@article{B_nsch_2024,

title = {An automated calculation pipeline for differential pair interaction energies with molecular force fields using the Tinker Molecular Modeling Package},

author = {Felix Bänsch and Mirco Daniel and Harald Lanig and Christoph Steinbeck and Achim Zielesny},

url = {http://dx.doi.org/10.1186/s13321-024-00890-5},

doi = {10.1186/s13321-024-00890-5},

issn = {1758-2946},

year  = {2024},

date = {2024-08-01},

journal = {Journal of Cheminformatics},

volume = {16},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zulfiqar_2024,

title = {Implementation of FAIR Practices in Computational Metabolomics Workflows—A Case Study},

author = {Mahnoor Zulfiqar and Michael R. Crusoe and Birgitta König-Ries and Christoph Steinbeck and Kristian Peters and Luiz Gadelha},

url = {http://dx.doi.org/10.3390/metabo14020118},

doi = {10.3390/metabo14020118},

issn = {2218-1989},

year  = {2024},

date = {2024-02-01},

journal = {Metabolites},

volume = {14},

number = {2},

pages = {118},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zulfiqar_2024b,

title = {Review on computer-assisted biosynthetic capacities elucidation to assess metabolic interactions and communication within microbial communities},

author = {Mahnoor Zulfiqar and Vinay Singh and Christoph Steinbeck and Maria Sorokina},

url = {http://dx.doi.org/10.1080/1040841X.2024.2306465},

doi = {10.1080/1040841x.2024.2306465},

issn = {1549-7828},

year  = {2024},

date = {2024-01-01},

journal = {Critical Reviews in Microbiology},

pages = {1–40},

publisher = {Informa UK Limited},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:38970120,

title = {Advancements in hand-drawn chemical structure recognition through an enhanced DECIMER architecture.},

author = {Rajan K and Brinkhaus HO and Zielesny A and Steinbeck C},

doi = {10.1186/s13321-024-00872-7},

year  = {2024},

date = {2024-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Kuhn_2023,

title = {Twenty years of nmrshiftdb2: A case study of an open database for analytical chemistry},

author = {Stefan Kuhn and Heinz Kolshorn and Christoph Steinbeck and Nils Schlörer},

url = {http://dx.doi.org/10.1002/mrc.5418},

doi = {10.1002/mrc.5418},

issn = {1097-458X},

year  = {2023},

date = {2023-12-01},

journal = {Magnetic Resonance in Chemistry},

publisher = {Wiley},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Zulfiqar_2023,

title = {Analysis of Metabolomics and Transcriptomics Data to Assess Interactions in Microalgal Co-culture ofSkeletonema marinoiandPrymnesium parvum},

author = {Mahnoor Zulfiqar and Anne-Susann Abel and Emanuel Barth and Kristy Syhapanha and Remington Xavier Poulin and Sassrika Nethmini Costa Warnakulasu Dehiwalage and Georg Pohnert and Christoph Steinbeck and Kristian Peters and Maria Sorokina},

url = {http://dx.doi.org/10.1101/2023.12.23.573174},

doi = {10.1101/2023.12.23.573174},

year  = {2023},

date = {2023-12-01},

publisher = {Cold Spring Harbor Laboratory},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PPR:PPR722493,

title = {Untargeted Metabolomics to Expand the Chemical Space of the Marine Diatom\textit{Skeletonema marinoi}},

author = {Zulfiqar M and Stettin D and Schmidt S and Nikitashina V and Pohnert G and Steinbeck C and Peters K and Sorokina M},

doi = {10.1101/2023.09.07.556696},

year  = {2023},

date = {2023-12-01},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Koepler_Steinbeck_Bach_Herres-Pawlis_Jung_Liermann_Neumann_Razum_2023,

title = {Digitalizing the Chemical Landscape: : A Comprehensive Overview and Progress Report of NFDI4Chem},

author = {Oliver Koepler and Christoph Steinbeck and Felix Bach and Sonja Herres-Pawlis and Nicole Jung and Johannes Liermann and Steffen Neumann and Matthias Razum},

