InChIs and Registry Numbers
Leigh, Jeffrey
J Cheminform 13 40 (2021).
DOI: https://doi.org/10.1515/ci.2012.34.6.23

The Status of the IUPAC InChI Chemical Structure Standard
Boucher, R.; Heller, S.; McNaught, A.
Chem Int 39 (3) 47–47 (2017).
DOI: https://doi.org/10.1515/ci-2017-0316

InChI, the IUPAC International Chemical Identifier.
Heller, Stephen R.; McNaught, Alan; Pletnev, Igor; Stein, Stephen; Tchekhovskoi, Dmitrii
J Cheminform 7 23 (2015).
DOI: https://www.doi.org/10.1186/s13321-015-0068-4

Many InChIs and Quite Some Feat
Warr, Wendy A.
J Comput Aid Mol Des 29 (8), 681–694 (2015).
DOI: https://doi.org/10.1007/s10822-015-9854-3

GenSMILES: An enhanced validity conscious representation for inverse design of molecules
Arun Singh Bhadwal, Kamal Kumar, Neeraj Kumar
Knowledge-Based Systems, V 268 (2023) 110429, ISSN 0950-7051
DOI: https://doi.org/10.1016/j.knosys.2023.110429

SELFIES and the future of molecular string representations
Mario Krenn , Qianxiang Ai , Senja Barthel , Nessa Carson , Angelo Frei , Nathan C. Frey , Pascal Friederich , Theophile Gaudin , Alberto Alexander Gayle , Kevin Maik Jablonka , Rafael F. Lameiro , Dominik Lemm , Alston Lo Seyed Mohamad Moosavi , Jos ́e Manuel Napoles-Duarte , AkshatKumar Nigam, Robert Pollice , Kohulan Rajan , Ulrich Schatzschneider , Philippe Schwaller Marta Skreta , Berend Smit , Felix Strieth-Kalthoff , Chong Sun , Gary Tom , Guido Falk von Rudorff , Andrew Wang , Andrew White Adamo Young , Rose Yu , and Alan Aspuru-Guzik
physics.chem-ph 31 Mar 2022.
DOI: https://arxiv.org/pdf/2204.00056.pdf

ABC-Net: a divide-and-conquer based deep learning architecture for SMILES recognition from molecular images
XC Zhang, JC Yi, GP Yang, CK Wu, TJ Hou, DS Cao
Briefings in Bioinformatics 23, (2022) 2, bbac033.
DOI: https://doi.org/10.1093/bib/bbac033

Reaction SPL-extension of a public document markup standard to chemical reactions
G Schadow, Y Borodina, V Delannée, WD Ihlenfeldt…
ChemRxiv. Cambridge: Cambridge Open Engage; 2022
DOI: https://chemrxiv.org/engage/chemrxiv/article-details/61e873330121b948b03266f2

Unraveling compound taxonomies in untargeted metabolomics through artificial intelligence
Henrique dos Santos Silva
Dissertation for Master's Degree in Biochemistry Specialization in Biochemistry, U Lisbon, Portugal
DOI: http://hdl.handle.net/10451/56544

Recent advances in computational modeling of MOFs: From molecular simulations to machine learning
Hakan Demir, Hilal Daglar, Hasan Can Gulbalkan, Gokhan Onder Aksu, Seda Keskin
Coordination Chemistry Reviews v 484, (1 June 2023) 215112
DOI: https://doi.org/10.1016/j.ccr.2023.215112

Combining Machine Learning with Physical Knowledge in Thermodynamic Modeling of Fluid Mixtures
Fabian Jirasek and Hans Hasse
Ann Rev of Chem and Bio Eng, Vol 14 (June 2023)
DOI: https://doi.org/10.1146/annurev-chembioeng-092220-025342

Transformer Performance for Chemical Reactions: Analysis of Different Predictive and Evaluation Scenarios
Fernando Jaume-Santero, Alban Bornet*, Alain Valery, Nona Naderi, David Vicente Alvarez, Dimitrios Proios, Anthony Yazdani, Colin Bournez, Thomas Fessard, and Douglas Teodoro
J. Chem. Inf. Model. 2023, 63, 7, 1914–1924
DOI: https://doi.org/10.1117/12.2667694

Automatic kinetic model generation: a novel modeling approach for liquid-phase processes
Gust Popelier
Dissertation for Master of Science in Chemical Engineering, Ghent U (2022).
DOI:

Biosynthesis and Biological Profiling of Collinolactone and Semisynthetic Derivatives and MetaboIDent, a Novel Tool for Automated Dereplication
JC Schmid
Ph D Dissertation; Mathematics and Natural Sciences. Eberhard Karls University of Tübingen.
DOI: https://tobias-lib.ub.uni-tuebingen.de/xmlui/bitstream/handle/10900/137947/Dissertation_Schmid.pdf?sequence=2&isAllowed=y

Combustion, Chemistry, and Carbon Neutrality
Katharina Kohse-Höinghaus
Chem. Rev. 2023, XXXX, XXX, XXX-XXX
DOI: https://doi.org/10.1021/acs.chemrev.2c00828

Analysing a billion reactions with the RInChI
Jonathan M. Goodman , Gerd Blanke  and Hans Kraut
Pure and Applied Chemistry, vol. , no. , 2022.
DOI: https://doi.org/10.1515/pac-2021-2008

VisMole: a molecular representation based on voxel for molecular property prediction
Qiang Tong, Jiahao Shen, Xiulei Liu

DOI: https://doi.org/10.1117/12.2667694

Physicochemical properties, drug likeness, ADMET, DFT studies, and in vitro antioxidant activity of oxindole derivatives
Imad Ahmad, Haroon Khan, Goncagül Serdaroğlu

DOI: https://doi.org/10.1016/j.compbiolchem.2023.107861

Data Centric Molecular Analysis and Evaluation of Hepatocellular Carcinoma Therapeutics Using Machine Intelligence-Based Tools
Rengul Cetin-Atalay; Deniz Cansen Kahraman; Esra Nalbat; Ahmet Sureyya Rifaioglu; Ahmet Atakan; Ataberk Donmez; Heval Atas; M. Volkan Atalay; Aybar C. Acar; Tunca Doğan
J Gastrointestinal Cancer (2021)
DOI:

Using deep neural networks to explore chemical space
Martin Vogt
Expert Opinion on Drug Disc (2021).
DOI: https://doi.org/10.1080/17460441.2022.2019704