ArticleBMC bioinformatics2021
Capsule-LPI: a LncRNA-protein interaction predicting tool based on a capsule network.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 52 citations in OpenAlex.
- Metamorphosis and lncRNAs: A Close Relationship.Genesis (New York, N.Y. : 2000) · 2026Review
- LncPTPred: predicting lncRNA-protein interaction based on crosslinking and immunoprecipitation (CLIP-Seq) data.Briefings in bioinformatics · 2025Article
- MFH-LPI: based on multi-view similarity networks fusion and hypergraph learning for long non-coding RNA-protein interactions prediction.BMC genomics · 2025Article
- Negative sampling strategies impact the prediction of scale-free biomolecular network interactions with machine learning.BMC biology · 2025Article
- Graph-RPI: predicting RNA-protein interactions via graph autoencoder and self-supervised learning strategies.Briefings in bioinformatics · 2025Article
- Review
- Inter-view contrastive learning and miRNA fusion for lncRNA-protein interaction prediction in heterogeneous graphs.Briefings in bioinformatics · 2025Article
- LPItabformer: Enhancing generalization in predicting lncRNA-protein interactions via a tabular Transformer.Computational and structural biotechnology journal · 2025Article
- Predicting lncRNA-protein interactions using a hybrid deep learning model with dinucleotide-codon fusion feature encoding.BMC genomics · 2024Article
- Predicting lncRNA-protein interactions through deep learning framework employing multiple features and random forest algorithm.BMC bioinformatics · 2024Article
- Prediction of LncRNA-protein Interactions Using Auto-Encoder, SE-ResNet Models and Transfer Learning.MicroRNA (Shariqah, United Arab Emirates) · 2024Article
- Analysis of lncRNAs inNon-coding RNA · 2023Article
- Deep Learning Approaches for lncRNA-Mediated Mechanisms: A Comprehensive Review of Recent Developments.International journal of molecular sciences · 2023Review
- Discovery and Validation of Clinically Relevant Long Non-Coding RNAs in Colorectal Cancer.Cancers · 2022Review
- Artificial intelligence methods enhance the discovery of RNA interactions.Frontiers in molecular biosciences · 2022Review
- Editorial: Machine Learning-Based Methods for RNA Data Analysis.Frontiers in genetics · 2022Article
- Opportunities and Challenges of Predictive Approaches for the Non-coding RNA in Plants.Frontiers in plant science · 2022Article
- Long non-coding RNAs and their potential impact on diagnosis, prognosis, and therapy in prostate cancer: racial, ethnic, and geographical considerations.Expert review of molecular diagnostics · 2021Review
- LPI-HyADBS: a hybrid framework for lncRNA-protein interaction prediction integrating feature selection and classification.BMC bioinformatics · 2021Article
- LPI-deepGBDT: a multiple-layer deep framework based on gradient boosting decision trees for lncRNA-protein interaction identification.BMC bioinformatics · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 1 institution in 2 countries.
Funding
Abstract
backgroundLong noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA-protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging. How to integrate multimodal features from more perspectives and build deep learning architectures with better recognition performance have always been the focus of research on LPIs.
resultsWe present a novel multichannel capsule network framework to integrate multimodal features for LPI prediction, Capsule-LPI. Capsule-LPI integrates four groups of multimodal features, including sequence features, motif information, physicochemical properties and secondary structure features. Capsule-LPI is composed of four feature-learning subnetworks and one capsule subnetwork. Through comprehensive experimental comparisons and evaluations, we demonstrate that both multimodal features and the architecture of the multichannel capsule network can significantly improve the performance of LPI prediction. The experimental results show that Capsule-LPI performs better than the existing state-of-the-art tools. The precision of Capsule-LPI is 87.3%, which represents a 1.7% improvement. The F-value of Capsule-LPI is 92.2%, which represents a 1.4% improvement.
conclusionsThis study provides a novel and feasible LPI prediction tool based on the integration of multimodal features and a capsule network. A webserver ( http://csbg-jlu.site/lpc/predict ) is developed to be convenient for users.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.