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CNEReg Interprets Ruminant-specific Conserved Non-coding Elements by Developmental gene regulatory network

Genomics, Proteomics & Bioinformatics 2023年第3期21卷 632-648页

作者： Xiangyu Pan Zhaoxia Ma Xinqi Sun Hui Li Tingting Zhang Chen Zhao Nini Wang Rasmus Heller Wing Hung Wong Wen Wang Yu Jiang Yong Wang Key Laboratory of Animal genetics Breeding and Reproduction of Shaanxi ProvinceCollege of Animal Science and TechnologyNorthwest A&F UniversityYangling 712100China Department of Medical Research Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Guangdong Cardiovascular Institute Guangdong Provincial People’s HospitalGuangdong Academy of Medical SciencesGuangzhou 510080China Academy of Mathematics and Systems Science Chinese Academy of SciencesBeijing 100190China School of Mathematics University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory for Conservation and Utilization of Subtropical Agro-Bioresources College of Animal Science and TechnologyGuangxi UniversityNanning 530005China Section for Computational and RNA Biology Department of BiologyUniversity of CopenhagenCopenhagen DK-2100Denmark Department of Statistics Department of Biomedical Data ScienceBio-X ProgramStanford UniversityStanfordCA 94305USA Center for Ecological and Environmental Sciences Northwestern Polytechnical UniversityXi’an 710072China State Key Laboratory of genetic Resources and Evolution Kunming Institute of ZoologyChinese Academy of SciencesKunming 650223China Center for Excellence in Animal Evolution and genetics Chinese Academy of SciencesKunming 650223China Key Laboratory of Systems Health Science of Zhejiang Province School of Life ScienceHangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

The genetic information coded in DNA leads to trait innovation via a gene regulatory network(GRN)in ***,we developed a conserved non-coding element interpretation method to integrate multi-omics data into gene regulatory network(CNEReg)to investigate the ruminant multi-chambered stomach *** generated paired expression and chromatin accessibility data during rumen and esophagus development in sheep,and revealed 1601 active ruminantspecific conserved non-coding elements(active-RSCNEs).To interpret the function of these activeRSCNEs,we defined toolkit transcription factors(TTFs)and modeled their regulation on rumenspecific genes via batteries of active-RSCNEs during *** developmental GRN revealed 18 TTFs and 313 active-RSCNEs regulating 7 rumen functional ***,6 TTFs(OTX1,SOX21,HOXC8,SOX2,TP63,and PPARG),as well as 16 active-RSCNEs,functionally distinguished the rumen from the *** study provides a systematic approach to understanding how gene regulation evolves and shapes complex traits by putting evo-devo concepts into practice with developmental multi-omics data.

关键词： Trait innovation gene regulatory network Conserved non-coding element Toolkit transcription factor Ruminant

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Single-cell gene regulatory network analysis for mixed cell populations

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Quantitative Biology 2024年第4期12卷 375-388页

作者： Junjie Tang Changhu Wang Feiyi Xiao Ruibin Xi School of Mathematical Sciences and Center of Statistical Science Peking UniversityBeijingChina Academy for Advanced Interdisciplinary Studies Peking UniversityBeijingChina

gene regulatory network(GRN)refers to the complex network formed by regulatory interactions between genes in living *** this paper,we consider inferring GRNs in single cells based on single-cell RNA sequencing(scRNA-seq)*** scRNA-seq,single cells are often profiled from mixed populations,and their cell identities are unknown.A common practice for single-cell GRN analysis is to first cluster the cells and infer GRNs for every cluster ***,this two-step procedure ignores uncertainty in the clustering step and thus could lead to inaccurate estimation of the ***,we consider the mixture Poisson lognormal model(MPLN)for network inference of count data from mixed *** precision matrices of the MPLN are the GRNs of different cell *** avoid the intractable optimization of the MPLN’s log-likelihood,we develop an algorithm called variational mixture Poisson log-normal(VMPLN)to jointly estimate the GRNs of different cell types based on the variational inference *** compare VMPLN with state-of-the-art single-cell regulatory network inference *** simulation shows that VMPLN achieves better performance,especially in scenarios where different cell types have a high mixing *** on real scRNA-seq data also demonstrates that VMPLN can provide more accurate network estimation in most ***,we apply VMPLN to a large scRNA-seq dataset from patients infected with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)and find that VMPLN identifies critical differences in regulatory networks in immune cells between patients with moderate and severe *** source codes are available on the GitHub website(***/XiDsLab/SCVMPLN).