url = {https://www.tib-op.org/ojs/index.php/CoRDI/article/view/213},

year  = {2023},

date = {2023-09-01},

journal = {Proceedings of the Conference on Research Data Infrastructure},

volume = {1},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rajan_2023,

title = {DECIMER.ai: an open platform for automated optical chemical structure identification, segmentation and recognition in scientific publications},

author = {Kohulan Rajan and Henning Otto Brinkhaus and M. Isabel Agea and Achim Zielesny and Christoph Steinbeck},

url = {https://doi.org/10.1038%2Fs41467-023-40782-0},

doi = {10.1038/s41467-023-40782-0},

year  = {2023},

date = {2023-08-01},

journal = {Nature Communications},

volume = {14},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Wenk_2023,

title = {Sherlock—A Free and Open-Source System for the Computer-Assisted Structure Elucidation of Organic Compounds from NMR Data},

author = {Michael Wenk and Jean-Marc Nuzillard and Christoph Steinbeck},

url = {https://doi.org/10.3390%2Fmolecules28031448},

doi = {10.3390/molecules28031448},

year  = {2023},

date = {2023-02-01},

journal = {Molecules},

volume = {28},

number = {3},

pages = {1448},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:36871033,

title = {MAW: the reproducible Metabolome Annotation Workflow for untargeted tandem mass spectrometry.},

author = {Zulfiqar M and Gadelha L and Steinbeck C and Sorokina M and Peters K},

doi = {10.1186/s13321-023-00695-y},

year  = {2023},

date = {2023-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:36803857,

title = {Notes on molecular fragmentation and parameter settings for a dissipative particle dynamics study of a C_{10}E_{4}/water mixture with lamellar bilayer formation.},

author = {Bänsch F and Steinbeck C and Zielesny A},

doi = {10.1186/s13321-023-00697-w},

year  = {2023},

date = {2023-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:36805192,

title = {Open data and algorithms for open science in AI-driven molecular informatics.},

author = {Brinkhaus HO and Rajan K and Schaub J and Zielesny A and Steinbeck C},

doi = {10.1016/j.sbi.2023.102542},

year  = {2023},

date = {2023-01-01},

journal = {Current opinion in structural biology},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{B_nsch_2023,

title = {MORTAR: a rich client application for in silico molecule fragmentation},

author = {Felix Bänsch and Jonas Schaub and Betül Sevindik and Samuel Behr and Julian Zander and Christoph Steinbeck and Achim Zielesny},

url = {https://doi.org/10.1186%2Fs13321-022-00674-9},

doi = {10.1186/s13321-022-00674-9},

year  = {2023},

date = {2023-01-01},

journal = {Journal of Cheminformatics},

volume = {15},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:37845745,

title = {Cheminformatics Microservice: unifying access to open cheminformatics toolkits.},

author = {Chandrasekhar V and Sharma N and Schaub J and Steinbeck C and Rajan K},

doi = {10.1186/s13321-023-00762-4},

year  = {2023},

date = {2023-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:38116530,

title = {Untargeted metabolomics to expand the chemical space of the marine diatom \textit{Skeletonema marinoi}.},

author = {Zulfiqar M and Stettin D and Schmidt S and Nikitashina V and Pohnert G and Steinbeck C and Peters K and Sorokina M},

doi = {10.3389/fmicb.2023.1295994},

year  = {2023},

date = {2023-01-01},

journal = {Frontiers in microbiology},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Lai_2022,

title = {An algorithm to classify homologous series within compound datasets},

author = {Adelene Lai and Jonas Schaub and Christoph Steinbeck and Emma L. Schymanski},

url = {https://doi.org/10.1186%2Fs13321-022-00663-y},

doi = {10.1186/s13321-022-00663-y},

year  = {2022},

date = {2022-12-01},

journal = {Journal of Cheminformatics},

volume = {14},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Herres_Pawlis_2022,

title = {Minimum Information Standards in Chemistry: A Call for Better Research Data Management Practices},

