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Predicting Key Example Compounds in Competitors' Patent Applications Using Structural Information Alone
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Text mining and its potential applications in systems biology
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Data visualisation tools—a perspective from the pharmaceutical industry
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Analysis and visualisation with host-based software – The features of STN®AnaVist™
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Text mining applied to patent mapping: a practical business case
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Text-mining approaches in molecular biology and biomedicine
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The Generation of a Unique Machine Description for Chemical Structures-A Technique Developed at Chemical Abstracts Service.
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On the Properties of Bit String-Based Measures of Chemical Similarity
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The Hidden Component of Size in Two-Dimensional Fragment Descriptors: Side Effects on Sampling in Bioactive Libraries
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Hit and lead generation: beyond high-throughput screening
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Protecting your inventions: the patent system
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Knowledge Discovery in Biology and Biotechnology Texts: A Review of Techniques, Evaluation Strategies, and Applications
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Mining the Biomedical Literature in the Genomic Era: An Overview
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A survey of current work in biomedical text mining
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Text mining and ontologies in biomedicine: Making sense of raw text
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The next generation of literature analysis: Integration of genomic analysis into text mining
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Machine learning in bioinformatics
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Mining literature for systems biology
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Guest Editors' Introduction: Mining Actionable Knowledge on the Web
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SYMBIOmatics: Synergies in Medical Informatics and Bioinformatics – exploring current scientific literature for emerging topics
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Text-mining and information-retrieval services for molecular biology.
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A Review of Two Text-Mining Packages
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
inferred← citeshttps://doi.org/10.1002/chin.200818215openalex-snapshot
ChemInform Abstract: Predicting Key Example Compounds in Competitors′ Patent Applications Using Structural Information Alone.
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Toward generalizable structure‐based deep learning models for protein–ligand interaction prediction: Challenges and strategies
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Applications of Artificial Intelligence in Drug Design: Opportunities and Challenges
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Artificial intelligence-driven patent analysis in drug discovery
inferred← citeshttps://doi.org/10.1016/j.drudis.2022.04.017openalex-snapshot
From traditional to data-driven medicinal chemistry: A case study
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Most Ligand-Based Classification Benchmarks Reward Memorization Rather than Generalization
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The Effect of Debiasing Protein–Ligand Binding Data on Generalization
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PatentNetML: A Novel Framework for Predicting Key Compounds in Patents Using Network Science and Machine Learning
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A Real-World Perspective on Molecular Design
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Improved Chemical Text Mining of Patents with Infinite Dictionaries and Automatic Spelling Correction
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Exploiting Structural Information in Patent Specifications for Key Compound Prediction
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Biologically Relevant Chemical Space Navigator: From Patent and Structure–Activity Relationship Analysis to Library Acquisition and Design
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Finding Key Members in Compound Libraries by Analyzing Networks of Molecules Assembled by Structural Similarity
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Bruton’s Tyrosine Kinase Inhibitors: Approaches to Potent and Selective Inhibition, Preclinical and Clinical Evaluation for Inflammatory Diseases and B Cell Malignancies
inferred← citeshttps://doi.org/10.1038/s41467-024-50779-yopenalex-snapshot
PatCID: an open-access dataset of chemical structures in patent documents
inferred← citeshttps://doi.org/10.1038/s41598-022-12116-5openalex-snapshot
Chemical property prediction under experimental biases
inferred← citeshttps://doi.org/10.1093/database/baz001openalex-snapshot
Automatic identification of relevant chemical compounds from patents
inferred← citeshttps://doi.org/10.1093/nar/gkr919openalex-snapshot
SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents
inferred← citeshttps://doi.org/10.1093/nar/gkv1253openalex-snapshot
SureChEMBL: a large-scale, chemically annotated patent document database
inferred← citeshttps://doi.org/10.1109/tem.2019.2958518openalex-snapshot
Monitoring Competitors’ Innovation Activities: Analyzing the Competitive Patent Landscape Based on Semantic Anchor Points
inferred← citeshttps://doi.org/10.1186/1758-2946-3-s1-o16openalex-snapshot
Improved chemical text mining of patents using infinite dictionaries, translation and automatic spelling correction
inferred← citeshttps://doi.org/10.1186/s13321-015-0097-zopenalex-snapshot
Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents
inferred← citeshttps://doi.org/10.1186/s13321-019-0401-4openalex-snapshot
IntelliPatent: a web-based intelligent system for fast chemical patent claim drafting
inferred← citeshttps://doi.org/10.1517/13543776.2011.547479openalex-snapshot
Novel γ-secretase modulators: a review of patents from 2008 to 2010
inferred← citeshttps://doi.org/10.1517/13543776.2013.821465openalex-snapshot
Novel γ-secretase modulators for the treatment of Alzheimer's disease: a review focusing on patents from 2010 to 2012
inferred← citeshttps://doi.org/10.17615/1tdd-3k21openalex-snapshot
Methods in literature-based drug discovery
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Revolutionizing Drug Development: Harnessing Artificial Intelligence in Pharmaceutical Sciences
inferred← citeshttps://doi.org/10.26434/chemrxiv-2022-5ck0sopenalex-snapshot
Glolloc: Mixture of Global and Local Experts for Molecular Activity Prediction
inferred← citeshttps://doi.org/10.26434/chemrxiv.9758423openalex-snapshot
The Missing Label Problem: Addressing False Assumptions Improves Ligand-Based Virtual Screening
inferred← citeshttps://doi.org/10.26434/chemrxiv.9758423.v1openalex-snapshot
The Missing Label Problem: Addressing False Assumptions Improves Ligand-Based Virtual Screening
inferred← citeshttps://doi.org/10.34096/ics.i22.763openalex-snapshot
Las patentes como fuente de información para la innovación en entornos competitivos
inferred← citeshttps://doi.org/10.4155/fmc.10.277openalex-snapshot
Computational Medicinal Chemistry in Fragment-Based Drug Discovery: What, How and When
inferred← citeshttps://doi.org/10.4155/fmc.14.60openalex-snapshot
The Essential Roles of Chemistry in High-Throughput Screening Triage
inferred← citeshttps://doi.org/10.4155/ppa.12.60openalex-snapshot
Building structure–activity Insights Through Patent Mining
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