InChI and Tautomerism: Toward a Comprehensive Treatment
Dhaked et al.'s comprehensive analysis of tautomerism in chemoinformatics, introducing 86 new tautomeric rules and their …...
Computational Chemistry Data Formats
Personal notes on molecular data formats and practical considerations for representation and storage.
InChI: The Worldwide Chemical Structure Identifier Standard
Heller et al. (2013) explain how IUPAC's InChI became the global standard for representing chemical structures, its …...
Making InChI FAIR and Sustainable for Inorganic Chemistry
The InChI v1.07 release modernizes chemical identifiers for FAIR data principles, fixes thousands of bugs, and proposes …...
Mixfile and MInChI: Machine-Readable Chemical Mixture Formats
Clark et al.'s Mixfile format and MInChI specification provide the first standardized, machine-readable way to represent …...
NInChI: Toward a Chemical Identifier for Nanomaterials
Lynch et al. propose NInChI (Nanomaterials InChI) - a standardized notation system for representing complex …
Recent Advances in the SELFIES Library (2023)
An overview of the major updates to the SELFIES Python library, including improved performance, expanded chemical …...
RInChI: Reaction International Chemical Identifier
RInChI extends the InChI standard to create unique, machine-readable identifiers for chemical reactions, enabling …...
SELFIES: The Original Paper (Krenn et al. 2020)
A summary of the foundational 2020 paper that introduced SELFIES - the 100% robust molecular string representation …
SMILES: The Original Paper (Weininger 1988)
A summary of David Weininger's foundational 1988 paper that introduced SMILES notation - the string-based molecular …
SELFIES (Self-Referencing Embedded Strings)
SELFIES is a 100% robust string-based representation for chemical molecules, designed for machine learning applications …...
SMILES (Simplified Molecular Input Line Entry System)
SMILES is a specification for describing the structure of chemical molecules using short ASCII strings....
Invalid SMILES are Beneficial Rather than Detrimental to Chemical Language Models
Skinnider's 2024 Nature Machine Intelligence paper demonstrates that the ability to generate invalid SMILES is actually …...