ORCID Profile
0000-0001-6966-0814
Current Organisations
Friedrich-Schiller-Universität Jena
,
European Bioinformatics Institute
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Publisher: Springer Science and Business Media LLC
Date: 23-04-2022
DOI: 10.1186/S13321-022-00604-9
Abstract: Chemical structure generators are used in cheminformatics to produce or enumerate virtual molecules based on a set of boundary conditions. The result can then be tested for properties of interest, such as adherence to measured data or for their suitability as drugs. The starting point can be a potentially fuzzy set of fragments or a molecular formula. In the latter case, the generator produces the set of constitutional isomers of the given input formula. Here we present the novel constitutional isomer generator based on the canonical generation path method. uses the package to compute automorphism groups of graphs. We outline the working principles of and present benchmarking results which show that is currently the fastest structure generator. is available under a liberal open-source license.
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C8NP90041H
Abstract: Correction for ‘The value of universally available raw NMR data for transparency, reproducibility, and integrity in natural product research’ by James B. McAlpine et al. , Nat. Prod. Rep. , 2018, DOI: 10.1039/c7np00064b.
Publisher: Royal Society of Chemistry (RSC)
Date: 2019
DOI: 10.1039/C7NP00064B
Abstract: With contributions from the global natural product (NP) research community, and continuing the Raw Data Initiative, this review collects a comprehensive demonstration of the immense scientific value of disseminating raw nuclear magnetic resonance (NMR) data, independently of, and in parallel with, classical publishing outlets.
Publisher: Wiley
Date: 16-05-2018
DOI: 10.1002/MRC.4737
Publisher: Public Library of Science (PLoS)
Date: 20-02-2014
Publisher: American Chemical Society (ACS)
Date: 22-09-2007
DOI: 10.1021/CI600531A
Abstract: CMLSpect is an extension of Chemical Markup Language (CML) for managing spectral and other analytical data. It is designed to be flexible enough to contain a wide variety of spectral data. The paper describes the CMLElements used and gives practical ex les for common types of spectra. In addition it demonstrates how different views of the data can be expressed and what problems still exist.
Publisher: SAGE Publications
Date: 12-2018
Abstract: WITH THE INCREASE IN prevalence of food allergy (FA) in young children, early childhood education and care (ECEC) providers are likely to have more enrolments of children who are at risk of anaphylaxis. This study examines the status of FA management in ECEC, and assesses the services’ current readiness to prevent and manage FA. A cross-sectional study comprising an online survey with multiple-choice and open-ended questions was conducted with 53 long day care services in Western Australia. Among the respondents, 83 per cent of services had at least one child enrolled with FA, 96 per cent had an FA policy, and 91 per cent required staff to undertake anaphylaxis training. A high level of self-reported confidence and skills were demonstrated however, gaps were identified in risk-minimisation knowledge, use of adrenaline (epinephrine) autoinjectors and available resources. Extensive promotion of available resources will help improve compliance with anaphylaxis guidelines.
Publisher: Springer Science and Business Media LLC
Date: 11-2016
DOI: 10.1038/NBT.3689
Publisher: Springer Science and Business Media LLC
Date: 27-01-2012
DOI: 10.1038/NG.1054
Publisher: Springer Science and Business Media LLC
Date: 13-12-2022
DOI: 10.1186/S13321-022-00663-Y
Abstract: Homologous series are groups of related compounds that share the same core structure attached to a motif that repeats to different degrees. Compounds forming homologous series are of interest in multiple domains, including natural products, environmental chemistry, and drug design. However, many homologous compounds remain unannotated as such in compound datasets, which poses obstacles to understanding chemical ersity and their analytical identification via database matching. To overcome these challenges, an algorithm to detect homologous series within compound datasets was developed and implemented using the RDKit. The algorithm takes a list of molecules as SMILES strings and a monomer (i.e., repeating unit) encoded as SMARTS as its main inputs. In an iterative process, substructure matching of repeating units, molecule fragmentation, and core detection lead to homologous series classification through grouping of identical cores. Three open compound datasets from environmental chemistry (NORMAN Suspect List Exchange, NORMAN-SLE), exposomics (PubChemLite for Exposomics), and natural products (the COlleCtion of Open NatUral producTs, COCONUT) were subject to homologous series classification using the algorithm. Over 2000, 12,000, and 5000 series with CH 2 repeating units were classified in the NORMAN-SLE, PubChemLite, and COCONUT respectively. Validation of classified series was performed using published homologous series and structure categories, including a comparison with a similar existing method for categorising PFAS compounds. The OngLai algorithm and its implementation for classifying homologues are openly available at: delenelai/onglai-classify-homologues .
Publisher: American Chemical Society (ACS)
Date: 20-01-2016
Location: United Kingdom of Great Britain and Northern Ireland
No related grants have been discovered for Christoph Steinbeck.