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RMechDB Documentation

RMechDB overview


Climate change
Air pollutants
Wild fires
Ozone depletion
Atmospheric pollutions

A free radical is a chemical compound with at least one half occupied orbital. The presence of the half occupied orbitals makes a radical compound highly reactive. Therefore, free radicals have the potential to both serve as powerful chemical tools and be extremely harmful contaminants. Chemical reactions involving a free radical are an essential part of synthetic, biochemical, atmospheric, and plasma chemistry. For instance, the climate crisis has dramatically altered fire activity worldwide. Wild land fires are increasing in frequency, duration, intensity, and size. The chemistry of flames is dominated by radical reactions and the chemical composition of fire smoke changes during atmospheric transport. This so-called “aging” of smoke is poorly understood, but known to be largely driven by free radical processes

RMechDB is a live platform for aggregating, curating, and distributing chemcial reactions in the form of elementary radical steps to accelerate research in chemoinformatics and radical reaction modeling. The RMechDB platform is designed to facilitate training deep learning and other AI models in data-driven workflows using its tabular data, with no need for additional pre-processing steps It provides a unified model that ought to facilitate data sharing, model building, dissemination, and publications. We encourage the community to explore and use the RMechDB data and functionalities, and contribute to its expansion.

Click here to read the RMechDB paper.


How to use RMechDB

To download the RMechDB data set, the user must enter his information and email address. Upon reading and agreeing to the terms of the CC-BY-NC-ND license, the user will receive an email containing the RMechDB data set. The RMechDB data set is a directory with five comma separated value (csv) files:

    all.csv:   All the radical elementary steps in the RMechDB data set.
    train_core.csv:   All the core radical elementary steps chosen for training machine learning models.
    train_specific.csv:   All the specific radical elementary steps chosen for training machine learning models.
    test_core.csv:   All the core radical elementary steps chosen for testing machine learning models.
    test_scpecific.csv:   All the specific radical elementary steps chosen for testing machine learning models.


Each of the csv files has five columns:
    1. The SMIKRS of elementary steps.
    2. The arrow codes of elementary steps.
    3. The intial condition of elementary steps.
    4. The category of elementary steps based on the three class classification explained in the Composition of the RMechDB Data Set section of the RMechDB paper.
    5. The category of the elementary step based on the seven class classification explained in the Composition of the RMechDB Data Set section of the RMechDB paper.

Upload multiple reaction steps

You must create a comma separated value (.csv) file containing all the steps. Each row of the file must represent a reaction with four columns:

(1) Reaction SMIRKS
(2) Arrow codes
(3) Original source
(4) Auxilary information (e.g. initial energy, special condition such as low pressure)

Here is a file sample that must be uploaded to the RMechDB:

If you could not upload the file you prepared, or the reaction data you collected does not fit the format mentioned above,

You can send the file via email to:

  • Amin Tavakoli , Email: mohamadt [at] uci [dot] edu.
  • Pierre Baldi , Email: pfbaldi [at] uci [dot] edu.
The subject of the email must read Upload Reactions to RMechDB.
It would be helpful that within your email, you include the reason(s) why you did not upload the file.
After receveing your email, we perform automatic and manual examination of the reactions. Then, you will receive and email with information on weather the reaction was inserted into the RMechDB database or not.
You can contact us with your questions.

Read this documentation on how to use Ketcher to draw molecules and reactions.