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Journal of Cheminformatics

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Featured article - SYBA: Bayesian estimation of synthetic accessibility of organic compounds

SYBA (SYnthetic Bayesian Accessibility) is a fragment-based method for the rapid classification of organic compounds as easy- (ES) or hard-to-synthesize (HS). It is based on a Bernoulli naïve Bayes classifier that is used to assign SYBA score contributions to individual fragments based on their frequencies in the database of ES and HS molecules. SYBA was trained on ES molecules available in the ZINC15 database and on HS molecules generated by the Nonpher methodology. SYBA was compared with a random forest, that was utilized as a baseline method, as well as with other two methods for synthetic accessibility assessment: SAScore and SCScore. When used with their suggested thresholds, SYBA improves over random forest classification, albeit marginally, and outperforms SAScore and SCScore. However, upon the optimization of SAScore threshold (that changes from 6.0 to – 4.5), SAScore yields similar results as SYBA. Because SYBA is based merely on fragment contributions, it can be used for the analysis of the contribution of individual molecular parts to compound synthetic accessibility.

Articles

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2020

In Silico Structure Generation: Recent Developments, Applications, and Challenges
Edited by José L. Medina-Franco, Emma Schymanski, Christoph Steinbeck
Collection published: 27 October 2020

Citation Typing Ontology (CiTO) Pilot
Edited by Egon Willighagen
Collection published: 28 July 2020

2019

Big Data in Chemistry
Edited by Igor V. Tetko
Collection published: 8 August 2019

Proceedings of the 11th International Conference on Chemical Structures
Edited by Gerard van Westen and Markus Wagener
Collection published: 14 February 2019

Programming Languages for Chemical Information
Edited by Rajarshi Guha
Collection published: 5 February 2019

2018

BioCreative V.5
Edited by Martin Krallinger, Obdulia Rabal, Anália Lourenço, Alfonso Valencia
Collection published: 14 December 2018

Novel applications of machine learning in cheminformatics
Edited by Ola Spjuth
Collection published: 21 February 2018

2015

Cross journal collection
Jean-Claude Bradley Memorial Series
Edited by Andrew SID Lang, Antony Williams
Collection published: 22 March 2015

2013

6th Joint Sheffield Conference on Chemoinformatics
Collection published: 29 July 2013

2012

The IUPAC International Chemical Identifier (InChI) and its influence on the domain of chemical information
Edited by Antony Williams
Collection published: 13 December 2012

Semantic physical science
Edited by Henry Rzepa, Peter Murray-Rust
Collection published: 3 August 2012

2011

Visions of a semantic molecular future
Collection published: 14 October 2011

RDF technologies in chemistry
Edited by Egon Willighagen, Martin Paul Braendle
Collection published: 13 May 2011

PubChem3D
Collection published: 27 January 2011

2020

Adoption of the Citation Typing Ontology by the Journal of Cheminformatics
Egon Willighagen
28 July 2020

Learning cheminformatics
Rajarshi Guha & Egon Willighagen
20 January 2020

2019

Journal of Cheminformatics, ORCID, and GitHub
Egon Willighagen, Nina Jeliazkova & Rajarshi Guha
8 July 2019

Implementing cheminformatics
Rajarshi Guha
5 February 2019

2018

Novel applications of Machine Learning in cheminformatics
Ola Spjuth
6 September 2018

2017

Helping to improve the practice of cheminformatics
Rajarshi Guha & Egon Willighagen

2013

Cheminformatics for the masses: a chance to increase educational opportunities for the next generation of cheminformaticians
David J Wild
5 July 2013

2012

InChI: connecting and navigating chemistry
Antony J Williams
13 December 2012

Semantic physical science
Peter Murray-Rust & Henry S Rzepa
3 August 2012

2011

Semantic science and its communication - a personal view
Peter Murray-Rust
14 October 2011

Resource description framework technologies in chemistry
Egon L Willighagen & Martin P Brändle
13 May 2011

2009

Grand challenges for cheminformatics
David J Wild

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Aims and Scope

Journal of CheminformaticsJournal of Cheminformatics is an open-access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.

Read the full scope here.

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New Collection: Big Data in Chemistry

The increasing volume of biomedical data in chemistry and life sciences requires the development of new methodologies and approaches for their analysis. Artificial intelligence (AI) and machine learning, especially neural networks, are increasingly used in the chemical industry, in particular with respect to big data. The collection presents progress and exemplifies the current needs, trends and requirements for machine learning in chemical data analysis.

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Editor profiles

Editors-in-Chief:

New Content ItemEgon Willighagen is a researcher in the BiGCaT Department for Bioinformatics and teacher at Maastricht University in the Netherlands.
 

New Content ItemRajarshi Guha is the Associate Director of Informatics at Vertex Pharmaceuticals where he leads the cheminformatics group that is responsible for informatics needs in high throughput screening.

Associate Editors:

Nina Jeliazkova, Idea Consult Ltd., Bulgaria
Barbara Zdrazil, University of Vienna, Austria

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Journal of Cheminformatics

ISSN: 1758-2946

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