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Prediction of circRNA-miRNA Associations Based on Network Embedding

Wei Lan, Mingrui Zhu, Qingfeng Chen, Jianwei Chen, Jin Ye, Jin Liu, Wei Peng, Shirui Pan, Hassan Zargarzadeh
2021 Complexity  
In this paper, we propose a new computational method, NECMA, based on network embedding to predict potential associations between circRNAs and miRNAs.  ...  In our method, the Gaussian interaction profile (GIP) kernel similarities of circRNA and miRNA are calculated based on the known circRNA-miRNA associations, respectively.  ...  For the above purposes, in this study, we propose a new computational algorithm based on network embedding, NECMA, to predict circRNA-miRNA association.  ... 
doi:10.1155/2021/6659695 fatcat:6r4wcnn7pbbxpachee3tjm67k4

GCNCMI: A Graph Convolutional Neural Network Approach for Predicting circRNA-miRNA Interactions

Jie He, Pei Xiao, Chunyu Chen, Zeqin Zhu, Jiaxuan Zhang, Lei Deng
2022 Frontiers in Genetics  
In this paper, we proposed a graph convolutional neural network-based approach named GCNCMI to predict the potential interactions between circRNAs and miRNAs.  ...  In addition, the case studies of two miRNAs, hsa-miR-622 and hsa-miR-149-5p, showed that our model has a good effect on predicting circRNA-miRNA interactions.  ...  AUTHOR CONTRIBUTIONS JH and LD designed and implemented the prediction method. JH, PX, CC, and JZ analyzed the data and wrote the manuscript. LD reviewed and revised the manuscript.  ... 
doi:10.3389/fgene.2022.959701 pmid:35991563 pmcid:PMC9389118 fatcat:ozjnx4aizvglnj2qwrfniad2hu

SAAED: Embedding and Deep Learning Enhance Accurate Prediction of Association Between circRNA and Disease

Qingyu Liu, Junjie Yu, Yanning Cai, Guishan Zhang, Xianhua Dai
2022 Frontiers in Genetics  
Based on the CircR2Disease benchmark dataset for evaluation, a fivefold cross-validation experiment showed an AUC of 98.92%, an accuracy of 95.39%, and a sensitivity of 93.06%.  ...  CircRNA–disease, circRNAmiRNA, disease–gene, disease–miRNA, disease–lncRNA, and disease–drug association information are used in this paper.  ...  Calculation of circRNA Embedding Vector Based on the circRNA-disease and circRNA-miRNA association data, the circRNA-related adjacency matrix C is constructed, and the embedding vector of circRNA is calculated  ... 
doi:10.3389/fgene.2022.832244 pmid:35273640 pmcid:PMC8902643 fatcat:kxnebhbixfe67dsgknqnwjlm5e

Identifying disease-associated circRNAs based on edge-weighted graph attention and heterogeneous graph neural network [article]

Chengqian Lu, Lishen Zhang, Min Zeng, Wei Lan, Jianxin Wang
2022 bioRxiv   pre-print
The circRNA network, miRNA network, disease network and heterogeneous network are constructed based on the introduced multi-source data on circRNAs, miRNAs, and diseases.  ...  graph neural networks for discovering probable circRNA-disease correlations prediction.  ...  In this work, we devise a model to predict possible circRNA-disease associations based on a heterogeneous graph neural network.  ... 
doi:10.1101/2022.05.04.490565 fatcat:tzuddw6ya5d3xh7xpsn6lsozuy

KGDCMI: A New Approach for Predicting circRNA–miRNA Interactions From Multi-Source Information Extraction and Deep Learning

Xin-Fei Wang, Chang-Qing Yu, Li-Ping Li, Zhu-Hong You, Wen-Zhun Huang, Yue-Chao Li, Zhong-Hao Ren, Yong-Jian Guan
2022 Frontiers in Genetics  
This study thus proposed a novel computing method, named KGDCMI, to predict the interactions between circRNA and miRNA based on multi-source information extraction and fusion.  ...  Recognizing the circRNAmiRNA interaction provides a new perspective for the detection and treatment of human complex diseases.  ...  The NTSHMDA (Luo et al., 2018 ) constructs a heterogeneous network by similarity network and uses a method based on the random walk to predict the microbe-disease association.  ... 
doi:10.3389/fgene.2022.958096 pmid:36051691 pmcid:PMC9426772 fatcat:2vv7nqghrrellg6pn7ttiyrwh4

