The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the g...The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function (transitions and outputs) of the cellular automata as models for the intracellular governing gene/epigene networks.展开更多
This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology ...This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology for solving the nonlinear partial differential equations, namely the Hamilton-Jacobi-Bellman and Hamilton-Jacobi-Isaacs equations through successive Galerkin’s approximation is implemented and the results are compared. Throughout the implementation, there were several caveats that need to be further resolved for practical applications in general cases. Such issues and the clarification of causes are mathematically established and reviewed.展开更多
The plant genome produces an extremely large collection of long noncoding RNAs(lncRNAs)that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes.Her...The plant genome produces an extremely large collection of long noncoding RNAs(lncRNAs)that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes.Here,we mapped the transcriptional heterogeneity of lncRNAs and their associated gene reg-ulatory networks at single-cell resolution.We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing(scRNA-seq)datasets from juvenile Arabidopsis seedlings.We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers.We further demon-strated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity.In addi-tion,we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs,and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs.The analysis results are available at the single-cell-based plant lncRNA atlas data-base(scPLAD;https://biobigdata.nju.edu.cn/scPLAD/).Overall,this work demonstrates the power of inte-grative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.展开更多
The complexity of unknown scenarios and the dynamics involved in target entrapment make designing control strategies for swarm robots a formidable task,which in turn impacts their efficiency in complex and dynamic set...The complexity of unknown scenarios and the dynamics involved in target entrapment make designing control strategies for swarm robots a formidable task,which in turn impacts their efficiency in complex and dynamic settings.To address these challenges,this paper introduces an adaptive swarm robot entrapment control model grounded in the transformation of gene regulatory networks(AT-GRN).This innovative model enables swarm robots to dynamically adjust entrap-ment strategies by assessing current environmental conditions via real-time sensory data.Further-more,an improved motion control model for swarm robots is designed to dynamically shape the for-mation generated by the AT-GRN.Through two sets of rigorous experimental environments,the proposed model significantly enhances the trapping performance of swarm robots in complex envi-ronments,demonstrating remarkable adaptability and stability.展开更多
Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is s...Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).展开更多
This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regul...This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.展开更多
The vegetative development of cabbage(Brassica oleracea var.capitata)passes through seedling,rosette,folding and heading stages.Leaves that form the rosette are large and mostly flat.In the following developmental sta...The vegetative development of cabbage(Brassica oleracea var.capitata)passes through seedling,rosette,folding and heading stages.Leaves that form the rosette are large and mostly flat.In the following developmental stages,the plants produce leaves that curve inward to produce the leafy head.Many microRNAs and their target genes have been described participating in leaf development and leaf curvature.The aim of this study is to investigate the role of miRNA-regulated genes in the transition from the rosette to the heading stage.We compared the mi RNA and gene abundances between emerging rosette and heading leaves.To remove transcripts(miRNAs and genes)whose regulation was most likely associated with plant age rather than the change from rosette to heading stage,we utilized a non-heading collard green(B.oleracea var.acephala)morphotype as control.This resulted in 33 DEMs and 1998 DEGs with likely roles in the transition from rosette to heading stage in cabbage.Among these 1998 DEGs,we found enriched GO terms related to DNA-binding transcription factor activity,transcription regulator activity,iron ion binding,and photosynthesis.We predicted the target genes of these 33 DEMs and focused on the subset that was differentially expressed(1998DEGs)between rosette and heading stage leaves to construct mi RNA-target gene interaction networks.Our main finding is a role for miR396b-5p targeting two Arabidopsis thaliana orthologues of GROWTH REGULATING FACTORs 3(GRF3)and 4(GRF4)in pointed cabbage head formation.展开更多
Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five differ...Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.展开更多
