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WWCodeHackathon

Women Who Code Mission: Predictable hackathon.

Team No. 18 - Bits N’ Bytes

COVID-19/SARS B-cell Epitope Prediction

A simple dataset for epitope prediction used in vaccine development

Introduction about Dataset

Due to spread of COVID-19, vaccine development is being demanded as soon as possible. Despite the importance of data analysis in vaccine development, there are not many simple data sets that data analysts can handle. The B-cell epitope predictions covered by in this dataset, is one of the key research topics in vaccine development. This dataset was developed during the research process and the data contained in it was obtained from IEDB and UniProt. And predicting of epitope regions is beneficial for the design and development of vaccines aimed to induce antigen-specific antibody production. This dataset has 14387 number of rows for all combinations of 14362 peptides and 757 proteins.

Column name Description
parent_protein_id parent protein ID
protein_seq parent protein sequence
start_position start position of peptide
end_position end position of peptide
peptide_seq peptide sequence
chou_fasman peptide feature, β turn
emini peptide feature, relative surface accessibility
kolaskar_tongaonkar peptide feature, antigenicity
parker peptide feature, hydrophobicity
isoelectric_point protein feature
aromacity protein feature
hydrophobicity protein feature
stability protein feature
target antibody valence (target value)

Relevant Papers

Epitope Prediction of Antigen Protein using Attention-Based LSTM Network (2020, bioRxiv)

Inspiration

Automated methods for B-cell epitope prediction. Machine learning helps rapid vaccine development.

The csv file input_bcell.csv for the dataset of this project can be downloaded from here

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  • Jupyter Notebook 99.9%
  • Python 0.1%