GATCDA: Predicting circRNA-Disease Associations Based on Graph Attention Network

Chen Bian, Xiu-Juan Lei, Fang-Xiang Wu
2021 Cancers  
In this study, we developed a novel computational method called GATCDA utilizing a graph attention network (GAT) to predict circRNA–disease associations with disease symptom similarity, network similarity  ...  As demonstrated by five-fold cross-validation, GATCDA yielded an AUC value of 0.9011. In addition, case studies showed that GATCDA can predict unknown circRNA–disease associations.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/cancers13112595 pmid:34070678 fatcat:pvurdjxvhzaezislq3rf6ze6pe

Learning representations of molecules to predict intermolecular interactions by constructing a large-scale heterogeneous molecular association network

Hai-Cheng Yi, Zhu-Hong You, De-Shuang Huang, Zhen-Hao Guo, Keith C.C. Chan, Yangming Li
2020 iScience  
To this end, a heterogeneous molecular association network is formed by systematically integrating comprehensive associations between miRNAs, lncRNAs, circRNAs, mRNAs, proteins, drugs, microbes, and complex  ...  More specifically, a network embedding model is developed to fully exploit the network behavior of biomolecules, and attribute features are also calculated.  ...  All nodes in the MAN network can be calculated for their network embedding based on their behavior with other nodes in the network.  ... 
doi:10.1016/j.isci.2020.101261 pmid:32580123 pmcid:PMC7317230 fatcat:4vpw2ykwyvdrjknq7w5zjuzyhq

SGCNCMI: A New Model Combining Multi-Modal Information to Predict circRNA-Related miRNAs, Diseases and Genes

Chang-Qing Yu, Xin-Fei Wang, Li-Ping Li, Zhu-Hong You, Wen-Zhun Huang, Yue-Chao Li, Zhong-Hao Ren, Yong-Jian Guan
2022 Biology  
The model can be used not only to predict the molecular level of circRNAmiRNA interactions but also to predict circRNA–cancer and circRNA–gene associations.  ...  Computational prediction of miRNAs, diseases, and genes associated with circRNAs has important implications for circRNA research, as well as provides a reference for wet experiments to save costs and time  ...  Notably, our model supports training and prediction using two types of training data, one based on circRNA-miRNA molecular sequences and known association data and the other based on circRNA as a cancer  ... 
doi:10.3390/biology11091350 fatcat:nulenazkynhh5ptmdmae2pip6m

DeepciRGO: functional prediction of circular RNAs through hierarchical deep neural networks using heterogeneous network features

Lei Deng, Wei Lin, Jiacheng Wang, Jingpu Zhang
2020 BMC Bioinformatics  
In addition, we demonstrate the considerable potential of integrating multiple interactions and association networks. Conclusions DeepciRGO will be a useful tool for accurately annotating circRNAs.  ...  However, determining the functions of circRNAs on a large scale is a challenging task because of the high experimental costs.  ...  The existing circRNA function prediction methods, for example, Mireap [14] , Miranda [15] , TargetScan [16] , and FunNet [17] , are mainly based on the principle of "guilt-by-association".  ... 
doi:10.1186/s12859-020-03748-3 pmid:33183227 fatcat:aqocgmhqejfzro4zlwykrdnkeq

Recent Deep Learning Methodology Development for RNA–RNA Interaction Prediction

Yi Fang, Xiaoyong Pan, Hong-Bin Shen
2022 Symmetry  
overview of deep learning models in the prediction of microRNA (miRNA)–mRNA interactions and long non-coding RNA (lncRNA)–miRNA interactions.  ...  This paper first gives a brief introduction to the traditional machine learning methods applied on RRI prediction and benchmark databases for training the models, and then provides a recent methodology  ...  Another GNN-based method, GEEL-FI [60] , is based on graph embeddings and deep attention neural networks.  ... 
doi:10.3390/sym14071302 fatcat:5lovtdwn3zb4dfbnjitwjnj3y4

Bioinformatics identification of the candidate microRNAs and construction of a competing endogenous RNA regulatory network in lacrimal gland adenoid cystic carcinoma high‑grade transformation