关键词： gene regulatory network graphical model precision matrix variational inference single-cell RNA sequencing

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Research of gene regulatory network with Multi-Time Delay Based on Bayesian network

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Journal of Northeast Agricultural University(English Edition) 2008年第2期15卷 61-64页

作者： LIU Bei MENG Fanjiang LI Yong LIULiyan Engineering College Northeast Agricultural University Harbin 150030 China

The gene regulatory network was reconstructed according to time-series microarray data getting from hybridization at different time between gene chips to analyze coordination and restriction between genes. An algorithm for controlling the gene expression regulatory network of the whole cell was designed using Bayesian network which provides an effective aided analysis for gene regulatory network.

关键词： gene regulatory network Bayesian network CPT DAG

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An Integrated gene regulatory network Inference Pipeline

An Integrated Gene Regulatory Network Inference Pipeline

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第三十届中国控制会议

作者： HORIMOTO Katsuhisa Computational Biology Research Center（CBRC） National Institute of Advanced Industrial Science and Technology（AIST）Tokyo135-0064Japan

＜正＞Rapidly accumulated gene expression data put forward the development of numerous methods for inferring gene regulatory networks and the efforts for critical performance assessment of these *** this paper,we propose an integrated pipeline for gene regulatory network inference motivated by the results and follow-up analysis of a blinded,community-wide challenge DREAM（Dialogue on Reverse Engineering Assessment and Methods） *** particular,we categorize the gene expression data into three types,i.e.,steady-state gene expression profile of knockout or knockdown experiments,steady-state gene expression profiles after multi-factorial perturbations,and time-series data after multi-factorial *** we analyze the three types of gene expression data by using the combination of fold change and t-test,the path consistency algorithm based on conditional mutual information,and the ordinary differential equation model,*** we integrate the three procedures to a pipeline for gene regulatory network inference by considering their complementarities. Performance for the network inference will be improved in the proposed pipeline by maximally utilizing information in the available data,emphasizing the knock-out and knock-down data,and differentiating the direct and indirect regulatory interactions.

关键词： gene regulatory network Reverse engineering Knock out Steady state Time series

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Impulsive Synchronization of Fractional-order Delayed gene regulatory network Based on Comparative System Method

Impulsive Synchronization of Fractional-order Delayed Gene R...

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第三十九届中国控制会议

作者： Feng Liu Shaoqiang Ye Shiqi Zheng Hua O Wang School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Mechanical Engineering Boston University

In this paper, we study the fractional-order delayed gene regulatory network based on the comparative system ***, we introduced the concept of fractional differential. We use Lyapunov direct method to prove the impulsive synchronization. For the oscillation behavior of a fractional-order system with time delay, we apply the pulse to control its synchronization. Finally, we verify the correctness of our theory through experiment.

关键词： Comparison system impulsive synchronization time delay fractional order gene regulatory network

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Stability and bifurcation of delayed gene regulatory network with self-feedback,positive feedback and negative feedback

Stability and bifurcation of delayed gene regulatory network...

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第37届中国控制会议

作者： LAI Qiang CHEN Qian School of Electrical and Automation Engineering East China Jiaotong University

This letter investigates the stability and bifurcation of delayed gene regulatory network with self-feedback,positive feedback and negative *** stability condition of the network without time delays is *** establishment of the existence condition of Hopf bifurcation of the network is given by considering its characteristic *** the variation of the time delays,the network appears Hopf bifurcation and loses its stability which is theoretically and numerically *** bistability of the network is also numerically presented.

关键词： gene regulatory network Self-feedback Positive feedback Time delay Bifurcation Stability

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Special Issue on “gene regulatory network”

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Genomics, Proteomics & Bioinformatics 2012年第4期10卷 I0003-I0003页

The journal Genomics Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published around April 2013） on the topic of ＂gene regulatory network＂.

关键词： Special Issue on gene regulatory network GRN

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Special Issue on “gene regulatory network”

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Genomics,Proteomics & Bioinformatics 2012年第4期 239-239页

The journal Genomics Proteomics & Bioinformatics(GPB) is now inviting submissions for a special issue(to be published around April 2013) on the topic of "gene regulatory network". The gene regulatory network(GRN) is a... 详细信息

关键词： gene regulatory network GRN Special Issue on

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Special Issue on "gene regulatory network"

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Genomics,Proteomics & Bioinformatics 2012年第3期 174-174页

The journal Genomics Proteomics & Bioinformatics(GPB) is now inviting submissions for a special issue(to be published around April 2013) on the topic of "gene regulatory network".

关键词： Special Issue on gene regulatory network

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Special Issue on “gene regulatory network”

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Genomics, Proteomics & Bioinformatics 2012年第2期10卷 I0001-I0001页

The journal Genomics Proteomics ＆ Bioinformatics （GPB） is now inviting submissions for a special issue （to be published around April 2013） on the topic of ＂gene regulatory network＂

关键词： Special Issue on gene regulatory network

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