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Mining Co-expression Graphs: Applications to MicroRNA Regulation and Disease Analysis

Malay Bhattacharyya, Malay Bhattacharyya
2012 Nature Precedings  
• Dense cores of autonomous systems in communication y networks -What about unweighted graphs?  ...  A, W n )}, is defined to be a graph for which becomes maximum  ...  Correspondence of a DBClique to an Interaction Matrix The Approach [15] The Approach Presented  ... 
doi:10.1038/npre.2012.7119 fatcat:evl57wk7dbhznceffuswwokc5y

Mining Co-expression Graphs: Applications to MicroRNA Regulation and Disease Analysis

Malay Bhattacharyya, Malay Bhattacharyya
2012 Nature Precedings  
• Dense cores of autonomous systems in communication y networks -What about unweighted graphs?  ...  A, W n )}, is defined to be a graph for which becomes maximum  ...  Correspondence of a DBClique to an Interaction Matrix The Approach [15] The Approach Presented  ... 
doi:10.1038/npre.2012.7119.1 fatcat:uprim75ukjhrpmci3fpg5u27ve

A statistically inferred microRNA network identifies breast cancer target miR-940 as an actin cytoskeleton regulator

Ricky Bhajun, Laurent Guyon, Amandine Pitaval, Eric Sulpice, Stéphanie Combe, Patricia Obeid, Vincent Haguet, Itebeddine Ghorbel, Christian Lajaunie, Xavier Gidrol
2015 Scientific Reports  
To fully appreciate centralities, we compared 3 graphs for 3 different meet/min thresholds (0.25, 0.5, 0.75) to a random network with 555 nodes and 2,911 edges 23 , a scale-free graph iterative construction  ...  The first graph was a random graph based on the Erdős-Rényi random graph construction algorithm 23 , where each edge has the same probability of appearance during construction.  ...  ., C.L. built the networks and performed the statistical analysis. A.P. performed the western blotting and immunofluorescence experiments. E.S., S.C. performed the transwell assays.  ... 
doi:10.1038/srep08336 pmid:25673565 pmcid:PMC5389139 fatcat:qbnti23mwbdfzmmuczii5iva5a

MicroRNA dysregulational synergistic network: discovering microRNA dysregulatory modules across subtypes in non-small cell lung cancers

Nhat Tran, Vinay Abhyankar, KyTai Nguyen, Jon Weidanz, Jean Gao
2018 BMC Bioinformatics  
Results: We proposed a pipeline to identify microRNA synergistic modules with similar dysregulation patterns across multiple subtypes by constructing the MicroRNA Dysregulational Synergistic Network.  ...  The majority of cancer-related deaths are due to lung cancer, and there is a need for reliable diagnostic biomarkers to predict stages in non-small cell lung cancer cases.  ...  Acknowledgements The authors thank the editor and the anonymous reviewers for their constructive comments to improve this work.  ... 
doi:10.1186/s12859-018-2536-0 fatcat:y72qwbd7tjgedm75k6bpt53xwu

Biocomputing and Synthetic Biology in Cells: Cells Special Issue

Feifei Cui, Quan Zou
2020 Cells  
[14] also proposes the prediction model for disease-microRNA associations, but they utilize the heterogeneous graph convolutional networks.  ...  [12] proposes a machine learning-based method for predicting disease-microRNA associations using network topology information.  ... 
doi:10.3390/cells9112459 pmid:33187277 fatcat:2zpyjpfyr5b6dkwfsgmxpeto7y

Identification of microRNA precursors based on random forest with network-level representation method of stem-loop structure

Jiamin Xiao, Xiaojing Tang, Yizhou Li, Zheng Fang, Daichuan Ma, Yangzhige He, Menglong Li
2011 BMC Bioinformatics  
Results: In the present work, a pre-miRNA stem-loop secondary structure is translated to a network, which provides a novel perspective for its structural analysis.  ...  Network parameters are used to construct prediction model, achieving an area under the receiver operating curves (AUC) value of 0.956.  ...  Acknowledgements We gratefully acknowledge all the anonymous reviewers for their constructive comments on this article.  ... 
doi:10.1186/1471-2105-12-165 pmid:21575268 pmcid:PMC3118167 fatcat:rl6dxrksdbd3fkzzdexaktcryu

Visual Data Mining of Biological Networks: One Size Does Not Fit All

Chiara Pastrello, David Otasek, Kristen Fortney, Giuseppe Agapito, Mario Cannataro, Elize Shirdel, Igor Jurisica, Fran Lewitter
2013 PLoS Computational Biology  
It is often useful to integrate these datasets using pathways and protein interaction networks to get a broader view of the experiment.  ...  The integration of such diverse data is necessary for the qualitative analysis of information relevant to hypotheses or discoveries.  ...  Introduction For a diverse set of biological problems, network visualization can be a powerful approach for data interpretation and analysis.  ... 
doi:10.1371/journal.pcbi.1002833 pmid:23341759 pmcid:PMC3547662 fatcat:6n5zpe6s6zbepdwybfdo3heqd4

A General Computational Framework for Prediction of Disease-associated Non-coding RNAs

Duc-Hau Le
2019 VNU Journal of Science Computer Science and Communication Engineering  
Therefore, in this study, we propose a general computational framework for prediction of disease-associated ncRNAs.  ...  This raises a pressing need to develop computational methods to associate diseases and ncRNAs.  ...  Acknowledgements Funding: This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.01-2017.14.  ... 
doi:10.25073/2588-1086/vnucsce.224 fatcat:6ivojgsgh5bonkasyseodx34fm

