DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity

Our proposed DeepMiRBP strategy represents the first of its kind designed for microRNA-protein interaction prediction. Its promising performance underscores the model's potential to uncover novel interactions critical for small RNA sorting and packaging, as well as to infer new RNA transporter proteins. The methodologies and insights from DeepMiRBP offer a scalable template for future small RNA research, from mechanistic discovery to modeling disease-related cell-to-cell communication, emphasizing its adaptability and potential for developing novel small RNA-centric therapeutic interventions and personalized medicine.

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Publication Details

Journal
BMC Bioinformatics
Published
2024-12-18
DOI
https://doi.org/10.1186/s12859-024-05985-2
Citations
2
Primary Topic
MicroRNA in disease regulation
Type
article
Field-Weighted Citation Impact
0.57
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article

DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity

Juan Cui, Sasan Azizian
2 citations
BMC Bioinformatics
MicroRNA in disease regulation
0.57
article

DeepMiRBP: a hybrid model for predicting microRNA-protein interactions based on transfer learning and cosine similarity

Juan Cui, Sasan Azizian
article en
2 citations

Abstract

Our proposed DeepMiRBP strategy represents the first of its kind designed for microRNA-protein interaction prediction. Its promising performance underscores the model's potential to uncover novel interactions critical for small RNA sorting and packaging, as well as to infer new RNA transporter proteins. The methodologies and insights from DeepMiRBP offer a scalable template for future small RNA research, from mechanistic discovery to modeling disease-related cell-to-cell communication, emphasizing its adaptability and potential for developing novel small RNA-centric therapeutic interventions and personalized medicine.

BMC BioinformaticsVol. 25(1)
University of Nebraska–Lincoln (US)
Openalex Percentile: Top 30%
MicroRNA in disease regulation
0.57
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