author = {Sonja Herres-Pawlis and Felix Bach and Ian J. Bruno and Stuart J. Chalk and Nicole Jung and Johannes C. Liermann and Leah R. McEwen and Steffen Neumann and Christoph Steinbeck and Matthias Razum and Oliver Koepler},

url = {https://doi.org/10.1002%2Fanie.202203038},

doi = {10.1002/anie.202203038},

year  = {2022},

date = {2022-11-01},

journal = {Angewandte Chemie International Edition},

volume = {61},

number = {51},

publisher = {Wiley},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rajan2022,

title = {Performance of chemical structure string representations for chemical image recognition using transformers},

author = {Kohulan Rajan and Christoph Steinbeck and Achim Zielesny},

url = {http://dx.doi.org/10.1039/D1DD00013F},

doi = {10.1039/D1DD00013F},

year  = {2022},

date = {2022-01-01},

urldate = {2022-01-01},

journal = {Digital Discovery},

pages = {-},

publisher = {RSC},

abstract = {The use of molecular string representations for deep learning in chemistry has been steadily increasing in recent years. The complexity of existing string representations, and the difficulty in creating meaningful tokens from them, lead to the development of new string representations for chemical structures. In this study, the translation of chemical structure depictions in the form of bitmap images to corresponding molecular string representations was examined. An analysis of the recently developed DeepSMILES and SELFIES representations in comparison with the most commonly used SMILES representation is presented where the ability to translate image features into string representations with transformer models was specifically tested. The SMILES representation exhibits the best overall performance whereas SELFIES guarantee valid chemical structures. DeepSMILES perform in between SMILES and SELFIES, InChIs are not appropriate for the learning task. All investigations were performed using publicly available datasets and the code used to train and evaluate the models has been made available to the public.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_111931255,

title = {Surge: a fast open-source chemical graph generator},

author = {Christoph Steinbeck and Brendan D. McKay and Mehmet Aziz Yirik and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-022-00604-9},

doi = {10.1186/s13321-022-00604-9},

year  = {2022},

date = {2022-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:35681226,

title = {DECIMER-hand-drawn molecule images dataset.},

author = {Brinkhaus HO and Zielesny A and Steinbeck C and Rajan K},

doi = {10.1186/s13321-022-00620-9},

year  = {2022},

date = {2022-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:35668480,

title = {RanDepict: Random chemical structure depiction generator.},

author = {Brinkhaus HO and Rajan K and Zielesny A and Steinbeck C},

doi = {10.1186/s13321-022-00609-4},

year  = {2022},

date = {2022-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_114466081,

title = {Notes on the Treatment of Charged Particles for Studying Cyclotide/Membrane Interactions with Dissipative Particle Dynamics},

author = {Christoph Steinbeck and Felix Bänsch and Christoph Steinbeck and Achim Zielesny},

url = {http://doi.org/10.3390/membranes12060619},

doi = {10.3390/membranes12060619},

year  = {2022},

date = {2022-01-01},

journal = {Membranes},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:35616633,

title = {The LOTUS initiative for open knowledge management in natural products research.},

author = {Rutz A and Sorokina M and Galgonek J and Mietchen D and Willighagen E and Gaudry A and Graham JG and Stephan R and Page R and Vondrášek J and Steinbeck C and Pauli GF and Wolfender JL and Allard PM},

doi = {10.7554/elife.70780},

year  = {2022},

date = {2022-01-01},

journal = {eLife},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:35242913,

title = {Draft genome assembly and sequencing dataset of the marine diatom \textit{Skeletonema} cf. \textit{costatum} RCC75.},

author = {Sorokina M and Barth E and Zulfiqar M and Kwantes M and Pohnert G and Steinbeck C},

doi = {10.1016/j.dib.2022.107931},

year  = {2022},

date = {2022-01-01},

journal = {Data in brief},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMCID:PMC9746203,

title = {An algorithm to classify homologous series within compound datasets},

author = {Lai A and Schaub J and Steinbeck C and Schymanski E},

year  = {2022},

date = {2022-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{pmid34404468,

title = {DECIMER 1.0: deep learning for chemical image recognition using transformers},

