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ncRNA-disease association prediction based on sequence information and tripartite network

Takuya Mori, Hayliang Ngouv, Morihiro Hayashida, Tatsuya Akutsu, Jose C. Nacher
2018 BMC Systems Biology  
Results: This study utilizes a disease-target-ncRNA tripartite network, and computes prediction scores between each disease-ncRNA pair by integrating biological information derived from pairwise similarity  ...  adding biological sequence information to enhance predictions.  ...  s method [13] . ncPred is a resource-propagation-based method applied on an ncRNA-target-disease tripartite network.  ... 
doi:10.1186/s12918-018-0527-4 pmid:29671405 pmcid:PMC5907179 fatcat:qmtrexyelrckbldlfull4bgj4m

Computational methods and applications for identifying disease-associated lncRNAs as potential biomarkers and therapeutic targets

Congcong Yan, Zicheng Zhang, Siqi Bao, Ping Hou, Meng Zhou, Chongyong Xu, Jie Sun
2020 Molecular Therapy: Nucleic Acids  
Identification of disease-associated lncRNAs is becoming increasingly crucial for fundamentally improving our understanding of molecular mechanisms of disease and developing novel biomarkers and therapeutic  ...  In this study, we first summarize data and knowledge resources publicly available for the study of lncRNA-disease associations.  ...  and QTJ18024).  ... 
doi:10.1016/j.omtn.2020.05.018 pmid:32585624 pmcid:PMC7321789 fatcat:qihynfkmgvhddjndjyc2svuscm

Microarray expression profiling and gene ontology analysis of long non-coding RNAs in spontaneously hypertensive rats and their potential roles in the pathogenesis of hypertension

LIANGLEI HOU, ZHENHAO LIN, YUNJIE NI, YIHAO WU, DEZHUN CHEN, LIJUAN SONG, XIAOYAN HUANG, HUANHUAN HU, DEYE YANG
2015 Molecular Medicine Reports  
Hypertension is a form of cardiovascular disease with at least one billion cases worldwide.  ...  Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed to predict the function of differentially expressed genes.  ...  Acknowledgements The present study was supported by the National Natural Science Foundation of China (grant no. 81270230) and Ministry of Health of the People's Republic of China Science Foundation (grant  ... 
doi:10.3892/mmr.2015.4554 pmid:26572900 fatcat:ujw4blsmm5dfvj5yk5dlug3gbm

Long Noncoding RNAs in Cardiac Development and Pathophysiology

N. Schonrock, R. P. Harvey, J. S. Mattick
2012 Circulation Research  
Until recently, it was thought that these regulatory networks are composed solely of protein-mediated transcriptional control and signaling systems; consequently, it was thought that cardiac disease involves  ...  gene regulation that may underpin heart adaptation and complex heart diseases.  ...  Unlike the well-studied miRNAs, lncRNAs do not seem to function via a common pathway; therefore, no predictions can be made about their function based on their primary sequence or secondary structure.  ... 
doi:10.1161/circresaha.112.268953 pmid:23104877 fatcat:nldfffhiafczbfstju2y6k6pc4

Construction and Analysis of Molecular Association Network by Combining Behavior Representation and Node Attributes

Hai-Cheng Yi, Zhu-Hong You, Zhen-Hao Guo
2019 Frontiers in Genetics  
diseases, in which various associations are interconnected and any type of associations can be predicted.  ...  A case study to predict miRNA-disease associations was also conducted to verify the prediction capability.  ...  Alaimo et al. (2014) proposed a tripartite network by associating ncRNA with disease through its targets (genes) based on recommended system technique.  ... 
doi:10.3389/fgene.2019.01106 pmid:31788002 pmcid:PMC6854842 fatcat:zsw6nrs2sjhgtee2yyzrajgwzi

Identifying lncRNA-Disease Relationships via Heterogeneous Clustering [chapter]

