InChI Full List of Publications & Presentations

 
CrystalNets. jl: Identification of Crystal Topologies: Lionel Zoubritzky and François-Xavier Coudert
{ChemRxiv. Cambridge: Cambridge Open Engage; 2022; This content is a preprint and has not been peer-reviewed.}
https://doi.org/10.26434/chemrxiv-2022-bl6mf
    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}
    https://doi.org/10.7554/eLife.70780
      BioHackathon 2015: Semantics of data for life sciences and reproducible research: Naohisa Goto
      {F1000Research, 9, 136.}
      https://doi.org/10.12688/F1000RESEARCH.18236.1
        Nutrient concentrations in food display universal behavior: G Menichetti, AL Barabási
        {Nature Food volume 3, pages 375–382 (2022)}
        https://www.nature.com/articles/s43016-022-00511-0
          Object approach to the organic molecule representation: Yehor S. Malets
          {}

            COMPARISON OF NON-LEARNED AND LEARNED MOLECULE REPRESENTATIONS FOR CATALYST DISCOVERY: Qianqian Yao
            {MS Thesis, N Dakota State U}
            https://library.ndsu.edu/ir/bitstream/handle/10365/32331/Comparison%20of%20Non-Learned%20and%20Learned%20Molecule%20Representations%20for%20Catalyst%20Discovery.pdf?sequence=1
              CAS Common Chemistry in 2021: Expanding Access to Trusted Chemical Information for the Scientific Community: Andrea Jacobs, Dustin Williams, Katherine Hickey, Nathan Patrick, Antony J. Williams, Stuart Chalk, Leah McEwen, Egon Willighagen, Martin Walker, Evan Bolton, Gabriel Sinclair, Adam Sanford
              {J. Chem. Inf. Model. 2022, XXXX, XXX, XXX-XXX}
              https://doi.org/10.1021/acs.jcim.2c00268
                The Next Frontier of Environmental Unknowns: Substances of Unknown or Variable Composition, Complex Reaction Products, or Biological Materials (UVCBs): Adelene Lai, Alex M. Clark, Beate I. Escher, Marc Fernandez, Leah R. McEwen, Zhenyu Tian, Zhanyun Wang, Emma L. Schymanski
                {Environ. Sci. Technol. 2022.}
                https://doi.org/10.1021/acs.est.2c00321
                  MolMiner: You only look once for chemical structure recognition: Y Xu, J Xiao, CH Chou, J Zhang, J Zhu, Q Hu, H Li, Ningsheng Han, Bingyu Liu, Shuaipeng Zhang, Jinyu Han, Zhen Zhang, Shuhao Zhang, Weilin Zhang, Luhua Lai, Jianfeng Pei
                  {arXiv:2205.11016v1}
                  https://doi.org/10.48550/arXiv.2205.11016
                    INPUT: An intelligent network pharmacology platform unique for traditional Chinese medicine: Xianhai Lia, QiangTang, Fanbo Menga, Pufeng Duc, Wei Chen
                    {Comp and Struc Biotech J 20, 1345-1351. 2022.}
                    https://doi.org/10.1016/j.csbj.2022.03.006
                      Reconstruction of lossless molecular representations: Umit V. Ucak, Islambek Ashyrmamatov, and Juyong Lee
                      {chemRxiv preprint 2022.}
                      https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/62273eb250b6211bf1ed8132/original/reconstruction-of-lossless-molecular-representations.pdf
                        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.}
                        https://doi.org/10.1101/2022.03.08.483448
                          A general procedure for rounding m/z values in low-resolution mass spectra: Mikhail Khrisanfov, Andrey Samokhin
                          {Rapid Comm in Mass Spec Volume36, Issue11 2022.}
                          https://doi.org/10.1002/rcm.9294
                            Data Resource for Prediction of Gas-Phase Thermodynamic Properties of Small Molecules: William Bains, Janusz Jurand Petkowski , Zhuchang Zhan and Sara Seager
                            {Molecules.Data 7,33 2022.}
                            https//doi.org/10.3390/data7030033
                              Predicting biochemical and physiological effects of natural products from molecular structures using machine learning: Junhyeok Jeon, Seongmo Kang, Hyun Uk Kim
                              {Natural Product Reports,38, Issue 11, 1954-1966, 2021.}
                              https://doi.org/10.1039/d1np00016k
                                TUCAN: A molecular identier and descriptor applicable to the whole periodic table from hydrogen to oganesson: JC Brammer, G Blanke, C Kellner, A Hoffmann, Sonja Herres-Pawlis, Ulrich Schatzschneider
                                {preprint, 2022.}
                                https://doi.org/10.21203/rs.3.rs-1466562/v1
                                  Molecular Sonification for Molecule to Music Information Transfer.: Babak Mahjour, Jordan Bench, Rui Zhang, Jared Frazier, Tim Cernak
                                  {preprint, 2022.}
                                  https://chemrxiv.org/engage/api-gateway/chemrxiv/assets/orp/resource/item/6236172dd75627dbfb1e0c92/original/molecular-sonification-for-molecule-to-music-information-transfer.pdf
                                    OntoPESScan: An Ontology for the Exploration of Potential Energy Surfaces: Angiras Menon, Laura Pascazio, Daniel Nurkowski, Feroz Farazi, Sebastian Mosbach, Jethro Akroyd, Markus Kraft
                                    {Cambridge Centre for Comp Chem Eng preprint, 2022.}
                                    https://como.ceb.cam.ac.uk/media/preprints/c4e_am2145_preprint_294.pdf
                                      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.}
                                      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=
                                        Machine Learning guided early drug discovery of small molecules: Nikhil Pillai, Aparajita Dasgupt, Sirimas Sudsakorn, Jennifer Fretlan, Panteleimon D.Mavroudis
                                        {Drug Discovery Today,2022.}
                                        https://doi.org/10.1016/j.drudis.2022.03.017