The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis...The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis was performed on the crested tissues of 6 Chinese crested ducks and the scalp tissues of 6 cherry valley ducks(CVs)from 2 developmental stages.This study identified 261 differentially expressed genes(DEGs),122 upregulated and 139 downregulated,in the E28 stage and 361 DEGs,154 upregulated and 207 downregulated in the D42 stage between CC and CV ducks.The subsequent results of weighted gene co-expression network analysis(WGCNA)revealed that the turquoise and cyan modules were associated with the crest trait in the D42 stage,meanwhile,the green,brown,and pink modules were associated with the crest trait in the E28 stage.Venn analysis of the DEGs and WGCNA showed that 145 and 45 genes are associated between the D42 and E28 stages,respectively.The expression of WNT16,BMP2,SLC35F2,SLC6A15,APOBEC2,ABHD6,TNNC2,MYL1,and TNNI2 were verified by real-time quantitative PCR.This study provides an approach to reveal the molecular mechanisms underlying the crested trait development.展开更多
Background:Pancreatic ductal adenocarcinoma(PDAC)has a rich and complex tumor immune microenvironment(TIME).M2 macrophages are among the most extensively infiltrated immune cells in the TIME and are necessary for the g...Background:Pancreatic ductal adenocarcinoma(PDAC)has a rich and complex tumor immune microenvironment(TIME).M2 macrophages are among the most extensively infiltrated immune cells in the TIME and are necessary for the growth and migration of cancers.However,the mechanisms and targets mediating M2 macrophage infiltration in pancreatic cancer remain elusive.Methods:The M2 macrophage infiltration score of patients was assessed using the xCell algorithm.Using weighted gene co-expression network analysis(WGCNA),module genes associated with M2 macrophages were identified,and a predictive model was designed.The variations in immunological cell patterns,cancer mutations,and enrichment pathways between the cohorts with the high-and low-risk were examined.Additionally,the expression of FCGR3A and RNASE2,as well as their association with M2 macrophages were evaluated using the HPA,TNMplot,and GEPIA2 databases and verified by tissue immunofluorescence staining.Moreover,in vitro cell experiments were conducted,where FCGR3A was knocked down in pancreatic cancer cells using siRNA to analyze its effects on M2 macrophage infiltration,tumor proliferation,and metastasis.Results:The prognosis of patients in high-risk and low-risk groups was successfully distinguished using a prognostic risk score model of M2 macrophage-related genes(p=0.024).Between the high-and low-risk cohorts,there have been notable variations in immune cell infiltration patterns,tumor mutations,and biological functions.The risk score was linked to the manifestation of prevalent immunological checkpoints,immunological scores,and stroma values(all p<0.05).In vitro experiments and tissue immunofluorescence staining revealed that FCGR3A can promote the infiltration or polarization of M2 macrophages and enhance tumor proliferation and migration.Conclusions:In this study,an M2 macrophage-related pancreatic cancer risk score model was established,and found that FCGR3A was correlated with tumor formation,metastasis,and M2 macrophage infiltration.展开更多
BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic...BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic KRAS mutations,resulting in the continuous activation of epidermal growth factor receptor signaling.AIM To investigate the key pathogenic genes in KRAS mutant colon cancer holds considerable importance.METHODS Weighted gene co-expression network analysis,in combination with additional bioinformatics analysis,were conducted to screen the key factors driving the progression of KRAS mutant colon cancer.Meanwhile,various in vitro experiments were also conducted to explore the biological function of transglutaminase 2(TGM2).RESULTS Integrated analysis demonstrated that TGM2 acted as an independent prognostic factor for progression-free survival.Immunohistochemical analysis on tissue microarrays revealed that TGM2 was associated with an elevated probability of perineural invasion in patients with KRAS mutant colon cancer.Additionally,biological roles of the key gene TGM2 was also assessed,suggesting that the downregulation of TGM2 attenuated the proliferation,invasion,and migration of the KRAS mutant colon cancer cell line.CONCLUSION This study underscores the potential significance of TGM2 in the progression of KRAS mutant colon cancer.This insight not only offers a theoretical foundation for therapeutic approaches but also highlights the need for additional clinical trials and fundamental research to support our preliminary findings.展开更多
BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic e...BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic evaluation.AIM To determine PBC-associated hub genes and assess their clinical utility for disease prediction.METHODS PBC expression data were obtained from the Gene Expression Omnibus database.Overlapping genes from differential expression analysis and weighted gene coexpression network analysis(WGCNA)were identified as key genes for PBC.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes.Hub genes were identified in protein-protein interaction(PPI)networks using the Degree algorithm in Cytoscape software.The relationship between hub genes and immune cells was investigated.Finally,a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.RESULTS We identified 71 overlapping key genes using differential expression analysis and WGCNA.These genes were primarily enriched in pathways related to cytokinecytokine receptor interaction,and Th1,Th2,and Th17 cell differentiation.We utilized Cytoscape software and identified five hub genes(CD247,IL10,CCL5,CCL3,and STAT3)in PPI networks.These hub genes showed a strong correlation with immune cell infiltration in PBC.However,inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.CONCLUSION Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment,thereby offering significant clinical utility.展开更多
BACKGROUND The development and progression of hepatocellular carcinoma(HCC)have been reported to be associated with immune-related genes and the tumor microenvir-onment.Nevertheless,there are not enough prognostic bio...BACKGROUND The development and progression of hepatocellular carcinoma(HCC)have been reported to be associated with immune-related genes and the tumor microenvir-onment.Nevertheless,there are not enough prognostic biomarkers and models available for clinical use.Based on seven prognostic genes,this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment(TME).AIM To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.METHODS We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC)datasets.TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression.The relative analysis of tumor mutation burden(TMB),TME cell infiltration,immune check-points,immune therapy,and functional pathways was also performed based on prognostic genes.RESULTS Seven prognostic genes were identified for signature construction.Survival receiver operating characteristic curve analysis showed the good performance of survival prediction.TMB could be regarded as an independent factor in HCC survival prediction.There was a significant difference in stromal score,immune score,and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model.Several immune checkpoints,including VTCN1 and TNFSF9,were found to be associated with the seven prognostic genes and risk score.Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies.Potential pathways,such as cell cycle regulation and metabolism of some amino acids,were also identified and analyzed.CONCLUSION The novel seven-gene(CYTH3,ENG,HTRA3,PDZD4,SAMD14,PGF,and PLN)prognostic model showed high predictive efficiency.The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC,which might be worthy of clinical application.展开更多
BACKGROUND Transcatheter arterial embolisation(TACE)is the primary treatment for intermediate-stage hepatocellular carcinoma(HCC)patients while some HCC cases have shown resistance to TACE.AIM To investigate the key g...BACKGROUND Transcatheter arterial embolisation(TACE)is the primary treatment for intermediate-stage hepatocellular carcinoma(HCC)patients while some HCC cases have shown resistance to TACE.AIM To investigate the key genes and potential mechanisms correlated with TACE refractoriness in HCC.METHODS The microarray datasets of TACE-treated HCC tissues,HCC and non-HCC tissues were collected by searching multiple public databases.The respective differentially expressed genes(DEGs)were attained via limma R package.Weighted gene co-expression network analysis was employed for identifying the significant modules related to TACE non-response.TACE refractoriness-related genes were obtained by intersecting up-regulated TACE-associated and HCC-associated DEGs together with the genes in significant modules related to TACE nonresponse.The key genes expression in the above two pairs of samples was compared respectively via Wilcoxon tests and standard mean differences model.The prognostic value of the key genes was evaluated by Kaplan-Meier curve.Multivariate analysis was utilised to investigate the independent prognostic factor in key genes.Single-cell RNA(scRNA)sequencing analysis was conducted to explore the cell types in HCC.TACE refractoriness-related genes activity was calculated via AUCell packages.The CellChat R package was used for the investigation of the cell–cell communication between the identified cell types.RESULTS HCC tissues of TACE non-responders(n=66)and TACE responders(n=81),HCC(n=3941)and non-HCC(n=3443)tissues were obtained.The five key genes,DLG associated protein 5(DLGAP5),Kinesin family member 20A(KIF20A),Assembly factor for spindle microtubules(ASPM),Kinesin family member 11(KIF11)and TPX2 microtubule nucleation factor(TPX2)in TACE refractoriness-related genes,were identified.The five key genes were all up-regulated in the TACE non-responders group and the HCC group.High expression of the five key genes predicted poor prognosis in HCC.Among the key genes,TPX2 was an independent prognostic factor.Four cell types,hepatocytes,embryonic stem cells,T cells and B cells,were identified in the HCC tissues.The TACE refractoriness-related genes expressed primarily in hepatocytes and embryonic stem cells.Hepatocytes,as the providers of ligands,had the strongest interaction with embryonic stem cells that provided receptors.CONCLUSION Five key genes(DLGAP5,KIF20A,ASPM,KIF11 and TPX2)were identified as promoting refractory TACE.Hepatocytes and embryonic stem cells were likely to boost TACE refractoriness.展开更多
Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing herit...Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET (Simultaneously Inference of GeNEs and Tissues) to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.展开更多
The feed forward loop (FFL), wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small nu...The feed forward loop (FFL), wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small number of reactant molecules and thus internal molecular fluctuation is considerable. Here we studied how an FFL responds to small external signal inputs at gene X, with particular attention paid to the fluctuation resonance (FR) phenomenon of gene Z. We found that for all coherent FFLs, where the sign of the direct regulation path from X to Z is the same as the overall sign of the indirect path via Y, the FR shows a regular single peak, while for incoherent FFLs, the FR exhibits distinct bimodal shapes. The results indicate that one could use small external signals to help identify the regulatory structure of an unknown FFL in complex gene networks.展开更多
The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the comp...The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the complicated regulation mechanism of shoot genes of Arabidopsis Thaliana in response to stimuli. The dynamics of the complicated logic network is analyzed, discussed, and simulated. The simulation results show that the logic network of the active genes of shoot eventually evolves into eleven attractors under the stimuli, including five 1-periodic and six 2-periodic attractors. Our work provides valuable reference and guidance for biologists to understand and explain Arabidopsis' response to external stimuli by experiments.展开更多
In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task i...In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task in bioinformatics.The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determine the network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use of both simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.展开更多
For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most im...For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most important environmental stress factors that limits plant productivity worldwide. Today, transcriptomic approaches seem to give the best coverage of genome level responses. Therefore, microarray serves as an invaluable tool for global gene expression analyses, unravelling new information about gene pathways, in-species and cross-species gene expression comparison, and for the characterization of unknown relationships between genes. In this review we summarize the recent progress in the transcriptomics of ozone to demonstrate the benefits that can be harvested from the application of integrative and systematic analytical approaches to study ozone stress response. We focused our consideration on microarray analyses identifying gene networks responsible for response and tolerance to elevated ozone concentration. From these analyses it is now possible to notice how plant ozone defense responses depend on the interplay between many complex signaling pathways and metabolite signals.展开更多
Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks fro...Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples.Here,we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.展开更多
文摘The aim of this work is to investigate the general functional properties of the intracellular governing gene/epigene networks. A body of mathematics used in automata and graphs theories is adequate for revealing the general dynamic properties of governing gene and epigene networks and provides a methodic basis for efficient analytical algorithms. The obtained results permit to reveal the properties of the characteristic function (transitions and outputs) of the cellular automata as models for the intracellular governing gene/epigene networks.
文摘This paper presents a design method of H<sub>2</sub> and H<sub>∞</sub>-feedback control loop for nonlinear smooth gene networks that are in control affine form. Formulaic solution methodology for solving the nonlinear partial differential equations, namely the Hamilton-Jacobi-Bellman and Hamilton-Jacobi-Isaacs equations through successive Galerkin’s approximation is implemented and the results are compared. Throughout the implementation, there were several caveats that need to be further resolved for practical applications in general cases. Such issues and the clarification of causes are mathematically established and reviewed.
基金supported by grants from the National Natural Science Foundation of China (grants 32070656,32270709,32070677,and 32000362)the Natural Science Foundation of Jiangsu Higher Education Institutions of China (grant 23KJA210002)+1 种基金the open funds of the Jiangsu Key Laboratory of Crop Genomics and Molecular Breeding (grant PL202105),the Priority Academic Program Development of Jiangsu Higher Education Institutions of Jiangsu Higher Education Institutions (PAPD)the 2023 Postgraduate Research&Practice Innovation Program of Jiangsu Province (grant KYCX23_0131).
