InChI Full List of Publications & Presentations

InChI Full List of Publications & Presentations

 
Acyl-CoA Identification in Mouse Liver Samples Using the In Silico CoA-Blast Tandem Mass Spectral Library: U Keshet, T Kind, X Lu, S Devi, O Fiehn
{Anal. Chem. 2022, 94, 6, 2732–2739}
https://doi.org/10.1021/acs.analchem.1c03272
Yuel: Improving the Generalizability of Structure-Free Compound–Protein Interaction Prediction: J Wang, NV Dokholyan
{Chem. Inf. Model. 2022, 62, 3, 463–471}
https://doi.org/10.1021/acs.jcim.1c01531
Transformative choices towards a sustainable academic publishing system: M Kayal, J Ballard, E Kayal
{ Ideas in Ecology and Evolution 14 (2021).}
https://doi.org/10.24908/iee.2021.14.3.f
Organic materials repurposing, a data set for theoretical predictions of new applications for existing compounds: ÖH Omar, T Nematiaram, A Troisi, D Padula
{Scientific Data volume 9, Article number: 54 (2022) }
https://www.nature.com/articles/s41597-022-01142-7
WikiPathways: Integrating Pathway Knowledge with Clinical Data: DN Slenter, M Kutmon, EL Willighagen
{… Guide to the Diagnosis, Treatment, and …, 2022}
https://link.springer.com/chapter/10.1007/978-3-030-67727-5_73
Computational methods on food contact chemicals: Big data and in silico screening on nuclear receptors family: Pietro Cozzini; Francesca Cavaliere; Giulia Spaggiari; Gianluca Morelli; Marco Riani
{Chemosphere 292 (2022) 133422.}
https://doi.org/10.1016/j.chemosphere.2021.133422
Dynamic Buffer Management in Massively Parallel Systems: A Case on GPUs: Minh Pham; Hao Li; Yongke Yuan; Chengcheng Mou; Kandethody Ramachandran; Zichen Xu; Yicheng Tu
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https://cse.usf.edu/~tuy/pub/tech21-001.pdf
HyFactor: Hydrogen-count labelled graph-based defactorization Autoencoder: Tagir Akhmetshin; Arkadii Lin; Daniyar Mazitov; Evgenii Ziaikin; Timur Madzhidov; Alexandre Varnek
{ChemRxiv preprint and has not been peer-reviewed.}
https://chemrxiv.org/engage/chemrxiv/article-details/61aa38576d4e8f3bdba8aead
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)}

Exploring Toxins for Hunting SARS-CoV-2 Main Protease Inhibitors: Molecular Docking, Molecular Dynamics, Pharmacokinetic Properties, and Reactome Study: MAA Ibrahim, AHM Abdelrahman, LA Jaragh Alhadad…
{Pharmaceuticals (Basel). 2022 Jan 27;15(2):153.}
https://doi.org/10.3390/ph15020153
Data Programs at NBS/NIST: 1901–2021: HG Semerjian, DR Burgess
{Jf Phys Chem Ref Data 51, 011501 (2022)}
https://doi.org/10.1063/5.0084230
A chemical kinetic mechanism for combustion and flame propagation of CH2F2/O2/N2 mixtures: Donald R. Burgess Jr., Valeri I. Babushok, Jeffrey A. Manion
{Int. J. Chem. Kinet. 61 (2021)}
https://doi.org/10.1002/kin.21549
Convolutional neural networks (CNNs): concepts and applications in pharmacogenomics.: Vaz, Joel Markus; Balaji, S.
{Mol Divers 25 1569-1584 (2021).}

Translating the Molecules: Adapting Neural Machine Translation to Predict IUPAC Names from a Chemical Identifier: Handsel, J., Matthews, B., Knight, N.J., Coles, S. J.
{J Cheminform 13, 79 (2021).}
https://www.doi.org/10.1186/s13321-021-00517-z
InChIs and Registry Numbers: Leigh, Jeffrey
{J Cheminform 13 40 (2021).}
https://doi.org/10.1515/ci.2012.34.6.23
Using deep neural networks to explore chemical space: Martin Vogt
{Expert Opinion on Drug Disc (2021).}
https://doi.org/10.1080/17460441.2022.2019704
A computer-aided drug design approach to discover tumour suppressor p53 protein activators for colorectal cancer therapy: Rui P.S. Patrício, Paula A. Videirab, Florbela Pereira
{Bioorganic & Medicinal Chemistry 53, 116530 (2022).}
https://doi.org/10.1016/j.bmc.2021.116530
De Novo Molecular Design with Chemical Language Models: Grisoni, F., Schneider, G.
{Artificial Intelligence in Drug Design (2022).}

A potential role of nitric oxide in postharvest pest control: A review: S.J.Granella, T.R.Bechlin; D.Christa; S.R.M.Coelho
{J Saudi Soc Ag Sci (2021).}
https://doi.org/10.1016/j.jssas.2021.12.002
Generative Chemical Transformer: Neural Machine Learning of Molecular Geometric Structures from Chemical Language via Attention: Hyunseung Kim; Jonggeol Na; Won Bo Lee
{J. Chem. Inf. Model. 2021, 61, 12, 5804–5814.}
https://doi.org/10.1021/acs.jcim.1c01289