On the public citation graph

Application of Nearest-Neighbor and Cluster Analyses in Pharmaceutical Lead Discovery

0 signed · 54 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 See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.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/10.1016/1074-5521(95)90283-xopenalex-snapshot
Predicting ligand binding to proteins by affinity fingerprinting
inferredcites →https://doi.org/10.1021/ci00007a012openalex-snapshot
Description of several chemical structure file formats used by computer programs developed at Molecular Design Limited
inferredcites →https://doi.org/10.1021/ci00007a013openalex-snapshot
Computer-aided molecular formula determination from mass, proton and carbon-13 NMR spectra
inferredcites →https://doi.org/10.1021/ci960463hopenalex-snapshot
Rapid Quantification of Molecular Diversity for Selective Database Acquisition

What points at this work

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

inferred← citeshttps://doi.org/10.1002/0471433519.ch1openalex-snapshot
Clustering Methods and Their Uses in Computational Chemistry
inferred← citeshttps://doi.org/10.1002/9783527613106.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/9783527619368.ch18openalex-snapshot
Lead Identification by Virtual Screening
inferred← citeshttps://doi.org/10.1002/9783527628766.biblioopenalex-snapshot
Bibliography
inferred← citeshttps://doi.org/10.1002/9783527665143.ch01openalex-snapshot
Identifying and Representing Scaffolds
inferred← citeshttps://doi.org/10.1002/cem.872openalex-snapshot
Active learning support vector machines for optimal sample selection in classification
inferred← citeshttps://doi.org/10.1002/chin.199918239openalex-snapshot
ChemInform Abstract: Application of Nearest-Neighbor and Cluster Analyses in Pharmaceutical Lead Discovery.
inferred← citeshttps://doi.org/10.1002/prot.10270openalex-snapshot
Virtual screening to enrich hit lists from high‐throughput screening: A case study on small‐molecule inhibitors of angiogenin
inferred← citeshttps://doi.org/10.1007/978-1-4419-8989-5_1openalex-snapshot
Elements of High-Throughput Analysis in Combinatorial Materials Science
inferred← citeshttps://doi.org/10.1007/978-3-319-10226-9_1openalex-snapshot
Introduction to Molecular Similarity and Chemical Space
inferred← citeshttps://doi.org/10.1007/978-981-10-7811-8_12openalex-snapshot
Statistical Machine Learning for Agriculture and Human Health Care Based on Biomedical Big Data
inferred← citeshttps://doi.org/10.1007/s10822-026-00850-1openalex-snapshot
The (r)evolution of chemical space and molecular modeling: a time-resolved perspective
inferred← citeshttps://doi.org/10.1016/b0-08-043152-6/00250-3openalex-snapshot
Combinatorial Screening
inferred← citeshttps://doi.org/10.1016/j.chembiol.2004.08.026openalex-snapshot
A Flexible Data Analysis Tool for Chemical Genetic Screens
inferred← citeshttps://doi.org/10.1016/j.sab.2020.105963openalex-snapshot
Classification of printing inks in pharmaceutucal packages by Laser-Induced Breakdown Spectroscopy and Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy
inferred← citeshttps://doi.org/10.1016/j.xphs.2020.11.034openalex-snapshot
Prediction Machines: Applied Machine Learning for Therapeutic Protein Design and Development
inferred← citeshttps://doi.org/10.1016/s0165-9936(03)00608-3openalex-snapshot
Analytical spectroscopic tools for high-throughput screening of combinatorial materials libraries
inferred← citeshttps://doi.org/10.1016/s0958-1669(99)00061-0openalex-snapshot
Extraction of pharmacophore information from high-throughput screens
inferred← citeshttps://doi.org/10.1016/s1093-3263(00)00059-0openalex-snapshot
Applications of random sampling to virtual screening of combinatorial libraries
inferred← citeshttps://doi.org/10.1016/s1359-6446(00)01616-0openalex-snapshot
Library design for NMR-based screening
inferred← citeshttps://doi.org/10.1016/s1367-5931(00)00091-0openalex-snapshot
Functional diversity of compound libraries
inferred← citeshttps://doi.org/10.1016/s1367-5931(00)00219-2openalex-snapshot
Visual and computational analysis of structure–activity relationships in high-throughput screening data
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.6c00672openalex-snapshot
TRPV4: A Promising Therapeutic Target Ion Channel─Discovery of Ultrapotent Selective Antagonists