文摘The plant genome produces an extremely large collection of long noncoding RNAs(lncRNAs)that are generally expressed in a context-specific manner and have pivotal roles in regulation of diverse biological processes.Here,we mapped the transcriptional heterogeneity of lncRNAs and their associated gene reg-ulatory networks at single-cell resolution.We generated a comprehensive cell atlas at the whole-organism level by integrative analysis of 28 published single-cell RNA sequencing(scRNA-seq)datasets from juvenile Arabidopsis seedlings.We then provided an in-depth analysis of cell-type-related lncRNA signatures that show expression patterns consistent with canonical protein-coding gene markers.We further demon-strated that the cell-type-specific expression of lncRNAs largely explains their tissue specificity.In addi-tion,we predicted gene regulatory networks on the basis of motif enrichment and co-expression analysis of lncRNAs and mRNAs,and we identified putative transcription factors orchestrating cell-type-specific expression of lncRNAs.The analysis results are available at the single-cell-based plant lncRNA atlas data-base(scPLAD;https://biobigdata.nju.edu.cn/scPLAD/).Overall,this work demonstrates the power of inte-grative single-cell data analysis applied to plant lncRNA biology and provides fundamental insights into lncRNA expression specificity and associated gene regulation.
基金supported in part by the National Science and Technol-ogy Major Project(No.2021ZD0111502)the National Nat-ural Science Foundation of China(Nos.62176147,62476163)+2 种基金the Science and Technology Planning Project of Guangdong Province of China(Nos.2022A1515110660,2021JC06X549)the STU Scientific Research Foundation for Talents(No.NTF21001)Guangdong Basic and Applied Basic Research Foundation(No.2023B1515120020)。
文摘The complexity of unknown scenarios and the dynamics involved in target entrapment make designing control strategies for swarm robots a formidable task,which in turn impacts their efficiency in complex and dynamic settings.To address these challenges,this paper introduces an adaptive swarm robot entrapment control model grounded in the transformation of gene regulatory networks(AT-GRN).This innovative model enables swarm robots to dynamically adjust entrap-ment strategies by assessing current environmental conditions via real-time sensory data.Further-more,an improved motion control model for swarm robots is designed to dynamically shape the for-mation generated by the AT-GRN.Through two sets of rigorous experimental environments,the proposed model significantly enhances the trapping performance of swarm robots in complex envi-ronments,demonstrating remarkable adaptability and stability.
基金supported by the Notional Natural Science Foundation of China,No.81960417 (to JX)Guangxi Key Research and Development Program,No.GuiKeA B20159027 (to JX)the Natural Science Foundation of Guangxi Zhuang Autonomous Region,No.2022GXNSFBA035545 (to YG)。
文摘Immune changes and inflammatory responses have been identified as central events in the pathological process of spinal co rd injury.They can greatly affect nerve regeneration and functional recovery.However,there is still limited understanding of the peripheral immune inflammato ry response in spinal cord inju ry.In this study.we obtained microRNA expression profiles from the peripheral blood of patients with spinal co rd injury using high-throughput sequencing.We also obtained the mRNA expression profile of spinal cord injury patients from the Gene Expression Omnibus(GEO)database(GSE151371).We identified 54 differentially expressed microRNAs and 1656 diffe rentially expressed genes using bioinformatics approaches.Functional enrichment analysis revealed that various common immune and inflammation-related signaling pathways,such as neutrophil extracellular trap formation pathway,T cell receptor signaling pathway,and nuclear factor-κB signal pathway,we re abnormally activated or inhibited in spinal cord inju ry patient samples.We applied an integrated strategy that combines weighted gene co-expression network analysis,LASSO logistic regression,and SVM-RFE algorithm and identified three biomarke rs associated with spinal cord injury:ANO10,BST1,and ZFP36L2.We verified the expression levels and diagnostic perfo rmance of these three genes in the original training dataset and clinical samples through the receiver operating characteristic curve.Quantitative polymerase chain reaction results showed that ANO20 and BST1 mRNA levels were increased and ZFP36L2 mRNA was decreased in the peripheral blood of spinal cord injury patients.We also constructed a small RNA-mRNA interaction network using Cytoscape.Additionally,we evaluated the proportion of 22 types of immune cells in the peripheral blood of spinal co rd injury patients using the CIBERSORT tool.The proportions of naive B cells,plasma cells,monocytes,and neutrophils were increased while the proportions of memory B cells,CD8^(+)T cells,resting natural killer cells,resting dendritic cells,and eosinophils were markedly decreased in spinal cord injury patients increased compared with healthy subjects,and ANO10,BST1 and ZFP26L2we re closely related to the proportion of certain immune cell types.The findings from this study provide new directions for the development of treatment strategies related to immune inflammation in spinal co rd inju ry and suggest that ANO10,BST2,and ZFP36L2 are potential biomarkers for spinal cord injury.The study was registe red in the Chinese Clinical Trial Registry(registration No.ChiCTR2200066985,December 12,2022).