Meixia Jiang, Xun Liu, Chuanli Zhang, Limin Zhu, Hai-Dong Wu, Lijie Dong, Tingting Wang, Tingting Lin, Yanjin He
2021 Oncology Letters  
A miRNA microarray on paraffin-embedded tissues was performed to identify the differentially expressed miRNAs (DEMs) of LACC-HGT.  ...  The circRNAs and genes with high expression in LACC-HGT were predicted as targeting miRNAs, and the circRNA-miRNA-mRNA regulatory network was constructed. miR-140-3p was identified as part of the ceRNA  ...  Funding The present study was supported by a grant from The National Natural Science Foundation of China (grant no. 81570872) and The Tianjin Key Clinical Discipline Construction Project (grant nos.  ... 
doi:10.3892/ol.2021.12621 pmid:33747217 pmcid:PMC7967933 fatcat:idf3pyrzavhsvhjdc3x4answga

CircRNA-disease associations prediction based on metapath2vec++ and matrix factorization

Yuchen Zhang, Xiujuan Lei, Zengqiang Fang, Yi Pan
2020 Big Data Mining and Analytics  
In this study, we propose a computational method to predict circRNA-disesae associations which is based on metapath2vec++ and matrix factorization with integrated multiple data (called PCD_MVMF).  ...  Secondly, metapath2vec++ is applied on an integrated heterogeneous network to learn the embedded features and initial prediction score.  ...  Acknowledgment This work was supported by the National Natural Science Foundation of China (Nos. 61972451, 61672334, and 61902230) and the Fundamental Research Funds for the Central Universities, Shaanxi  ... 
doi:10.26599/bdma.2020.9020025 fatcat:qzlfugwdorcfxo7lpmdzzeghcu

CRAFT: a bioinformatics software for custom prediction of circular RNA functions [article]

Anna Dal Molin, Enrico Gaffo, Valeria Difilippo, Alessia Buratin, Caterina Tretti Parenzan, Silvia Bresolin, Stefania Bortoluzzi
2021 bioRxiv   pre-print
, mainly focusing on the miRNA sponge activity of circRNAs.  ...  Currently, circRNA functional predictions are provided by web databases that do not allow custom analyses, while self-standing circRNA prediction tools are mostly limited to predict only one type of function  ...  CRAFT miRNA prediction output based on circZNF609 analysis.  ... 
doi:10.1101/2021.11.17.468947 fatcat:j3ujl3xh35g4zdzug7eycqj5aq

Expression Profiles of CircRNA and mRNA in Lacrimal Glands of AQP5–/– Mice With Primary Dry Eye

Yaning Liu, Guohu Di, Shaohua Hu, Tianyu Zhao, Xinkai Xu, Xiaoyi Wang, Peng Chen
2020 Frontiers in Physiology  
According to the bioinformatics analysis of identified circRNAs, we predicted a circRNA-miRNA-mRNA network of phagosomes.  ...  We identified differently expressed circRNAs in the lacrimal glands of AQP5-/- and AQP5+/+ mice, predicting a circRNA-miRNA-mRNA network of phagosomes.  ...  of Qingdao University (Qingdao, China).  ... 
doi:10.3389/fphys.2020.01010 pmid:33013441 pmcid:PMC7497440 fatcat:f7xtxn3voneitjegs6aipkd27e

Integrated Analysis of circRNA-miRNA-mRNA ceRNA Network in Cardiac Hypertrophy

Yang-Hao Chen, Ling-Feng Zhong, Xia Hong, Qian-Li Zhu, Song-Jie Wang, Ji-Bo Han, Wei-Jian Huang, Bo-Zhi Ye
2022 Frontiers in Genetics  
Based on this result, we went on to establish a circRNAs-related ceRNA regulatory network.  ...  This study is the first to establish a circRNA-mediated ceRNA regulatory network associated with myocardial hypertrophy.  ...  Based on a miRNA First Strand cDNA Synthesis Tailing Reaction kit (Sangon Biotech), we got the first strand cDNA of miRNA.  ... 
doi:10.3389/fgene.2022.781676 pmid:35211156 pmcid:PMC8860901 fatcat:tek2dipkwbgthnwzjrbderi6nq
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