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Automatic identification of relevant chemical compounds from patents

https://doi.org/10.1093/database/baz001
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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 for Drugs and Chemical Compounds: Methods, Tools and Applications
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Making every SAR point count: the development of Chemistry Connect for the large-scale integration of structure and bioactivity data
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Text mining techniques for patent analysis
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Patents: A unique source for scientific technical information in chemistry related industry?
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Indexing chemical structures: Exemplified compound indexing in patents by the vendors Thomson Reuters, Chemical Abstracts and Elsevier – A comparative study by the Patent Documentation Group (PDG)
inferredcites →https://doi.org/10.1016/j.wpi.2016.11.004openalex-snapshot
“80% of technical information found only in patents” – Is there proof of this [1] ?
inferredcites →https://doi.org/10.1021/acs.chemrev.6b00851openalex-snapshot
Information Retrieval and Text Mining Technologies for Chemistry
inferredcites →https://doi.org/10.1021/bk-2014-1164.ch008openalex-snapshot
The Making of Reaxys—Towards Unobstructed Access to Relevant Chemistry Information
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/ci3001293openalex-snapshot
Exploiting Structural Information in Patent Specifications for Key Compound Prediction
inferredcites →https://doi.org/10.1021/ci7002686openalex-snapshot
Predicting Key Example Compounds in Competitors' Patent Applications Using Structural Information Alone
inferredcites →https://doi.org/10.1021/ci800449topenalex-snapshot
CLiDE Pro: The Latest Generation of CLiDE, a Tool for Optical Chemical Structure Recognition
inferredcites →https://doi.org/10.1021/ci9001102openalex-snapshot
Finding Key Members in Compound Libraries by Analyzing Networks of Molecules Assembled by Structural Similarity
inferredcites →https://doi.org/10.1039/c0md00148aopenalex-snapshot
Data-mining patent literature for novel chemical reagents for use in medicinal chemistry design
inferredcites →https://doi.org/10.1093/bioinformatics/btg1023openalex-snapshot
GENIA corpus—a semantically annotated corpus for bio-textmining
inferredcites →https://doi.org/10.1093/database/bas049openalex-snapshot
BioCreative-2012 Virtual Issue
inferredcites →https://doi.org/10.1093/database/baw061openalex-snapshot
Chemical entity recognition in patents by combining dictionary-based and statistical approaches
inferredcites →https://doi.org/10.1093/database/baw120openalex-snapshot
The Markyt visualisation, prediction and benchmark platform for chemical and gene entity recognition at BioCreative/CHEMDNER challenge
inferredcites →https://doi.org/10.1093/database/baz001openalex-snapshot
Automatic identification of relevant chemical compounds from patents
inferredcites →https://doi.org/10.1093/nar/gkp886openalex-snapshot
Chemical Entities of Biological Interest: an update
inferredcites →https://doi.org/10.1093/nar/gkr919openalex-snapshot
SCRIPDB: a portal for easy access to syntheses, chemicals and reactions in patents
inferredcites →https://doi.org/10.1093/nar/gkt1031openalex-snapshot
The ChEMBL bioactivity database: an update
inferredcites →https://doi.org/10.1093/nar/gkt1068openalex-snapshot
DrugBank 4.0: shedding new light on drug metabolism
inferredcites →https://doi.org/10.1093/nar/gkv1253openalex-snapshot
SureChEMBL: a large-scale, chemically annotated patent document database
inferredcites →https://doi.org/10.1093/nar/gkv951openalex-snapshot
PubChem Substance and Compound databases
inferredcites →https://doi.org/10.1186/1758-2946-3-14openalex-snapshot
Analysis of in vitrobioactivity data extracted from drug discovery literature and patents: Ranking 1654 human protein targets by assayed compounds and molecular scaffolds
inferredcites →https://doi.org/10.1186/1758-2946-3-40openalex-snapshot
Mining chemical information from open patents
inferredcites →https://doi.org/10.1186/1758-2946-4-35openalex-snapshot
Consistency of systematic chemical identifiers within and between small-molecule databases
inferredcites →https://doi.org/10.1186/1758-2946-6-17openalex-snapshot
Chemical named entities recognition: a review on approaches and applications
inferredcites →https://doi.org/10.1186/1758-2946-6-s1-o12openalex-snapshot
Identification of host interactions for phenotypic antimalarial hits
inferredcites →https://doi.org/10.1186/1758-2946-7-s1-s1openalex-snapshot
CHEMDNER: The drugs and chemical names extraction challenge
inferredcites →https://doi.org/10.1186/1758-2946-7-s1-s10openalex-snapshot
Recognition of chemical entities: combining dictionary-based and grammar-based approaches
inferredcites →https://doi.org/10.1186/1758-2946-7-s1-s2openalex-snapshot
The CHEMDNER corpus of chemicals and drugs and its annotation principles
inferredcites →https://doi.org/10.1186/s13321-015-0097-zopenalex-snapshot
Managing expectations: assessment of chemistry databases generated by automated extraction of chemical structures from patents
inferredcites →https://doi.org/10.1186/s13321-015-0102-6openalex-snapshot
Ambiguity of non-systematic chemical identifiers within and between small-molecule databases
inferredcites →https://doi.org/10.1371/journal.pone.0107477openalex-snapshot
Annotated Chemical Patent Corpus: A Gold Standard for Text Mining
inferredcites →https://doi.org/10.1371/journal.pone.0121635openalex-snapshot
Quantitative Determination of Technological Improvement from Patent Data
inferredcites →https://doi.org/10.17632/6hykykmn65openalex-snapshot
Automatic identification of relevant chemical compounds from patents. The training corpus.
inferredcites →https://doi.org/10.17863/cam.16293openalex-snapshot
Extraction of chemical structures and reactions from the literature
inferredcites →https://doi.org/10.2174/1568026054637692openalex-snapshot
Information Extraction in the Life Sciences: Perspectives for Medicinal Chemistry, Pharmacology and Toxicology
inferredcites →https://doi.org/10.3115/1572392.1572403openalex-snapshot
Annotation of chemical named entities

