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A scalable algorithm for structure identification of complex gene regulatory network from temporal expression data

Shupeng Gui, Andrew P. Rice, Rui Chen, Liang Wu, Ji Liu, Hongyu Miao
2017 BMC Bioinformatics  
Result: We present a novel scalable algorithm for identifying genome-wide regulatory network structures.  ...  However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes from temporal gene expression data, especially for complex eukaryotes like human.  ...  Availability of data and materials All the data sets used in this study are from public databases, including RegNetwork, GEO, and ENCODE.  ... 
doi:10.1186/s12859-017-1489-z pmid:28143596 pmcid:PMC5294888 fatcat:knwvke4mibfx5o3qvoz2csfzam

A Scalable Algorithm for Structure Identification of Complex Gene Regulatory Network from Temporal Expression Data [article]

Shupeng Gui, Rui Chen, Liang Wu, Ji Liu, Hongyu Miao
2016 bioRxiv   pre-print
Result: We present a novel scalable algorithm for identifying genome-wide regulatory network structures.  ...  However, only a few previous computational studies have claimed success in revealing genome-wide regulatory landscapes from temporal gene expression data, especially for complex eukaryotes like human.  ...  Hulin Wu (UTSPH) for developing the RegNetwork database. We also thank Dr. Andrew P. Rice (BCM) for constructive feedbacks.  ... 
doi:10.1101/073296 fatcat:ady5d44zdfanbd5oqlhgw5t4em

Stable Gene Regulatory Network Modeling From Steady-State Data

Joy Larvie, Mohammad Sefidmazgi, Abdollah Homaifar, Scott Harrison, Ali Karimoddini, Anthony Guiseppi-Elie
2016 Bioengineering  
The identification algorithm proposed is applicable for the identification of regulatory roles of individual genes and control genes in the network.  ...  In most applications, the regulatory network structure is unknown, and has to be reverse engineered from experimental data consisting of expression levels of the genes usually measured as messenger RNA  ...  Acknowledgments: The authors wish to acknowledge Michael Zavlanos for making the source codes to his genetic network identification algorithm available.  ... 
doi:10.3390/bioengineering3020012 pmid:28952574 pmcid:PMC5597136 fatcat:6ybul52o2jeunagb4r2cdrf4i4

A parallel approach for accelerated parameter identification of Gene Regulatory Networks

Tariq Saeed, Jamil Ahmad
2014 International Work-Conference on Bioinformatics and Biomedical Engineering  
Model Checking is one of the formal verification methods which can be used to infer parameters of a Gene Regulatory Network (GRN) using discrete formalism of René Thomas.  ...  However, the sequential approach for identification of these logical parameters is computationally intensive and takes lot of processing time, depending on number of genes and range of their expression  ...  As the complexity of these networks increase, efficient computational methods are required not only to infer network information from gene expression data, but also to gain insight into regulatory mechanisms  ... 
dblp:conf/iwbbio/SaeedA14 fatcat:ymrgxtq4sfedjgbvgmli3oifau

Survey on Modelling Methods Applicable to Gene Regulatory Network [article]

Chanda Panse, Dr. Manali Kshirsagar
2013 arXiv   pre-print
Gene Regulatory Network (GRN) plays an important role in knowing insight of cellular life cycle.  ...  For inference of GRN, time series data provided by Microarray technology is used.  ...  From the observation of pattern of gene expressions a new model is proposed in [12] .  ... 
arXiv:1310.2361v1 fatcat:hcg4qetvgrdcrg6tadhpxjk3ze

Hybrid Modeling and Simulation of Genetic Regulatory Networks: A Qualitative Approach [chapter]

Hidde de Jong, Jean-Luc Gouzé, Céline Hernandez, Michel Page, Tewfik Sari, Johannes Geiselmann
2003 Lecture Notes in Computer Science  
This has incited an increasingly large group of researchers to turn from the structure to the behavior of genetic regulatory networks, against the background of a broader movement nowadays often referred  ...  The functioning and development of living organisms is controlled by large and complex networks of genes, proteins, small molecules, and their interactions, so-called genetic regulatory networks.  ...  Along these lines, we have started to work on the identification of PADE models of genetic regulatory network from time-course gene expression data.  ... 
doi:10.1007/3-540-36580-x_21 fatcat:4jw7dloz5nhbng3nl3ngcxafim

A Survey of Graph Mining Techniques for Biological Datasets [chapter]

S. Parthasarathy, S. Tatikonda, D. Ucar
2010 Managing and Mining Graph Data  
The field of bioinformatics has emerged as important application area in this context. Examples abound ranging from the analysis of protein interaction networks to the analysis of phylogenetic data.  ...  We conclude this article with a discussion of the key results and identify some interesting directions for future research.  ...  Acknowledgments The authors wish to acknowledge the support of NSF CAREER Grant IIS-0347662.  ... 
doi:10.1007/978-1-4419-6045-0_18 dblp:series/ads/ParthasarathyTU10 fatcat:aeu53r3dbzd67d5whkjypv64uq

Network Inference in Systems Biology: Recent Developments, Challenges, and Applications [article]