author = {Kohulan Rajan and Achim Zielesny and Christoph Steinbeck},

doi = {10.1186/s13321-021-00538-8},

issn = {1758-2946},

year  = {2021},

date = {2021-08-17},

journal = {J Cheminform},

volume = {13},

number = {1},

pages = {61},

abstract = {The amount of data available on chemical structures and their properties has increased steadily over the past decades. In particular, articles published before the mid-1990 are available only in printed or scanned form. The extraction and storage of data from those articles in a publicly accessible database are desirable, but doing this manually is a slow and error-prone process. In order to extract chemical structure depictions and convert them into a computer-readable format, Optical Chemical Structure Recognition (OCSR) tools were developed where the best performing OCSR tools are mostly rule-based. The DECIMER (Deep lEarning for Chemical ImagE Recognition) project was launched to address the OCSR problem with the latest computational intelligence methods to provide an automated open-source software solution. Various current deep learning approaches were explored to seek a best-fitting solution to the problem. In a preliminary communication, we outlined the prospect of being able to predict SMILES encodings of chemical structure depictions with about 90% accuracy using a dataset of 50-100 million molecules. In this article, the new DECIMER model is presented, a transformer-based network, which can predict SMILES with above 96% accuracy from depictions of chemical structures without stereochemical information and above 89% accuracy for depictions with stereochemical information.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Yirik_2021,

title = {MAYGEN - an Open-Source Chemical Structure Generator for Constitutional Isomers Based on the Orderly Generation Principle},

author = {Mehmet Aziz Yirik and Maria Sorokina and Christoph Steinbeck},

url = {https://doi.org/10.26434%2Fchemrxiv.14497959},

doi = {10.26434/chemrxiv.14497959},

year  = {2021},

date = {2021-04-01},

publisher = {American Chemical Society (ACS)},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Schaub_2021,

title = {Description and Analysis of Glycosidic Residues in the Largest Open Natural Products Database},

author = {Jonas Schaub and Achim Zielesny and Christoph Steinbeck and Maria Sorokina},

url = {https://doi.org/10.3390%2Fbiom11040486},

doi = {10.3390/biom11040486},

year  = {2021},

date = {2021-03-01},

journal = {Biomolecules},

volume = {11},

number = {4},

pages = {486},

publisher = {MDPI AG},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_86548226,

title = {COCONUT online: Collection of Open Natural Products database},

author = {Christoph Steinbeck and Maria Sorokina and Peter Merseburger and Kohulan Rajan and Mehmet Aziz Yirik and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-020-00478-9},

doi = {10.1186/s13321-020-00478-9},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_90179013,

title = {DECIMER-Segmentation: Automated extraction of chemical structure depictions from scientific literature},

author = {Christoph Steinbeck and Kohulan Rajan and Henning Otto Brinkhaus and Maria Sorokina and Achim Zielesny and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-021-00496-1},

doi = {10.1186/s13321-021-00496-1},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_92883418,

title = {STOUT: SMILES to IUPAC names using neural machine translation},

author = {Christoph Steinbeck and Kohulan Rajan and Achim Zielesny and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-021-00512-4},

doi = {10.1186/s13321-021-00512-4},

year  = {2021},

date = {2021-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:33526050,

title = {Molecule Set Comparator (MSC): a CDK-based open rich-client tool for molecule set similarity evaluations.},

author = {Rajan K and Hein JM and Steinbeck C and Zielesny A},

doi = {10.1186/s13321-021-00485-4},

year  = {2021},

date = {2021-01-01},

journal = {Journal of cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_86287117,

title = {Chemical graph generators},

author = {Christoph Steinbeck and Mehmet Aziz Yirik and Daniel Mietchen and Christoph Steinbeck},

url = {http://doi.org/10.1371/journal.pcbi.1008504},

doi = {10.1371/journal.pcbi.1008504},

year  = {2021},

date = {2021-01-01},

journal = {PLOS Computational Biology},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Rajan_2020b,