Emanuele Pio Barracchia, Gianvito Pio, Donato Malerba, Michelangelo Ceci
2018 Lecture Notes in Computer Science  
In this paper, we propose a computational approach, based on heterogeneous clustering, which is able to predict possibly unknown lncRNA-disease relationships by analyzing complex heterogeneous networks  ...  Our experimental evaluation, performed on a heterogeneous network consisting of microRNAs, lncRNAs, diseases, genes and their known relationships, shows that the proposed method is able to obtain better  ...  -612944) and TOREADOR -Trustworthy Model-aware Analytics Data Platform (Grant Number H2020-688797).  ... 
doi:10.1007/978-3-319-78680-3_3 fatcat:anjdwfkxhfej3e3rbumw5plmlm

Analysing miRNA-Target Gene Networks in Inflammatory Bowel Disease and Other Complex Diseases Using Transcriptomic Data

John P. Thomas, Marton Ölbei, Johanne Brooks-Warburton, Tamas Korcsmaros, Dezso Modos
2022 Genes  
We demonstrate through a case study example how to combine the resulting miRNA-target gene networks with transcriptomics data to find potential disease-specific miRNA regulators and miRNA-target genes  ...  This approach could help to identify miRNAs that may have important disease-modifying effects in IBD and other complex disorders, and facilitate the discovery of novel therapeutic targets.  ...  Acknowledgments: We are grateful for the help and advice of the Korcsmaros lab for their support. Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/genes13020370 pmid:35205414 pmcid:PMC8872053 fatcat:d7524kd3wvag5ebydjtfzyy57m

LDNFSGB: prediction of long non-coding rna and disease association using network feature similarity and gradient boosting

Yuan Zhang, Fei Ye, Dapeng Xiong, Xieping Gao
2020 BMC Bioinformatics  
In this paper, we develop a novel and effective method for the prediction of lncRNA-disease associations using network feature similarity and gradient boosting (LDNFSGB).  ...  Accurate prediction of lncRNA-disease associations can provide a new perspective for the diagnosis and treatment of diseases.  ...  [25] firstly constructed an updated tripartite network by integrating the miRNA-disease interaction network, miRNA-lncRNA interaction network, and lncRNA-disease network, and then predicted lncRNA-disease  ... 
doi:10.1186/s12859-020-03721-0 pmid:32883200 fatcat:mhs7f2ei4vbqtiks75mjhjfz64

Platforms for Investigating LncRNA Functions

John Lalith Charles Richard, Pieter Johan Adam Eichhorn
2018 SLAS TECHNOLOGY Translating Life Sciences Innovation  
Although still in its infancy, research into the biology of lncRNAs has demonstrated the importance of lncRNAs in development and disease.  ...  However, with the advent of next-generation sequencing, it has now been recognized that most complex eukaryotic genomes are in fact transcribed into noncoding RNAs (ncRNAs), including a family of transcripts  ...  2013 Sep-10 and T1-2014 Oct-08).  ... 
doi:10.1177/2472630318780639 pmid:29945466 fatcat:rzghd7mkjfbdljmpjvzn2kjjwi

Prediction of LncRNA-Disease Associations Based on Network Consistency Projection

Guanghui Li, Jiawei Luo, Cheng Liang, Qiu Xiao, Pingjian Ding, Yuejin Zhang
2019 IEEE Access  
The lncRNA-disease association probability matrix is calculated based on known lncRNA-disease associations and disease semantic similarity.  ...  In this paper, we present a novel network consistency projection for LncRNA-disease association prediction (NCPLDA) model by integrating the lncRNA-disease association probability matrix with the integrated  ...  [12] devised a new model based on a constructed bipartite network that relies on available disease-lncRNA network topological information. Yang et al.  ... 
doi:10.1109/access.2019.2914533 fatcat:7qao344jqzh5jibhjy5w4zlzp4

Long Non-coding RNAs: Mechanisms, Experimental, and Computational Approaches in Identification, Characterization, and Their Biomarker Potential in Cancer

