InChI: open-source chemical structure representation algorithm

AI/ML Papers Using InChI

Papers Citing InChI and Using Various AI/ML Applications

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
GC-EI-MS datasets of trimethylsilyl (TMS) and tert-butyl dimethyl silyl (TBDMS) derivatives for development of machine learning-based compound identification approaches
Milka Ljoncheva, Sintija Stevanoska, Tina Kosjek, Sašo Džeroski
(2022) J.Chem. 14(1):62
DOI: https://doi.org/10.1016/j.dib.2023.109138
The LOTUS initiative for open knowledge management in natural products research
Adriano Rutz, Maria Sorokina, Jakub Galgonek, Daniel Mietchen, Egon Willighagen, Arnaud Gaudry, James G Graham, Ralf Stephan, Roderic Page, Jiří Vondrášek, Christoph Steinbeck, Guido F Pauli, Jean-Luc Wolfender, Jonathan Bisson Is a corresponding author , Pierre-Marie Allard
research eLife 11:e70780 (2022).https://doi.org/10.7554/eLife.70780
DOI: https://doi.org/10.7554/eLife.70780
Bayesian multi-model-based 13C15N-metabolic flux analysis quantifies carbon-nitrogen metabolism in mycobacteria
Khushboo Borah, Martin Bey, Ye Xu, Jim Barber, Catia Costa, Jane Newcombe, Khushboo Borah, Martin Bey, Ye Xu, Jim Barber, Catia Costa, Jane Newcombe, Axel Theorell, Melanie J Bailey, Dany JV Beste, Johnjoe McFadden, Katharina Nöh
bioRxiv preprint 2022.
DOI: https://doi.org/10.1101/2022.03.08.483448
Reconstruction of lossless molecular representations
Umit V. Ucak, Islambek Ashyrmamatov, and Juyong Lee
chemRxiv preprint 2022.
DOI: https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/62273eb250b6211bf1ed8132/original/reconstruction-of-lossless-molecular-representations.pdf
Machine Learning guided early drug discovery of small molecules
Nikhil Pillai, Aparajita Dasgupt, Sirimas Sudsakorn, Jennifer Fretlan, Panteleimon D.Mavroudis
Drug Discovery Today,2022.
DOI: https://doi.org/10.1016/j.drudis.2022.03.017
MolGenSurvey: A Systematic Survey in Machine Learning Models for Molecule Design
Yuanqi Du, Tianfan Fu, Jimeng Sun, Shengchao Liu
JOURNAL OF LATEX CLASS FILES, VOL. 14, NO. 8, AUGUST 2015.
DOI: https://scholar.google.com/scholar_url?url=https://arxiv.org/pdf/2203.14500&hl=en&sa=X&d=11912729450092978116&ei=5mRHYo7GL5GJmwH9jKuIDA&scisig=AAGBfm2A2bPRrJ3sTNGpuKj9ix3SdzmTHg&oi=scholaralrt&hist=XkF1yqEAAAAJ:14262565674548175021:AAGBfm0uWO8vxmHzWni4rLbVw6MFcfqxLg&html=&pos=1&folt=cit&fols=