title = {DECIMER: towards deep learning for chemical image recognition},

author = {Kohulan Rajan and Achim Zielesny and Christoph Steinbeck},

url = {https://doi.org/10.1186%2Fs13321-020-00469-w},

doi = {10.1186/s13321-020-00469-w},

year  = {2020},

date = {2020-10-01},

journal = {Journal of Cheminformatics},

volume = {12},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Steinbeck:bi,

title = {NFDI4Chem - Towards a National Research Data Infrastructure for Chemistry in Germany},

author = {Christoph Steinbeck and Oliver Koepler and Felix Bach and Sonja Herres-Pawlis and Nicole Jung and Johannes Liermann and Steffen Neumann and Matthias Razum and Carsten Baldauf and Frank Biedermann and Thomas Bocklitz and Franziska Boehm and Frank Broda and Paul Czodrowski and Thomas Engel and Martin Hicks and Stefan Kast and Carsten Kettner and Wolfram Koch and Giacomo Lanza and Andreas Link and Ricardo Mata and Wolfgang Nagel and Andrea Porzel and Nils Schlörer and Tobias Schulze and Hans-Georg Weinig and Wolfgang Wenzel and Ludger Wessjohann and Stefan Wulle},

url = {https://riojournal.com/article/55852/},

doi = {10.3897/rio.6.e55852},

year  = {2020},

date = {2020-06-26},

journal = {Research Ideas and Outcomes},

volume = {6},

pages = {e55852},

publisher = {Pensoft Publishers},

abstract = {The vision of NFDI4Chem is the digitalisation of all key steps in chemical research to support scientists in their efforts to collect, store, process, analyse, disclose and re-use research data. Measures to promote Open Science and Research Data Management (RDM) in agreement with the FAIR data principles are fundamental aims of NFDI4Chem to serve the chemistry community with a holistic concept for access to research data. To this end, the overarching objective is the development and maintenance of a national research data infrastructure for the research domain of chemistry in Germany, and to enable innovative and easy to use services and novel scientific approaches based on re-use of research data. NFDI4Chem intends to represent all disciplines of chemistry in academia. We aim to collaborate closely with thematically related consortia. In the initial phase, NFDI4Chem focuses on data related to molecules and reactions including data for their experimental and theoretical characterisation.This overarching goal is achieved by working towards a number of key objectives:Key Objective 1: Establish a virtual environment of federated repositories for storing, disclosing, searching and re-using research data across distributed data sources. Connect existing data repositories and, based on a requirements analysis, establish domain-specific research data repositories for the national research community, and link them to international repositories.Key Objective 2: Initiate international community processes to establish minimum information (MI) standards for data and machine-readable metadata as well as open data standards in key areas of chemistry. Identify and recommend open data standards in key areas of chemistry, in order to support the FAIR principles for research data. Finally, develop standards, if there is a lack.Key Objective 3: Foster cultural and digital change towards Smart Laboratory Environments by promoting the use of digital tools in all stages of research and promote subsequent Research Data Management (RDM) at all levels of academia, beginning in undergraduate studies curricula.Key Objective 4: Engage with the chemistry community in Germany through a wide range of measures to create awareness for and foster the adoption of FAIR data management. Initiate processes to integrate RDM and data science into curricula. Offer a wide range of training opportunities for researchers.Key Objective 5: Explore synergies with other consortia and promote cross-cutting development within the NFDI.Key Objective 6: Provide a legally reliable framework of policies and guidelines for FAIR and open RDM.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sorokina_2020,

title = {Review on natural products databases: where to find data in 2020},

author = {Maria Sorokina and Christoph Steinbeck},

url = {https://doi.org/10.1186%2Fs13321-020-00424-9},

doi = {10.1186/s13321-020-00424-9},

year  = {2020},

date = {2020-04-01},

journal = {Journal of Cheminformatics},

volume = {12},

number = {1},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Steinbeck_2020,

