
Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures
inferredcites →https://doi.org/10.1021/ci049641uopenalex-snapshot
Virtual Screening of Molecular Databases Using a Support Vector Machine
inferredcites →https://doi.org/10.1021/jm00251a014openalex-snapshot
Substructural analysis. Novel approach to the problem of drug design
inferredcites →https://doi.org/10.1021/jm00251a015openalex-snapshot
Preparation and antitumor activity of 4'-thio analogs of 2,2'-anhydro-1-.beta.-D-arabinofuranosylcytosine
inferredcites →https://doi.org/10.1021/pr0255654openalex-snapshot
A New Algorithm for the Evaluation of Shotgun Peptide Sequencing in Proteomics: Support Vector Machine Classification of Peptide MS/MS Spectra and SEQUEST Scores
inferredcites →https://doi.org/10.5555/299094openalex-snapshot
Advances in kernel methods: support vector learning
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/9780470567623.ch4openalex-snapshot
Data Mining Approaches for Compound Selection and Iterative Screening
inferred← citeshttps://doi.org/10.1002/9781118742921.ch2.2openalex-snapshot
Combinatorial Chemistry Library Design
inferred← citeshttps://doi.org/10.1002/9781119564782.ch12openalex-snapshot
Virtual Screening and Bioactivity Modeling for G Protein‐Coupled Receptors
inferred← citeshttps://doi.org/10.1002/9783527645121.ch8openalex-snapshot
Statistical Methods for Predicting Compound Recovery Rates for Ligand‐Based Virtual Screening and Assessing the Probability of Activity
inferred← citeshttps://doi.org/10.1002/aris.2009.1440430108openalex-snapshot
Similarity methods in chemoinformatics
inferred← citeshttps://doi.org/10.1002/jcc.21347openalex-snapshot
Identification of small molecule aggregators from large compound libraries by support vector machines
inferred← citeshttps://doi.org/10.1002/jps.20985openalex-snapshot
Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins
inferred← citeshttps://doi.org/10.1002/minf.201400143openalex-snapshot
Physicochemical Profiles of the Marketed Agrochemicals and Clues for Agrochemical Lead Discovery and Screening Library Development
inferred← citeshttps://doi.org/10.1002/qsar.200860155openalex-snapshot
Similarity‐Based Virtual Screening Using Bayesian Inference Network: Enhanced Search Using 2D Fingerprints and Multiple Reference Structures
inferred← citeshttps://doi.org/10.1007/978-1-4419-9842-2_8openalex-snapshot
Data Mining and Signal Detection
inferred← citeshttps://doi.org/10.1007/s00894-010-0854-xopenalex-snapshot
Brainstorming: weighted voting prediction of inhibitors for protein targets
inferred← citeshttps://doi.org/10.1007/s10822-006-9096-5openalex-snapshot
Evaluation of machine-learning methods for ligand-based virtual screening
inferred← citeshttps://doi.org/10.1007/s11030-021-10326-zopenalex-snapshot
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
inferred← citeshttps://doi.org/10.1016/j.artmed.2011.10.005openalex-snapshot
Prediction of human major histocompatibility complex class II binding peptides by continuous kernel discrimination method
inferred← citeshttps://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
inferred← citeshttps://doi.org/10.1021/acs.accounts.7b00311openalex-snapshot
Mesoionic Pyrido[1,2- a ]pyrimidinone Insecticides: From Discovery to Triflumezopyrim and Dicloromezotiaz
inferred← citeshttps://doi.org/10.1021/acs.jafc.7b00249openalex-snapshot
Discovery of Novel Succinate Dehydrogenase Inhibitors by the Integration of in Silico Library Design and Pharmacophore Mapping
inferred← citeshttps://doi.org/10.1021/acs.jcim.9b01075openalex-snapshot
Ranking Molecules with Vanishing Kernels and a Single Parameter: Active Applicability DomainIncluded
inferred← citeshttps://doi.org/10.1021/acsomega.1c04587openalex-snapshot