inferred← citeshttps://doi.org/10.1021/acschembio.6b00029openalex-snapshot
Analysis of Iterative Screening with Stepwise Compound Selection Based on Novartis In-house HTS Data
inferred← citeshttps://doi.org/10.1021/acsmedchemlett.0c00563openalex-snapshot
Fragment-Based Discovery of Novel Allosteric MEK1 Binders
inferred← citeshttps://doi.org/10.1021/ci034129eopenalex-snapshot
Using Ensembles to Classify Compounds for Drug Discovery
inferred← citeshttps://doi.org/10.1021/ci050087dopenalex-snapshot
Identifying Biologically Active Compound Classes Using Phenotypic Screening Data and Sampling Statistics
inferred← citeshttps://doi.org/10.1021/ci200043zopenalex-snapshot
G-Protein Coupled Receptors Virtual Screening Using Genetic Algorithm Focused Chemical Space
inferred← citeshttps://doi.org/10.1021/ci990435+openalex-snapshot
CerBeruS: A System Supporting the Sequential Screening Process
inferred← citeshttps://doi.org/10.1021/co200007wopenalex-snapshot
Combinatorial and High-Throughput Screening of Materials Libraries: Review of State of the Art
inferred← citeshttps://doi.org/10.1023/b:modi.0000006537.06541.8aopenalex-snapshot
A reagent-based strategy for the design of large combinatorial libraries: A preliminary experimental validation
inferred← citeshttps://doi.org/10.1038/nrg1317openalex-snapshot
Chemogenomics: an emerging strategy for rapid target and drug discovery
inferred← citeshttps://doi.org/10.1039/d4ra02159bopenalex-snapshot
A data-driven QSPR model for screening organic corrosion inhibitors for carbon steel using machine learning techniques
inferred← citeshttps://doi.org/10.1093/bib/bbw105openalex-snapshot
Data-driven approaches used for compound library design, hit triage and bioactivity modeling in high-throughput screening
inferred← citeshttps://doi.org/10.1177/1087057106297826openalex-snapshot
A Simple Strategy for Mitigating the Effect of Data Variability on the Identification of Active Chemotypes from High-Throughput Screening Data
inferred← citeshttps://doi.org/10.1186/s13321-014-0044-4openalex-snapshot
InCHlib – interactive cluster heatmap for web applications
inferred← citeshttps://doi.org/10.1201/9780203913390.ch25openalex-snapshot
Data Mining Applications in Drug Discovery
inferred← citeshttps://doi.org/10.1371/journal.pone.0168806openalex-snapshot
A 2D-QSAR and Grid-Independent Molecular Descriptor (GRIND) Analysis of Quinoline-Type Inhibitors of Akt2: Exploration of the Binding Mode in the Pleckstrin Homology (PH) Domain
inferred← citeshttps://doi.org/10.2174/138620711797537148openalex-snapshot
Integration of Virtual and High Throughput Screening in Lead Discovery Settings
inferred← citeshttps://doi.org/10.2174/1568026023394227openalex-snapshot
New Paradigms in Drug Design and Discovery
inferred← citeshttps://doi.org/10.2477/jccj.2.119openalex-snapshot
Chemical Data Mining Based on Structural Similarity
inferred← citeshttps://doi.org/10.2477/jccj.2012-0002openalex-snapshot
Compression of Topological Fragment Spectra (TFS) for Accelerating Chemical Data Mining
inferred← citeshttps://doi.org/10.30750/ijpbr.1.2.11openalex-snapshot
In-Silico Drug Design: A revolutionary approach to change the concept of current Drug Discovery Process
inferred← citeshttps://doi.org/10.33915/etd.7549openalex-snapshot
Validation of Fast Spectrochemical Screening Methods for the Identification of Counterfeit Pharmaceutical Packaging
inferred← citeshttps://doi.org/10.7287/peerj.6283v0.1/reviews/1openalex-snapshot
Peer Review #1 of "GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.6283v0.1/reviews/2openalex-snapshot
Peer Review #2 of "GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.6283v0.1/reviews/3openalex-snapshot
Peer Review #3 of "GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors (v0.1)"
inferred← citeshttps://doi.org/10.7287/peerj.6283v0.2/reviews/1openalex-snapshot
Peer Review #1 of "GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors (v0.2)"
inferred← citeshttps://doi.org/10.7287/peerj.6283v0.2/reviews/2openalex-snapshot
Peer Review #2 of "GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors (v0.2)"
inferred← citeshttps://doi.org/10.7717/peerj.6283openalex-snapshot
GRID-independent molecular descriptor analysis and molecular docking studies to mimic the binding hypothesis of γ-aminobutyric acid transporter 1 (GAT1) inhibitors
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.