GraphTar: applying word2vec and graph neural networks to miRNA target prediction
Abstract Background MicroRNAs (miRNAs) are short, non-coding RNA molecules that regulate gene expression by binding to specific mRNAs, inhibiting their translation. They play a critical role in regulating various biological processes and are implicated in many diseases, including cardiovascular, onc...
Main Authors: | Jan Przybyszewski, Maciej Malawski, Sabina Lichołai |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2023-11-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12859-023-05564-x |
Similar Items
-
Service Discovery Method Based on Knowledge Graph and Word2vec
by: Junkai Zhou, et al.
Published: (2022-08-01) -
RDF-star2Vec: RDF-star Graph Embeddings for Data Mining
by: Shusaku Egami, et al.
Published: (2023-01-01) -
Integrating Heterogeneous Graphs Using Graph Transformer Encoder for Solving Math Word Problems
by: Soyun Shin, et al.
Published: (2023-01-01) -
Prediction of adverse drug reactions based on knowledge graph embedding
by: Fei Zhang, et al.
Published: (2021-02-01) -
Word Sense Disambiguation Using Cosine Similarity Collaborates with Word2vec and WordNet
by: Korawit Orkphol, et al.
Published: (2019-05-01)