Suchergebnisse - Gene co-expression network inference algorithms

The Performance Comparison of Gene Co-expression Networks of Breast and Prostate Cancer using Different Selection Criteria von Cingiz, Mustafa Özgür, Biricik, Göksel, Diri, Banu

“… Gene co-expression networks (GCN) present undirected relations between genes to understand molecular structures behind the diseases, including cancer …”
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The inference of gene co-expression networks of breast and colon cancer using miRNA-target gene interactions data von Cingiz, Mustafa Ozgur, Diri, Banu

“… Popular information theory based gene network inference algorithms are utilized to infer gene co-expression networks …”
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NetMiner-an ensemble pipeline for building genome-wide and high-quality gene co-expression network using massive-scale RNA-seq samples von Yu, Hua, Jiao, Bingke, Lu, Lu, Wang, Pengfei, Chen, Shuangcheng, Liang, Chengzhi, Liu, Wei

“… Accurately reconstructing gene co-expression network is of great importance for uncovering the genetic architecture underlying complex and various phenotypes …”
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Ensemble and Greedy Approach for the Reconstruction of Large Gene Co-Expression Networks von Gómez-Vela, Francisco, Delgado-Chaves, Fernando M., Rodríguez-Baena, Domingo S., García-Torres, Miguel, Divina, Federico

“… Gene networks have become a powerful tool in the comprehensive analysis of gene expression …”
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Intrinsic-overlapping co-expression module detection with application to Alzheimer's Disease von Manners, Hazel Nicolette, Roy, Swarup, Kalita, Jugal K.

“… •A new density-based algorithm called CluViaN is proposed that can detect intrinsic as well as overlapping modules from gene co-expression network …”
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k- Strong Inference Algorithm: A Hybrid Information Theory Based Gene Network Inference Algorithm von Cingiz, Mustafa Özgür

“… Numerous gene network inference (GNI) algorithms have been presented in the literature to infer accurate gene networks …”
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Inference of Gene Regulatory Network from Single-Cell Transcriptomic Data Using pySCENIC von Kumar, Nilesh, Mishra, Bharat, Athar, Mohammad, Mukhtar, Shahid

“… The gene regulatory network (GRN) mainly consists of genes and their regulators-transcription factors (TF …”
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Condition-adaptive fused graphical lasso (CFGL): An adaptive procedure for inferring condition-specific gene co-expression network von Lyu, Yafei, Xue, Lingzhou, Zhang, Feipeng, Koch, Hillary, Saba, Laura, Kechris, Katerina, Li, Qunhua

“… Co-expression network analysis provides useful information for studying gene regulation in biological processes …”
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lionessR: single sample network inference in R von Kuijjer, Marieke L, Hsieh, Ping-Han, Quackenbush, John, Glass, Kimberly

“… Background In biomedical research, network inference algorithms are typically used to infer complex association patterns between biological entities, such as between genes or proteins, using data from a population …”
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Evaluation and improvement of the regulatory inference for large co-expression networks with limited sample size von Guo, Wenbin, Calixto, Cristiane P. G., Tzioutziou, Nikoleta, Lin, Ping, Waugh, Robbie, Brown, John W. S., Zhang, Runxuan

“… Evaluation studies on co-expression network analysis methods mostly focus on networks of small or medium size of up to a few hundred nodes …”
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Computational Inference of Gene Co-Expression Networks for the identification of Lung Carcinoma Biomarkers: An Ensemble Approach von Delgado-Chaves, Fernando M., Gómez-Vela, Francisco, García-Torres, Miguel, Divina, Federico, Vázquez Noguera, José Luis

“… In this work, we present an application of gene co-expression networks in the modelling of lung cancer gene regulatory networks, which ultimately served to the discovery of new biomarkers …”
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Addressing confounding artifacts in reconstruction of gene co-expression networks von Parsana, Princy, Ruberman, Claire, Jaffe, Andrew E., Schatz, Michael C., Battle, Alexis, Leek, Jeffrey T.

“… Gene co-expression networks capture biological relationships between genes and are important tools in predicting gene function and understanding disease mechanisms …”
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Computational Ensemble Gene Co-Expression Networks for the Analysis of Cancer Biomarkers von Figueroa-Martínez, Julia, Saz-Navarro, Dulcenombre M., López-Fernández, Aurelio, Rodríguez-Baena, Domingo S., Gómez-Vela, Francisco A.

“… Thanks to these networks generated by means of inference algorithms, it is possible to study different biological processes and even identify new biomarkers for such diseases …”
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Genetic network inference: from co-expression clustering to reverse engineering von D’haeseleer, Patrik, Liang, Shoudan, Somogyi, Roland

“… In particular, using high-throughput gene expression assays, we are able to measure the output of the gene regulatory network …”
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Sharing and Specificity of Co-expression Networks across 35 Human Tissues von Pierson, Emma, Koller, Daphne, Battle, Alexis, Mostafavi, Sara

“… To address this problem, we infer tissue-specific gene co-expression networks for 35 tissues in the GTEx dataset using a novel algorithm, GNAT, that uses a hierarchy of tissues to share data between related tissues …”
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Estimation of the proteomic cancer co-expression sub networks by using association estimators von Yamanishi, Yoshihiro, Erdoğan, Cihat, Kurt, Zeyneb, Diri, Banu

“… In this study, the association estimators, which have significant influences on the gene network inference methods and used for determining the molecular interactions, were examined within the co …”
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Library size-stabilized metacells construction enhances co-expression network analysis in single-cell data von Zhang, Tianjiao, Zhu, Haibin

“… Single-cell RNA sequencing (scRNA-seq) deciphers cell type-specific co-expression networks to resolve biological functions but remains constrained by data sparsity and compositional biases …”
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Comparison of co-expression measures: mutual information, correlation, and model based indices von Song, Lin, Langfelder, Peter, Horvath, Steve

“… Background Co-expression measures are often used to define networks among genes. Mutual information (MI …”
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Gene Regulatory Network Inference Using Convolutional Neural Networks from scRNA-seq Data von Mao, Guo, Pang, Zhengbin, Zuo, Ke, Liu, Jie

“… In this article, we propose a novel supervised convolutional neural network (CNNSE), which can extract gene expression information from 2D co-expression matrices of gene doublets and identify interactions between genes …”
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Two-tier combinatorial structure to integrate various gene co-expression networks of prostate cancer von Cingiz, Mustafa Özgür, Diri, Banu

“… In this study, we present a two-tiered combinatorial structure (TTCS) to integrate gene co-expression networks (GCNs …”
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