title = {Meet the Editors-in-Chief},

author = {Christoph Steinbeck and Paul Trevorrow},

url = {https://doi.org/10.1002%2Fansa.20190010},

doi = {10.1002/ansa.20190010},

year  = {2020},

date = {2020-03-01},

journal = {Analytical Science Advances},

publisher = {Wiley},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Sorokina:2020cl,

title = {Review on natural products databases: where to find data in 2020},

author = {Maria Sorokina and Christoph Steinbeck},

url = {https://jcheminf.biomedcentral.com/articles/10.1186/s13321-020-00424-9},

doi = {10.1186/s13321-020-00424-9},

year  = {2020},

date = {2020-01-01},

journal = {Journal of cheminformatics},

volume = {12},

number = {1},

pages = {1--51},

publisher = {BioMed Central},

abstract = {Natural products (NPs) have been the centre of attention of the scientific community in the last decencies and the interest around them continues to grow incessantly. As a consequence, in the last 20 years, there was a rapid multiplication of various databases and collections as generalistic or thematic resources for NP information. In this review, we establish a complete overview of these resources, and the numbers are overwhelming: over 120 different NP databases and collections were published and re-used since 2000. 98 of them are still somehow accessible and only 50 are open access. The latter include not only databases but also big collections of NPs published as supplementary material in scientific publications and collections that were backed up in the ZINC database for commercially-available compounds. Some databases, even published relatively recently are already not accessible anymore, which leads to a dramatic loss of data on NPs. The data sources are presented in this manuscript, together with the comparison of the content of open ones. With this review, we also compiled the open-access natural compounds in one single dataset a COlleCtion of Open NatUral producTs (COCONUT), which is available on Zenodo and contains structures and sparse annotations for over 400,000 non-redundant NPs, which makes it the biggest open collection of NPs available to this date.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:32193935,

title = {Gene Cluster Activation in a Bacterial Symbiont Leads to Halogenated Angucyclic Maduralactomycins and Spirocyclic Actinospirols.},

author = {Guo H and Schwitalla JW and Benndorf R and Baunach M and Steinbeck C and Görls H and Beer de ZW and Regestein L and Beemelmanns C},

doi = {10.1021/acs.orglett.0c00601},

year  = {2020},

date = {2020-01-01},

journal = {Organic letters},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_81571333b,

title = {A review of optical chemical structure recognition tools},

author = {Christoph Steinbeck and Kohulan Rajan and Henning Otto Brinkhaus and Achim Zielesny and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-020-00465-0},

doi = {10.1186/s13321-020-00465-0},

year  = {2020},

date = {2020-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_81571333c,

title = {A review of optical chemical structure recognition tools},

author = {Christoph Steinbeck and Kohulan Rajan and Henning Otto Brinkhaus and Achim Zielesny and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-020-00465-0},

doi = {10.1186/s13321-020-00465-0},

year  = {2020},

date = {2020-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck_81571333b,

title = {A review of optical chemical structure recognition tools},

author = {Christoph Steinbeck and Kohulan Rajan and Henning Otto Brinkhaus and Achim Zielesny and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-020-00465-0},

doi = {10.1186/s13321-020-00465-0},

year  = {2020},

date = {2020-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{PMID:33271569,

title = {Metabolomics - the stethoscope for the 21st century.},

author = {Ashrafian H and Sounderajah V and Glen R and Ebbels T and Blaise BJ and Kalra D and Kultima K and Spjuth O and Tenori L and Salek R and Kale N and Haug K and Schober D and Rocca-Serra P and Cascante M},

doi = {10.1159/000513545},

year  = {2020},

date = {2020-01-01},

journal = {Medical principles and practice : international journal of the Kuwait University, Health Science Centre},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Helfrich_2019,

title = {Automated structure prediction of trans-acyltransferase polyketide synthase products},

author = {Eric J N Helfrich and Reiko Ueoka and Alon Dolev and Michael Rust and Roy A Meoded and Agneya Bhushan and Gianmaria Califano and Rodrigo Costa and Muriel Gugger and Christoph Steinbeck and Pablo Moreno and Jörn Piel},