Anshika Chowdhary, Venkata Satagopam, Reinhard Schneider
2021 Frontiers in Genetics  
We also illustrate the application of co-expression networks on the TCGA-LIHC dataset for putative functional predictions of lncRNAs having a therapeutic potential in Hepatocellular carcinoma (HCC).  ...  Dysregulation and genomic variations of several lncRNAs have been implicated in several diseases.  ...  predict lncRNA-disease links from a network of heterogenous lncRNAs and associated diseases based on their node interaction paths (Xiao et al., 2018) .  ... 
doi:10.3389/fgene.2021.649619 doaj:e24a384c23f94dfd82a6a0212a6f34aa fatcat:hzxn5mjydbbfdfob5ixoit6uxm

GBDTL2E: Predicting lncRNA-EF Associations Using Diffusion and HeteSim Features Based on a Heterogeneous Network

Jiaqi Wang, Zhufang Kuang, Zhihao Ma, Genwei Han
2020 Frontiers in Genetics  
learning algorithm GBDT to predict the association between lncRNAs and EFs based on heterogeneous networks.  ...  The innovation of the GBDTL2E integrates the structural information and heterogenous networks, combines the Hetesim features and the diffusion features based on multi-feature fusion, and uses the machine  ...  ACKNOWLEDGMENTS We would like to thank the Experimental Center of School of Computer and Information Engineering, Central South University of Forestry and Technology, for providing computing resources.  ... 
doi:10.3389/fgene.2020.00272 pmid:32351537 pmcid:PMC7174746 fatcat:t3sfguybbjgatcr4yklvmgpyqa

Predictive and prognostic molecular markers for cancer medicine

Sunali Mehta, Andrew Shelling, Anita Muthukaruppan, Annette Lasham, Cherie Blenkiron, George Laking, Cristin Print
2010 Therapeutic Advances in Medical Oncology  
While there are well-formed routes for translating new molecular information into drug therapy, the routes for translating new information into sensitive and specific diagnostic, prognostic and predictive  ...  This review will summarize the current technologies for predicting treatment response and prognosis in cancer medicine, and outline what the future may hold.  ...  Profiles based on simple mRNA quantification only capture part of the available information.  ... 
doi:10.1177/1758834009360519 pmid:21789130 pmcid:PMC3126011 fatcat:rmhgljyrtnf7tbmoe6stpytpz4

FPGA-based Design and Implementation of Real-time Robot Motion Planning

Ruige Li, Xiangcai Huang, Sijia Tian, Rong Hu, Dingxin He, Qiang Gu
2019 2019 9th International Conference on Information Science and Technology (ICIST)  
First, the correlated data source and experimentally validated information of diseases and lncRNAs are integrated to construct a heterogeneous bilayer network.  ...  Next, the integrated heterogeneous bilayer network can be formalized as a comprehensive adjacency matrix which includes lncRNA similarity matrix, disease similarity matrix, and disease-lncRNA association  ...  Additionally, the second minor branch is composed of network-based models, random walk and a variety of propagation algorithms implemented on a heterogeneous network to infer latent disease-lncRNA associations  ... 
doi:10.1109/icist.2019.8836825 fatcat:3w5o6uy5vfcp5k4s6eekfgc3tu

Inferring Latent Disease-lncRNA Associations by Faster Matrix Completion on a Heterogeneous Network

Wen Li, Shulin Wang, Junlin Xu, Guo Mao, Geng Tian, Jialiang Yang
2019 Frontiers in Genetics  
First, the correlated data source and experimentally validated information of diseases and lncRNAs are integrated to construct a heterogeneous bilayer network.  ...  Next, the integrated heterogeneous bilayer network can be formalized as a comprehensive adjacency matrix which includes lncRNA similarity matrix, disease similarity matrix, and disease-lncRNA association  ...  Additionally, the second minor branch is composed of network-based models, random walk and a variety of propagation algorithms implemented on a heterogeneous network to infer latent disease-lncRNA associations  ... 
doi:10.3389/fgene.2019.00769 pmid:31572428 pmcid:PMC6749816 fatcat:hkcy5puttvgf7bmvkyg6smxj64
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