ArticleFrontiers in genetics2018
Multivariate Information Fusion With Fast Kernel Learning to Kernel Ridge Regression in Predicting LncRNA-Protein Interactions.
Article in Frontiers in genetics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed.
- Fusion of multi-source relationships and topology to infer lncRNA-protein interactions.Molecular therapy. Nucleic acids · 2024Article
- A systems genomics approach to uncover patient-specific pathogenic pathways and proteins in ulcerative colitis.Nature communications · 2022Article
- LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification.BMC bioinformatics · 2021Article
- A Survey of Current Resources to Study lncRNA-Protein Interactions.Non-coding RNA · 2021Review
- A sequence-based multiple kernel model for identifying DNA-binding proteins.BMC bioinformatics · 2021Article
- An Accurate Tool for Uncovering Cancer Subtypes by Fast Kernel Learning Method to Integrate Multiple Profile Data.Frontiers in cell and developmental biology · 2021Article
- A deep learning model for plant lncRNA-protein interaction prediction with graph attention.Molecular genetics and genomics : MGG · 2020Article
- LPI-SKF: Predicting lncRNA-Protein Interactions Using Similarity Kernel Fusions.Frontiers in genetics · 2020Article
- LPI-IBNRA: Long Non-coding RNA-Protein Interaction Prediction Based on Improved Bipartite Network Recommender Algorithm.Frontiers in genetics · 2019Article
- Probing lncRNA-Protein Interactions: Data Repositories, Models, and Algorithms.Frontiers in genetics · 2019Review
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Long non-coding RNAs (lncRNAs) constitute a large class of transcribed RNA molecules. They have a characteristic length of more than 200 nucleotides which do not encode proteins. They play an important role in regulating gene expression by interacting with the homologous RNA-binding proteins. Due to the laborious and time-consuming nature of wet experimental methods, more researchers should pay great attention to computational approaches for the prediction of lncRNA-protein interaction (LPI). An in-depth literature review in the state-of-the-art
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Registered trials
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