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Preprints, Working Papers, ... Year : 2024

Antibiotic Bacteria Interaction: Dataset and Benchmarking

Abstract

This study introduces a dataset for drug-bacteria associations (DBA) that affects humans. Our contribution extends beyond merely curating the association matrix; we also conduct genomic similarity computations for all known bacteria impacting humans and assess structural similarities for all antibiotic drugs. This is a first of a kind dataset serving the fundamental goal of streamlining antibiotic repurposing for bacterial infections. we conducted thorough benchmarking on this dataset using state-of-the-art drug repurposing models. Furthermore, we applied this dataset to three case studies involving drug-resistant bacterial infections. Our results indicate that the dataset coupled with the algorithms are indeed effective for repurposing drugs with the potential for treating drug resistant bacterial infections.
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Dates and versions

hal-04376907 , version 1 (07-01-2024)

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  • HAL Id : hal-04376907 , version 1

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Sayantika Chatterjee, Angshul Majumdar, Emilie Chouzenoux. Antibiotic Bacteria Interaction: Dataset and Benchmarking. 2023. ⟨hal-04376907⟩
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