ArticleOncotarget2016
IRWRLDA: improved random walk with restart for lncRNA-disease association prediction.
Article in Oncotarget, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 100 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
100 citing papers in PubMed.
- Genome-wide analyses of long noncoding RNA expression profiles in lung adenocarcinoma.Scientific reports · 2017Trial
- Meta-signature LncRNAs serve as novel biomarkers for colorectal cancer: integrated bioinformatics analysis, experimental validation and diagnostic evaluation.Scientific reports · 2017Trial
- DSGCNLDA: A Multi-view Learning Model with DualScope Attention for lncRNA-Disease Association Prediction.Interdisciplinary sciences, computational life sciences · 2026Article
- Decoding potential lncRNA and disease associations through graph representation learning and gradient boosting with histogram.Scientific reports · 2025Article
- Neighborhood-Regularized Matrix Factorization for lncRNA-Disease Association Identification.International journal of molecular sciences · 2025Article
- LDAGM: prediction lncRNA-disease asociations by graph convolutional auto-encoder and multilayer perceptron based on multi-view heterogeneous networks.BMC bioinformatics · 2024Article
- iGATTLDA: Integrative graph attention and transformer-based model for predicting lncRNA-Disease associations.IET systems biology · 2024Article
- Identification of Drought Stress-Responsive Genes in Rice by Random Walk with Multi-Restart Probability on MultiPlex Biological Networks.International journal of molecular sciences · 2024Article
- Node-adaptive graph Transformer with structural encoding for accurate and robust lncRNA-disease association prediction.BMC genomics · 2024Article
- GCNFORMER: graph convolutional network and transformer for predicting lncRNA-disease associations.BMC bioinformatics · 2024Article
- A novel microbe-drug association prediction model based on stacked autoencoder with multi-head attention mechanism.Scientific reports · 2023Article
- Ranking Plant Network Nodes Based on Their Centrality Measures.Entropy (Basel, Switzerland) · 2023Article
- GM-lncLoc: LncRNAs subcellular localization prediction based on graph neural network with meta-learning.BMC genomics · 2023Article
- A lncRNA-disease association prediction tool development based on bridge heterogeneous information network via graph representation learning for family medicine and primary care.Frontiers in genetics · 2023Article
- A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning.BMC bioinformatics · 2022Article
- JSCSNCP-LMA: a method for predicting the association of lncRNA-miRNA.Scientific reports · 2022Article
- iPiDA-GCN: Identification of piRNA-disease associations based on Graph Convolutional Network.PLoS computational biology · 2022Article
- A Survey on Computational Methods for Investigation on ncRNA-Disease Association through the Mode of Action Perspective.International journal of molecular sciences · 2022Review
- HBRWRLDA: predicting potential lncRNA-disease associations based on hypergraph bi-random walk with restart.Molecular genetics and genomics : MGG · 2022Article
- High expression of lncRNA PELATON serves as a risk factor for the incidence and prognosis of acute coronary syndrome.Scientific reports · 2022Article
40 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In recent years, accumulating evidences have shown that the dysregulations of lncRNAs are associated with a wide range of human diseases. It is necessary and feasible to analyze known lncRNA-disease associations, predict potential lncRNA-disease associations, and provide the most possible lncRNA-disease pairs for experimental validation. Considering the limitations of traditional Random Walk with Restart (RWR), the model of Improved Random Walk with Restart for LncRNA-Disease Association prediction (IRWRLDA) was developed to predict novel lncRNA-disease associations by integrating known lncRNA-disease associations, disease semantic similarity, and various lncRNA similarity measures. The novelty of IRWRLDA lies in the incorporation of lncRNA expression similarity and disease semantic similarity to set the initial probability vector of the RWR. Therefore, IRWRLDA could be applied to diseases without any known related lncRNAs. IRWRLDA significantly improved previous classical models with reliable AUCs of 0.7242 and 0.7872 in two known lncRNA-disease association datasets downloaded from the lncRNADisease database, respectively. Further case studies of colon cancer and leukemia were implemented for IRWRLDA and 60% of lncRNAs in the top 10 prediction lists have been confirmed by recent experimental reports.
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.