On the public citation graph

“In-House Likeness”: Comparison of Large Compound Collections Using Artificial Neural Networks

https://doi.org/10.1021/ci049702o
0 signed · 33 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.
Claim with ORCID
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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1021/ci0003810openalex-snapshot
Improving the Odds in Discriminating “Drug-like” from “Non Drug-like” Compounds
inferredcites →https://doi.org/10.1021/ci00063a006openalex-snapshot
Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics
inferredcites →https://doi.org/10.1021/ci00063a007openalex-snapshot
Review of ring perception algorithms for chemical graphs
inferredcites →https://doi.org/10.1021/ci0100649openalex-snapshot
New Diversity Calculations Algorithms Used for Compound Selection
inferredcites →https://doi.org/10.1021/ci0102721openalex-snapshot
Prediction of CNS Activity of Compound Libraries Using Substructure Analysis
inferredcites →https://doi.org/10.1021/ci025538yopenalex-snapshot
Property-Based Design of GPCR-Targeted Library
inferredcites →https://doi.org/10.1021/ci0302862openalex-snapshot
Drugs and Nondrugs: An Effective Discrimination with Topological Methods and Artificial Neural Networks
inferredcites →https://doi.org/10.1021/ci030340eopenalex-snapshot
Artificial Neural Networks and Linear Discriminant Analysis: A Valuable Combination in the Selection of New Antibacterial Compounds
inferredcites →https://doi.org/10.1021/ci034114gopenalex-snapshot
Structure-Based versus Property-Based Approaches in the Design of G-Protein-Coupled Receptor-Targeted Libraries
inferredcites →https://doi.org/10.1021/ci960151eopenalex-snapshot
Clustering of Large Databases of Compounds: Using the MDL “Keys” as Structural Descriptors
inferredcites →https://doi.org/10.1021/ci960463hopenalex-snapshot
Rapid Quantification of Molecular Diversity for Selective Database Acquisition
inferredcites →https://doi.org/10.1021/jm0302795openalex-snapshot
Prediction of Biological Targets Using Probabilistic Neural Networks and Atom-Type Descriptors
inferredcites →https://doi.org/10.1021/jm970666copenalex-snapshot
Can We Learn To Distinguish between “Drug-like” and “Nondrug-like” Molecules?
inferredcites →https://doi.org/10.1021/jm9706776openalex-snapshot
A Scoring Scheme for Discriminating between Drugs and Nondrugs
inferredcites →https://doi.org/10.1023/a:1020811805001openalex-snapshot
An overview of the diversity represented in commercially-available databases
inferredcites →https://doi.org/10.2174/138620704772884832openalex-snapshot
(Research Papers) Design of a Compound Screening Collection for use in High Throughput Screening
inferredcites →https://doi.org/10.5860/choice.41-5919openalex-snapshot
An introduction to chemoinformatics

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/9783527621286.ch17openalex-snapshot
Properties Guiding Drug‐ and Lead‐Likeness
inferred← citeshttps://doi.org/10.1002/cmdc.200700139openalex-snapshot
Lessons Learnt from Assembling Screening Libraries for Drug Discovery for Neglected Diseases
inferred← citeshttps://doi.org/10.1002/qsar.200610097openalex-snapshot
Similarity Metrics and Descriptor Spaces – Which Combinations to Choose?
inferred← citeshttps://doi.org/10.1007/978-0-387-30440-3_134openalex-snapshot
Drug Design with Artificial Neural Networks
inferred← citeshttps://doi.org/10.1007/978-1-4939-2239-0_9openalex-snapshot
Ligand Biological Activity Predictions Using Fingerprint-Based Artificial Neural Networks (FANN-QSAR)
inferred← citeshttps://doi.org/10.1007/springerreference_60306openalex-snapshot
Drug Design with Artificial Neural Networks
inferred← citeshttps://doi.org/10.1016/j.cbpa.2008.03.010openalex-snapshot
Dissimilarity-based approaches to compound acquisition
inferred← citeshttps://doi.org/10.1016/j.drudis.2011.04.005openalex-snapshot
Rendezvous in chemical space? Comparing the small molecule compound libraries of Bayer and Schering
inferred← citeshttps://doi.org/10.1016/s1003-6326(06)60317-8openalex-snapshot
Predictive model based on artificial neural net for purity of perovskite-type SrTiO3 nanocrystalline
inferred← citeshttps://doi.org/10.1016/s1574-1400(06)02009-3openalex-snapshot
Chapter 9 Molecular Similarity: Advances in Methods, Applications and Validations in Virtual Screening and QSAR
inferred← citeshttps://doi.org/10.1021/ci9000458openalex-snapshot
FOG: Fragment Optimized Growth Algorithm for the de Novo Generation of Molecules Occupying Druglike Chemical Space
inferred← citeshttps://doi.org/10.1021/mp300237zopenalex-snapshot
Molecular Fingerprint-Based Artificial Neural Networks QSAR for Ligand Biological Activity Predictions
inferred← citeshttps://doi.org/10.1109/icif.2007.4408024openalex-snapshot
Feature vs. classifier fusion for predictive data mining a case study in pesticide classification
inferred← citeshttps://doi.org/10.1186/s13321-017-0212-4openalex-snapshot
Comparative analyses of structural features and scaffold diversity for purchasable compound libraries
inferred← citeshttps://doi.org/10.1517/17460441.2010.497534openalex-snapshot
De novodesign: balancing novelty and confined chemical space
inferred← citeshttps://doi.org/10.2174/156802607782194761openalex-snapshot
Complementarity Between Public and Commercial Databases: New Opportunities in Medicinal Chemistry Informatics
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.