Journal of Cheminformatics is an open-access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.
Featured article - MS2DeepScore: a novel deep learning similarity measure to compare tandem mass spectra
Mass spectrometry data is one of the key sources of information in many workflows in medicine and across the life sciences. Mass fragmentation spectra are generally considered to be characteristic signatures of the chemical compound they originate from, yet the chemical structure itself usually cannot be easily deduced from the spectrum. Often, spectral similarity measures are used as a proxy for structural similarity but this approach is strongly limited by a generally poor correlation between both metrics. Here, the authors propose MS2DeepScore: a novel Siamese neural network to predict the structural similarity between two chemical structures solely based on their MS/MS fragmentation spectra. Using a cleaned dataset of > 100,000 mass spectra of about 15,000 unique known compounds, the authors trained MS2DeepScore to predict structural similarity scores for spectrum pairs with high accuracy. In addition, sampling different model varieties through Monte-Carlo Dropout is used to further improve the predictions and assess the model’s prediction uncertainty. On 3600 spectra of 500 unseen compounds, MS2DeepScore is able to identify highly-reliable structural matches and to predict Tanimoto scores for pairs of molecules based on their fragment spectra with a root mean squared error of about 0.15. Furthermore, the prediction uncertainty estimate can be used to select a subset of predictions with a root mean squared error of about 0.1. Furthermore, the authors demonstrate that MS2DeepScore outperforms classical spectral similarity measures in retrieving chemically related compound pairs from large mass spectral datasets, thereby illustrating its potential for spectral library matching. Finally, MS2DeepScore can also be used to create chemically meaningful mass spectral embeddings that could be used to cluster large numbers of spectra. Added to the recently introduced unsupervised Spec2Vec metric, the authors believe that machine learning-supported mass spectral similarity measures have great potential for a range of metabolomics data processing pipelines.
Featured Collection - In Silico Structure Generation: Recent Developments, Applications, and Challenges
This special collection showcases recent advances, applications, challenges in the enumeration of chemical structures: from the design to the analysis and use of either small, focused data sets, to large compound libraries. Analysis and handling of the newly constructed chemical structures include the storage, mining, integration of the constructed structures with other existing data sets, and curation.
Biomedical Data Analyses Facilitated by Open Cheminformatics Workflows
Edited by Eva Nittinger, Alex Clark, Anna Gaulton, Barbara Zdrazil
Started publishing: 2 July 2021
In Silico Structure Generation: Recent Developments, Applications, and Challenges
Edited by José L. Medina-Franco, Emma Schymanski, Christoph Steinbeck
Started publishing: 27 October 2020
Citation Typing Ontology (CiTO) Pilot
Edited by Egon Willighagen
Started publishing: 28 July 2020
Big Data in Chemistry
Edited by Igor V. Tetko
Started publishing: 8 August 2019
Proceedings of the 11th International Conference on Chemical Structures
Edited by Gerard van Westen and Markus Wagener
Started publishing: 14 February 2019
Programming Languages for Chemical Information
Edited by Rajarshi Guha
Started publishing: 5 February 2019
Edited by Martin Krallinger, Obdulia Rabal, Anália Lourenço, Alfonso Valencia
Started publishing: 14 December 2018
Novel applications of machine learning in cheminformatics
Edited by Ola Spjuth
Started publishing: 21 February 2018
Cross journal collection
Jean-Claude Bradley Memorial Series
Edited by Andrew SID Lang, Antony Williams
Started publishing: 22 March 2015
6th Joint Sheffield Conference on Chemoinformatics
Started publishing: 29 July 2013
The IUPAC International Chemical Identifier (InChI) and its influence on the domain of chemical information
Edited by Antony Williams
Started publishing: 13 December 2012
Semantic physical science
Edited by Henry Rzepa, Peter Murray-Rust
Started publishing: 3 August 2012
Visions of a semantic molecular future
Started publishing: 14 October 2011
RDF technologies in chemistry
Edited by Egon Willighagen, Martin Paul Braendle
Started publishing: 13 May 2011
Started publishing: 27 January 2011
What is the role of cheminformatics in a pandemic?
Rajarshi Guha, Egon Willighagen, Barbara Zdrazil & Nina Jeliazkova
2 March 2021
From Big Data to Artificial Intelligence: chemoinformatics meets new challenges
Igor V. Tetko & Ola Engkvist
18 December 2020
Adoption of the Citation Typing Ontology by the Journal of Cheminformatics
28 July 2020
Rajarshi Guha & Egon Willighagen
20 January 2020
Journal of Cheminformatics, ORCID, and GitHub
Egon Willighagen, Nina Jeliazkova & Rajarshi Guha
8 July 2019
5 February 2019
Novel applications of Machine Learning in cheminformatics
6 September 2018
Helping to improve the practice of cheminformatics
Rajarshi Guha & Egon Willighagen
InChI: connecting and navigating chemistry
Antony J Williams
13 December 2012
Semantic physical science
Peter Murray-Rust & Henry S Rzepa
3 August 2012
Semantic science and its communication - a personal view
14 October 2011
Resource description framework technologies in chemistry
Egon L Willighagen & Martin P Brändle
13 May 2011
Grand challenges for cheminformatics
David J Wild
Upcoming Special Issues
Learn more about open Calls for Papers and upcoming Special Issues here.
Modern data science approaches aim to properly interconnect information in order to generate new knowledge and reveal hidden relationships in the data. The open data revolution has given users explicit rights, via open licenses, to download, curate, and reshare results, leading to a democratization of data. This collection focuses on cheminformatics workflows licensed with an OSI-approved or Creative Commons license, serving the curation and analysis of diverse life science data sets.
Call for Editor applications!
Journal of Cheminformatics is looking for a new Associate Editor. To find out more information, including how to apply if you are interested, please click here.
The Journal of Cheminformatics is piloting use of the Citation Typing Ontology (CiTO) in its papers. Any author wishing to submit to the journal is free to participate in the pilot. To learn more about how, please click through to our dedicated page on the CiTO pilot and to see published papers already participating in the pilot.
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We offer a free open access support service to make it easier for you to discover and apply for article-processing charge (APC) funding.
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Rajarshi Guha is currently a Director in Data & Computational Sciences at Vertex Pharmaceuticals, covering method development for small molecule informatics, genomics and image analytics.
Barbara Zdrazil is a group leader at the University of Vienna, Austria, and works as a safety data scientist for the European Bioinformatics Institute (EMBL-EBI), UK.
Nina Jeliazkova is a founder and co-owner of Ideaconsult Ltd, Bulgaria, and has been technical manager of the company since 2009.
Annual Journal Metrics
47 days to first decision for reviewed manuscripts only
32 days to first decision for all manuscripts
124 days from submission to acceptance
16 days from acceptance to publication
1567 Altmetric mentions
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