基金funded by the National Natural Science Foundation of China(62176147)the Science and Technology Planning Project of Guangdong Province of China,the State Key Lab of Digital Manufacturing Equipment and Technology(DMETKF2019020)the National Defense Technology Innovation Special Zone Project(193-A14-226-01-01)。
文摘This study proposes a method for uniformly revolving swarm robots to entrap multiple targets,which is based on a gene regulatory network,an adaptive decision mechanism,and an improved Vicsek-model.Using the gene regulatory network method,the robots can generate entrapping patterns according to the environmental input,including the positions of the targets and obstacles.Next,an adaptive decision mechanism is proposed,allowing each robot to choose the most well-adapted capture point on the pattern,based on its environment.The robots employ an improved Vicsek-model to maneuver to the planned capture point smoothly,without colliding with other robots or obstacles.The proposed decision mechanism,combined with the improved Vicsek-model,can form a uniform entrapment shape and create a revolving effect around targets while entrapping them.This study also enables swarm robots,with an adaptive pattern formation,to entrap multiple targets in complex environments.Swarm robots can be deployed in the military field of unmanned aerial vehicles’(UAVs)entrapping multiple targets.Simulation experiments demonstrate the feasibility and superiority of the proposed gene regulatory network method.
基金funded by the Mexican government through the Consejo Nacional de Ciencia y Tecnología (CONACYT),C.V.761325,for the PhD project of Jorge Aleman-Baez。
文摘The vegetative development of cabbage(Brassica oleracea var.capitata)passes through seedling,rosette,folding and heading stages.Leaves that form the rosette are large and mostly flat.In the following developmental stages,the plants produce leaves that curve inward to produce the leafy head.Many microRNAs and their target genes have been described participating in leaf development and leaf curvature.The aim of this study is to investigate the role of miRNA-regulated genes in the transition from the rosette to the heading stage.We compared the mi RNA and gene abundances between emerging rosette and heading leaves.To remove transcripts(miRNAs and genes)whose regulation was most likely associated with plant age rather than the change from rosette to heading stage,we utilized a non-heading collard green(B.oleracea var.acephala)morphotype as control.This resulted in 33 DEMs and 1998 DEGs with likely roles in the transition from rosette to heading stage in cabbage.Among these 1998 DEGs,we found enriched GO terms related to DNA-binding transcription factor activity,transcription regulator activity,iron ion binding,and photosynthesis.We predicted the target genes of these 33 DEMs and focused on the subset that was differentially expressed(1998DEGs)between rosette and heading stage leaves to construct mi RNA-target gene interaction networks.Our main finding is a role for miR396b-5p targeting two Arabidopsis thaliana orthologues of GROWTH REGULATING FACTORs 3(GRF3)and 4(GRF4)in pointed cabbage head formation.