What points at this work

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

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ChEMU: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents
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Overview of ChEMU 2020: Named Entity Recognition and Event Extraction of Chemical Reactions from Patents
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ChEMU 2021: Reaction Reference Resolution and Anaphora Resolution in Chemical Patents
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Overview of ChEMU 2021: Reaction Reference Resolution and Anaphora Resolution in Chemical Patents
inferred← citeshttps://doi.org/10.1007/978-3-030-99739-7_50openalex-snapshot
The ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents
inferred← citeshttps://doi.org/10.1007/978-3-031-13643-6_30openalex-snapshot
Overview of ChEMU 2022 Evaluation Campaign: Information Extraction in Chemical Patents
inferred← citeshttps://doi.org/10.1016/b978-0-443-29808-0.00017-0openalex-snapshot
Artificial intelligence-driven patent analysis in drug discovery
inferred← citeshttps://doi.org/10.1016/j.compind.2021.103525openalex-snapshot
Using text mining to retrieve information about circular economy
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Current methodologies for chemical compound searching in patents: A case study
inferred← citeshttps://doi.org/10.1016/j.wpi.2022.102134openalex-snapshot
Validity of PubChem compounds supplied by Patentscope or SureChEMBL
inferred← citeshttps://doi.org/10.1021/acs.jcim.1c00151openalex-snapshot
Identification of the Core Chemical Structure in SureChEMBL Patents
inferred← citeshttps://doi.org/10.1021/acs.jcim.3c01449openalex-snapshot
OSPAR: A Corpus for Extraction of Organic Synthesis Procedures with Argument Roles
inferred← citeshttps://doi.org/10.1021/acs.jmedchem.3c01893openalex-snapshot
PatentNetML: A Novel Framework for Predicting Key Compounds in Patents Using Network Science and Machine Learning
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/s41524-025-01538-0openalex-snapshot
Foundation models for materials discovery – current state and future directions
inferred← citeshttps://doi.org/10.1038/s41540-022-00250-9openalex-snapshot
Old drugs, new tricks: leveraging known compounds to disrupt coronavirus-induced cytokine storm
inferred← citeshttps://doi.org/10.1038/s41597-021-00875-1openalex-snapshot
NLM-Chem, a new resource for chemical entity recognition in PubMed full text literature
inferred← citeshttps://doi.org/10.1039/d2dd00019aopenalex-snapshot
Extraction of chemical structures from literature and patent documents using open access chemistry toolkits: a case study with PFAS
inferred← citeshttps://doi.org/10.1063/5.0021106openalex-snapshot
Data-driven materials research enabled by natural language processing and information extraction
inferred← citeshttps://doi.org/10.1093/bib/bbac461openalex-snapshot
Multi-modal chemical information reconstruction from images and texts for exploring the near-drug space
inferred← citeshttps://doi.org/10.1093/nar/gkac956openalex-snapshot
PubChem 2023 update
inferred← citeshttps://doi.org/10.1145/3366030.3366104openalex-snapshot
Named Entity Recognition for Biomedical Patent Text using Bi-LSTM Variants
inferred← citeshttps://doi.org/10.1186/s13321-021-00568-2openalex-snapshot
ChemTables: a dataset for semantic classification on tables in chemical patents
inferred← citeshttps://doi.org/10.1186/s13321-025-01134-wopenalex-snapshot
Summarizing relationships between chemicals, genes, proteins, and diseases in PubChem using analysis of their co-occurrences in patents
inferred← citeshttps://doi.org/10.18653/v1/2021.eacl-main.116openalex-snapshot
ChEMU-Ref: A Corpus for Modeling Anaphora Resolution in the Chemical Domain
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Proceedings of the 13th International Workshop on Health Text Mining and Information Analysis (LOUHI)
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Distinguishing between focus and background entities in biomedical corpora using discourse structure and transformers
inferred← citeshttps://doi.org/10.22363/2658-4670-2023-31-1-64-74openalex-snapshot
Methods of extracting biomedical information from patents and scientific publications (on the example of chemical compounds)
inferred← citeshttps://doi.org/10.3389/frma.2021.654438openalex-snapshot
ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents
inferred← citeshttps://doi.org/10.3389/frma.2021.691105openalex-snapshot
From Tokenization to Self-Supervision: Building a High-Performance Information Extraction System for Chemical Reactions in Patents
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A Comparative Review of Artificial Intelligence Applications in Small Molecule Versus Peptide Drug Discovery
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Statistics of the Popularity of Chemical Compounds in Relation to the Non-Target Analysis
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Congenericity of Claimed Compounds in Patent Applications
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Drug Repurposing Patent Documents Vs Peer Review: Patent Information Comes More Than 600 Days Earlier On Average
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Biological Activity Relationship of Cyclic and Noncyclic Alkanes Using Quantum Molecular Descriptors
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Word Embeddings for Chemical Patent Natural Language Processing
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Deep learning-based automatic action extraction from structured chemical synthesis procedures
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