Michael M. Saint-Antoine, Abhyudai Singh
2019 arXiv   pre-print
One of the most interesting, difficult, and potentially useful topics in computational biology is the inference of gene regulatory networks (GRNs) from expression data.  ...  We also discuss unsolved computational challenges, including the optimal combination of algorithms, integration of multiple data sources, and pseudo-temporal ordering of static expression data.  ...  Here, analysis of gene expression data from the species in question is combined with analysis of gene expression data from homologous species.  ... 
arXiv:1911.04046v1 fatcat:qvccpyxkszh7le3deljvggabim

Regulatory Snapshots: Integrative Mining of Regulatory Modules from Expression Time Series and Regulatory Networks

Joana P. Gonçalves, Ricardo S. Aires, Alexandre P. Francisco, Sara C. Madeira, Peter Csermely
2012 PLoS ONE  
Personalized ranking is then applied to prioritize prominent regulators targeting the modules at each time point using a network of documented regulatory associations and the expression data.  ...  Temporal biclustering is first used to reveal transcriptional modules composed of genes showing coherent expression profiles over time.  ...  Analyzed the data: JPG. Contributed reagents/ materials/analysis tools: RSA APF SCM. Wrote the paper: JPG.  ... 
doi:10.1371/journal.pone.0035977 pmid:22563474 pmcid:PMC3341384 fatcat:t2h4sblp6vhjtb6of4indyr4bu

Feature selection revisited in the single-cell era

Pengyi Yang, Hao Huang, Chunlei Liu
2021 Genome Biology  
We review their application to a range of single-cell data types generated from traditional cytometry and imaging technologies and the latest array of single-cell omics technologies.  ...  AbstractRecent advances in single-cell biotechnologies have resulted in high-dimensional datasets with increased complexity, making feature selection an essential technique for single-cell data analysis  ...  Acknowledgements The authors thank the feedback from the members of the Sydney Precision Bioinformatics Alliance.  ... 
doi:10.1186/s13059-021-02544-3 pmid:34847932 pmcid:PMC8638336 fatcat:u62n34lpgzh43mu7mszwm63ls4

Inferring Gene Regulatory Network from Bayesian Network Model Based on Re-sampling

Qiang Zhang, Xuedong Zheng, Qiang Zhang, Changjun Zhou
2013 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
For such cases, it is difficult to learn network structure from such data. And the result is not ideal. So it needs to take measures to expand the capacity of the sample.  ...  But the time-series expression data present a phenomenon that the number of genes is in thousands and the number of experimental data is only a few dozen.  ...  Acknowledgement This work is supported by the National Natural Science Foundation of China  ... 
doi:10.12928/telkomnika.v11i1.769 fatcat:eihzcjij6zemlo6pl3w22jc6oa

Inferring Gene Regulatory Network from Bayesian Network Model Based on Re-Sampling

Qian Zhang, Xuedong Zheng, Qiang Zhang, Changjun Zhou
2013 TELKOMNIKA (Telecommunication Computing Electronics and Control)  
For such cases, it is difficult to learn network structure from such data. And the result is not ideal. So it needs to take measures to expand the capacity of the sample.  ...  But the time-series expression data present a phenomenon that the number of genes is in thousands and the number of experimental data is only a few dozen.  ...  Acknowledgement This work is supported by the National Natural Science Foundation of China  ... 
doi:10.12928/telkomnika.v11i1.907 fatcat:zuv5mydocfaztabb4kb2dfrc6i

Feature selection revisited in the single-cell era [article]

Pengyi Yang, Hao Huang, Chunlei Liu
2021 arXiv   pre-print
We review their versatile application to a range of single-cell data types including those generated from traditional cytometry and imaging technologies and the latest array of single-cell omics technologies  ...  Feature selection techniques are essential for high-dimensional data analysis.  ...  Acknowledgements The authors thank the feedback from the members of Sydney Precision Bioinformatics Alliance.  ... 
arXiv:2110.14329v1 fatcat:fvliiws52ramrhyz53ijdlt73u

2020 Index IEEE/ACM Transactions on Computational Biology and Bioinformatics Vol. 17

2021 IEEE/ACM Transactions on Computational Biology & Bioinformatics  
., +, TCBB March-April 2020 704-711 Pancreas Data-Driven Robust Control for a Closed-Loop Artificial Pancreas. 1981 -1993  ...  P Pain Classification of Patients with Coronary Microvascular Dysfunction.  ...  -Dec. 2020 2005-2016 Multi-Domain Networks Association for Biological Data Using Block Identification of Minimum Set of Master Regulatory Genes in Gene Regulatory Networks.  ... 
doi:10.1109/tcbb.2020.3047571 fatcat:x3kmrpexsve6bnjtd3dh6ntkyy

Molecular Network Analysis and Applications [chapter]

Minlu Zhang, Jingyuan Deng, Chunsheng V. Fang, Xiao Zhang, Long Jason Lu
2010 Knowledge-Based Bioinformatics  
having a specific regulatory pattern in controlling gene expression ( Figure 11 .3 (a)).  ...  The input of the module extraction methods can be a homogeneous molecular network, or a network integrated with other genomic data such as gene expression.  ... 
doi:10.1002/9780470669716.ch11 fatcat:dutvoyqsnbcgndejl2fpvo4o6a
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