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The Chemical Checker (CC) is a data-driven resource of small molecule bioactivity data. The main goal of the CC is to express data in a format that can be used off-the-shelf in daily computational drug discovery tasks. The resource is organized in **5 levels** of increasing complexity, ranging from the chemical properties of the compounds to their clinical outcomes. In between, we consider targets, off-targets, perturbed biological networks and several cell-based assays, including gene expression, growth inhibition, and morphological profiles. The CC is different to other integrative compounds database in almost every aspect. The classical, relational representation of the data is surpassed here by a less explicit, more machine-learning-friendly abstraction of the data (see the CC [Manifesto](manifesto)).
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The CC resource is ever-growing and maintained by the [Structural Bioinformatics & Network Biology Laboratory](http://sbnb.irbbarcelona.org) at the Institute for Research in Biomedicine ([IRB Barcelona](http://irbbarcelona.org)). Should you have any inquiries, please send an email to [miquel.duran@irbbarcelona.org](miquel.duran@irbbarcelona.org) or [patrick.aloy@irbbarcelona.org](patrick.aloy@irbbarcelona.org).
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The CC resource is ever-growing and maintained by the [Structural Bioinformatics & Network Biology Laboratory](http://sbnb.irbbarcelona.org) at the Institute for Research in Biomedicine ([IRB Barcelona](http://irbbarcelona.org)). Should you have any questions, please send an email to [miquel.duran@irbbarcelona.org](miquel.duran@irbbarcelona.org) or [patrick.aloy@irbbarcelona.org](patrick.aloy@irbbarcelona.org).
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The CC was first released to the scientific community in the following paper: [Duran-Frigola et al., *Extending the small molecule similarity principle to all levels of biology* (2019)](https://www.dropbox.com/s/x2rqszfdfpqdqdy/duranfrigola_etal_ms_current.pdf?dl=0), and has since produced a number of [related publications](publications).
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This project first presented to the scientific community in the following paper: [Duran-Frigola et al., *Extending the small molecule similarity principle to all levels of biology* (2019)](https://www.dropbox.com/s/x2rqszfdfpqdqdy/duranfrigola_etal_ms_current.pdf?dl=0), and has since produced a number of [related publications](publications).
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## Source data and datasets
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The CC capitalizes on publicly-available bioactivity data fetched from different sources. We are committed to updating the CC resource **every 6 months** (versions named accordingly, e.g. `chemical_checker_2019_01`), including the latest datasets, and incorporating new ones upon request and posterior evaluation by our team.
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The CC capitalizes on publicly-available bioactivity data fetched from many sources. We are committed to updating the resource **every 6 months** (versions named accordingly, e.g. `chemical_checker_2019_01`), incorporating the latest datasets, and adding new ones upon request and posterior evaluation by our team.
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The basic data unit of the CC is the *dataset*. There are 5 *levels* (`A` Chemistry, `B` Targets, `C` Networks, `D` Cells and `E` Clinics) and, in turn, each level is divided into 5 sublevels or *coordinates* (`A1`-`E5`), denoting different types or aspects of the data. Each dataset belongs to one and only one of the 25 coordinates, and each coordinate can have an arbitrary number of datasets (e.g. `A1.001`), one of which is selected as being *exemplary*.
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The CC is a chemistry-first biomedical resource and, as such, it contains several predefined compound collections that are of interest to drug discovery, including approved drugs, natural products, and commercial screening libraries.
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The CC is a chemistry-first biomedical resource and, as such, it contains several predefined compound collections that are of interest to drug discoverers, including approved drugs, natural products, and commercial screening libraries.
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For further information, please refer to:
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* [Bioactivity data sources](data)
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