Detection of gene communities in multi-networks reveals cancer drivers

Laura Cantini, Enzo Medico, Santo Fortunato, Michele Caselle
2015 Scientific Reports  
communities a set of candidate driver cancer genes.  ...  The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks.  ...  and one of the four layers (co-expression network) is a complete graph.  ... 
doi:10.1038/srep17386 pmid:26639632 pmcid:PMC4671005 fatcat:4jjwqktj5nhklhqkr6xqulkcwu

MicroRNA-derived network analysis of differentially methylated genes in schizophrenia, implicating GABA receptor B1 [GABBR1] and protein kinase B [AKT1]

Vadim Gumerov, Hedi Hegyi
2015 Biology Direct  
form a small-world network.  ...  Conclusions: We find that GABBR1 has a central importance in schizophrenia, even if no direct cause and effect have been shown for it for the time.  ...  To see if the network has small-world property, we constructed random graphs using the Erdős-Rényi algorithm with the same number of nodes and the same average number of edges for each node.  ... 
doi:10.1186/s13062-015-0089-y pmid:26450699 pmcid:PMC4598960 fatcat:ibghtzy4svc6nj33jzp3pw3nyi

Visualization of Functional Aspects of microRNA Regulatory Networks Using the Gene Ontology [chapter]

Alkiviadis Symeonidis, Ioannis G. Tollis, Martin Reczko
2006 Lecture Notes in Computer Science  
The post-transcriptional regulation of genes by microRNAs (miRNAs) is a recently discovered mechanism of growing importance.  ...  Executables for MS-Windows are available under  ...  The GO hierarchical construction guarantees the absence of cycles in the graph. Thus, the GO hierarchy is a Directed Acyclic Graph (DAG).  ... 
doi:10.1007/11946465_2 fatcat:azcx5ufdqrc7tl44c6vtsjbgsy

Construction of competitive endogenous RNA network reveals regulatory role of long non-coding RNAs in type 2 diabetes mellitus

Zijing Lin, Xinyu Li, Xiaorong Zhan, Lijie Sun, Jie Gao, Yan Cao, Hui Qiu
2017 Journal of Cellular and Molecular Medicine  
Here, we constructed a T2DM-related competitive endogenous RNA (ceRNA) network (DMCN) to explore biological function of lncRNAs during the development of diabetes mellitus.  ...  This network contained 351 nodes including 98 mRNAs, 86 microRNAs and 167 lncRNAs. Functional analysis showed that the mRNAs in DMCN were annotated into some diabetes-related pathways.  ...  It can be defined as follows: Deg (i) = K For a graph G: = (V,E) with n nodes, the betweenness B i stands for a node i as B i ¼ 1 ðn À 1Þðn À 2Þ X s6 ¼i6 ¼t S st ðiÞ S st where S st is the number of shortest  ... 
doi:10.1111/jcmm.13224 pmid:28643459 pmcid:PMC5706502 fatcat:v2beb73ujvciplldecpj7h2jji

Preprocessing and analyzing genetic data with complex networks: An application to Obstructive Nephropathy

Massimiliano Zanin, Ernestina Menasalvas, Pedro A. C. Sousa, Stefano Boccaletti
2012 Networks and Heterogeneous Media  
Many diseases have a genetic origin, and a great effort is being made to detect the genes that are responsible for their insurgence.  ...  Yet, a practical problem of this approach is its computational cost, which scales as the square of the number of features included in the initial dataset.  ...  Example of the construction of a fictitious network.  ... 
doi:10.3934/nhm.2012.7.473 fatcat:fstvjamguzaa5krothth5g77w4

CIDeR: multifactorial interaction networks in human diseases

Martin Lechner, Veit Höhn, Barbara Brauner, Irmtraud Dunger, Gisela Fobo, Goar Frishman, Corinna Montrone, Gabi Kastenmüller, Brigitte Waegele, Andreas Ruepp
2012 Genome Biology  
Systematic annotation and interactive graphical representation of disease networks make CIDeR a versatile knowledge base for biologists, analysis of large-scale data and systems biology approaches.  ...  The pathobiology of common diseases is influenced by heterogeneous factors interacting in complex networks.  ...  The first step in modeling is construction of a qualitative network describing the mode of interaction between the components of a network.  ... 
doi:10.1186/gb-2012-13-7-r62 pmid:22809392 pmcid:PMC3491383 fatcat:okq7fid6l5hsxpzod6b3nozwce

A Method of Biomedical Knowledge Discovery by Literature Mining Based on SPO Predications: A Case Study of Induced Pluripotent Stem Cells [chapter]

Zheng-Yin Hu, Rong-Qiang Zeng, Xiao-Chu Qin, Ling Wei, Zhiqiang Zhang
2018 Lecture Notes in Computer Science  
In order to identify the previously unknown biomedical knowledge from these resources, we propose a new method of knowledge discovery based on SPO predications, which constructs a three-level SPO-semantic  ...  relation network in the considered area.  ...  First, we present an introduction to the SPO-based semantic relation network. Then, we construct a three-level graph, which is different from the graph generated by the NetMiner.  ... 
doi:10.1007/978-3-319-96133-0_29 fatcat:gvxslu77v5ci3hqyxgj37sxwhu
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