url = {https://doi.org/10.1038%2Fs41589-019-0313-7},

doi = {10.1038/s41589-019-0313-7},

year  = {2019},

date = {2019-07-01},

journal = {Nature Chemical Biology},

publisher = {Springer Science and Business Media LLC},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{publ2001984494,

title = {Interoperable and scalable data analysis with microservices: Applications in Metabolomics.},

author = {P Emami Khoonsari and P Moreno and S Bergmann and J Burman and M Capuccini and M Carone and M Cascante and P de Atauri and C Foguet and A Gonzalez-Beltran and T Hankemeier and K Haug and S He and S Herman and D Johnson and A Larsson and N Kale and K Peters and S Neumann and P Rocca-Serra and L Pireddu and R Rueedi and P Roger and N Sadawi and C Ruttkies and SA Sansone and RM Salek and V Selivanov and D Schober and EA Thévenot and M van Vliet and G Zanetti and C Steinbeck and K Kultima and O Spjuth},

doi = {10.1093/bioinformatics/btz160},

year  = {2019},

date = {2019-01-01},

address = {Oxford},

abstract = {The PhenoMeNal consortium maintains a web portal (https://portal.phenomenal-h2020.eu) providing a GUI for launching the virtual research environment. The GitHub repository https://github.com/phnmnl/ hosts the source code of all projects. 

Supplementary data are available at Bioinformatics online. 

Developing a robust and performant data analysis workflow that integrates all necessary components whilst still being able to scale over multiple compute nodes is a challenging task. We introduce a generic method based on the microservice architecture, where software tools are encapsulated as Docker containers that can be connected into scientific workflows and executed using the Kubernetes container orchestrator. 

We developed a virtual research environment which facilitates rapid integration of new tools and developing scalable and interoperable workflows for performing metabolomics data analysis. The environment can be launched on-demand on cloud resources and desktop computers. IT-expertise requirements on the user side are kept to a minimum, and workflows can be re-used effortlessly by any novice user. We validate our method in the field of metabolomics on two mass spectrometry, one nuclear magnetic resonance spectroscopy and one fluxomics study. We showed that the method scales dynamically with increasing availability of computational resources. We demonstrated that the method facilitates interoperability using integration of the major software suites resulting in a turn-key workflow encompassing all steps for mass-spectrometry-based metabolomics including preprocessing, statistics, and identification. Microservices is a generic methodology that can serve any scientific discipline and opens up for new types of large-scale integrative science. 

AVAILABILITY AND IMPLEMENTATION 

SUPPLEMENTARY INFORMATION 

MOTIVATION 

RESULTS},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Fritsch:2019dt,

title = {ErtlFunctionalGroupsFinder: automated rule-based functional group detection with the Chemistry Development Kit (CDK)},

author = {Sebastian Fritsch and Stefan Neumann and Jonas Schaub and Christoph Steinbeck and Achim Zielesny},

url = {https://jcheminf.biomedcentral.com/articles/10.1186/s13321-019-0361-8},

doi = {10.1186/s13321-019-0361-8},

year  = {2019},

date = {2019-01-01},

journal = {Journal of cheminformatics},

volume = {11},

number = {1},

pages = {37},

publisher = {BioMed Central},

abstract = {The Ertl algorithm for automated functional groups (FG) detection and extraction of organic molecules is implemented on the basis of the Chemistry Development Kit (CDK). A distinct impact of the chosen CDK aromaticity model is demonstrated by an FG analysis of the ChEMBL database compounds. The average performance of less than a millisecond for a single-molecule FG extraction allows for fast processing of even large compound databases.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Christoph_Steinbeck60376927,

title = {NaPLeS: a natural products likeness scorer—web application and database},

author = {Christoph Steinbeck and Maria Sorokina and Christoph Steinbeck},

url = {http://doi.org/10.1186/s13321-019-0378-z},

doi = {10.1186/s13321-019-0378-z},

year  = {2019},

date = {2019-01-01},

journal = {Journal of Cheminformatics},

keywords = {},

pubstate = {published},

tppubtype = {article}

}