Similarity-Based Virtual Screen Using Enhanced Siamese Deep Learning Methods
inferred← citeshttps://doi.org/10.1021/ci0505426openalex-snapshot
Virtual Screening Using Binary Kernel Discrimination: Effect of Noisy Training Data and the Optimization of Performance
inferred← citeshttps://doi.org/10.1021/ci100022uopenalex-snapshot
Classifying Large Chemical Data Sets: Using A Regularized Potential Function Method
inferred← citeshttps://doi.org/10.1021/ci100399jopenalex-snapshot
Ligand Classifier of Adaptively Boosting Ensemble Decision Stumps (LiCABEDS) and Its Application on Modeling Ligand Functionality for 5HT-Subtype GPCR Families
inferred← citeshttps://doi.org/10.1021/ci200128wopenalex-snapshot
Classifying Molecules Using a Sparse Probabilistic Kernel Binary Classifier
inferred← citeshttps://doi.org/10.1021/ci200303mopenalex-snapshot
Note on Naive Bayes Based on Binary Descriptors in Cheminformatics
inferred← citeshttps://doi.org/10.1021/ci300547gopenalex-snapshot
Combination of Similarity Rankings Using Data Fusion
inferred← citeshttps://doi.org/10.1021/ci600186bopenalex-snapshot
Prediction of Multiple Binding Modes of the CDK2 Inhibitors, Anilinopyrazoles, Using the Automated Docking Programs GOLD, FlexX, and LigandFit: An Evaluation of Performance
inferred← citeshttps://doi.org/10.1021/ci700087vopenalex-snapshot
Prediction of Ion Channel Activity Using Binary Kernel Discrimination
inferred← citeshttps://doi.org/10.1021/ci700350nopenalex-snapshot
How To Winnow Actives from Inactives: Introducing Molecular Orthogonal Sparse Bigrams (MOSBs) and Multiclass Winnow
inferred← citeshttps://doi.org/10.1021/ci700461sopenalex-snapshot
Support-Vector-Machine-Based Ranking Significantly Improves the Effectiveness of Similarity Searching Using 2D Fingerprints and Multiple Reference Compounds
inferred← citeshttps://doi.org/10.1021/ci800079xopenalex-snapshot
Ligand-Target Prediction Using Winnow and Naive Bayesian Algorithms and the Implications of Overall Performance Statistics
inferred← citeshttps://doi.org/10.1039/9781847558879-00182openalex-snapshot
Probabilistic Approaches in Activity Prediction
inferred← citeshttps://doi.org/10.1080/08927022.2011.616891openalex-snapshot
Identification of DNA adduct formation of small molecules by molecular descriptors and machine learning methods
inferred← citeshttps://doi.org/10.1371/journal.pone.0038086openalex-snapshot
Application of Consensus Scoring and Principal Component Analysis for Virtual Screening against β-Secretase (BACE-1)
inferred← citeshttps://doi.org/10.1371/journal.pone.0195478openalex-snapshot
Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach
inferred← citeshttps://doi.org/10.1517/17460441.2010.486830openalex-snapshot
Advances in 2D fingerprint similarity searching
inferred← citeshttps://doi.org/10.2477/jccj.h1921openalex-snapshot
Prediction of Carcinogenicity of Noncongeneric Chemical Substances by a Support Vector Machine
inferred← citeshttps://doi.org/10.3390/molecules26216669openalex-snapshot
Similarity-Based Virtual Screen Using Enhanced Siamese Multi-Layer Perceptron
inferred← citeshttps://doi.org/10.34040/ijcb.1.1.2012.12openalex-snapshot
APPLICATIONS OF SUPPORT VECTOR MACHINES AS A ROBUST TOOL IN HIGH THROUGHPUT VIRTUAL SCREENING
inferred← citeshttps://doi.org/10.4018/978-1-61520-911-8.ch010openalex-snapshot
Virtual Screening Methods Based on Bayesian Statistics
inferred← citeshttps://doi.org/10.5539/jmr.v5n1p22openalex-snapshot
The Aitchison and Aitken Kernel Function Revisited
inferred← citeshttps://doi.org/10.9734/jerr/2023/v25i7952openalex-snapshot
Artificial Intelligence in Toxicology and Pharmacology
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.