基金supported in part by the Priority Academic Program Development of Jiangsu Higher Education Institutions and the State Key Laboratory of Crop Genetics and Germplasm Enhancement,China(ZW201813)。
文摘Rosa roxburghii fruit is rich in flavonoids, but little is known about their biosynthetic pathways. In this study, we employed transcriptomics and metabolomics to study changes related to the flavonoids at five different stages of R. roxburghii fruit development. Flavonoids and the genes related to their biosynthesis were found to undergo significant changes in abundance across different developmental stages, and numerous quercetin derivatives were identified. We found three gene expression modules that were significantly associated with the abundances of the different flavonoids in R. roxburghii and identified three structural UDP-glycosyltransferase genes directly involved in the synthesis of quercetin derivatives within these modules. In addition, we found that RrBEH4, RrLBD1 and RrPIF8could significantly increase the expression of downstream quercetin derivative biosynthesis genes. Taken together,these results provide new insights into the metabolism of flavonoids and the accumulation of quercetin derivatives in R. roxburghii.
基金supported by the earmarked fund for CARS,China(CARS-42)the earmarked fund for Jiangsu Agricultural Industry Technology System,China(JATS(2022)331)the Jiangsu Key Research and Development Program,China(BE2021332)。
文摘The Chinese crested duck is a unique duck breed having a bulbous feather shape on its duck head.However,the mechanisms involved in its formation and development are unclear.In the present study,RNA sequencing analysis was performed on the crested tissues of 6 Chinese crested ducks and the scalp tissues of 6 cherry valley ducks(CVs)from 2 developmental stages.This study identified 261 differentially expressed genes(DEGs),122 upregulated and 139 downregulated,in the E28 stage and 361 DEGs,154 upregulated and 207 downregulated in the D42 stage between CC and CV ducks.The subsequent results of weighted gene co-expression network analysis(WGCNA)revealed that the turquoise and cyan modules were associated with the crest trait in the D42 stage,meanwhile,the green,brown,and pink modules were associated with the crest trait in the E28 stage.Venn analysis of the DEGs and WGCNA showed that 145 and 45 genes are associated between the D42 and E28 stages,respectively.The expression of WNT16,BMP2,SLC35F2,SLC6A15,APOBEC2,ABHD6,TNNC2,MYL1,and TNNI2 were verified by real-time quantitative PCR.This study provides an approach to reveal the molecular mechanisms underlying the crested trait development.
文摘Background:Pancreatic ductal adenocarcinoma(PDAC)has a rich and complex tumor immune microenvironment(TIME).M2 macrophages are among the most extensively infiltrated immune cells in the TIME and are necessary for the growth and migration of cancers.However,the mechanisms and targets mediating M2 macrophage infiltration in pancreatic cancer remain elusive.Methods:The M2 macrophage infiltration score of patients was assessed using the xCell algorithm.Using weighted gene co-expression network analysis(WGCNA),module genes associated with M2 macrophages were identified,and a predictive model was designed.The variations in immunological cell patterns,cancer mutations,and enrichment pathways between the cohorts with the high-and low-risk were examined.Additionally,the expression of FCGR3A and RNASE2,as well as their association with M2 macrophages were evaluated using the HPA,TNMplot,and GEPIA2 databases and verified by tissue immunofluorescence staining.Moreover,in vitro cell experiments were conducted,where FCGR3A was knocked down in pancreatic cancer cells using siRNA to analyze its effects on M2 macrophage infiltration,tumor proliferation,and metastasis.Results:The prognosis of patients in high-risk and low-risk groups was successfully distinguished using a prognostic risk score model of M2 macrophage-related genes(p=0.024).Between the high-and low-risk cohorts,there have been notable variations in immune cell infiltration patterns,tumor mutations,and biological functions.The risk score was linked to the manifestation of prevalent immunological checkpoints,immunological scores,and stroma values(all p<0.05).In vitro experiments and tissue immunofluorescence staining revealed that FCGR3A can promote the infiltration or polarization of M2 macrophages and enhance tumor proliferation and migration.Conclusions:In this study,an M2 macrophage-related pancreatic cancer risk score model was established,and found that FCGR3A was correlated with tumor formation,metastasis,and M2 macrophage infiltration.
基金Supported by National Nature Science Foundation of China,No.82100195China Postdoctoral Science Foundation,No.2021M700777Medical Research Project of Foshan Municipal Health Bureau,No.20230349.
文摘BACKGROUND Colon cancer is acknowledged as one of the most common malignancies worldwide,ranking third in United States regarding incidence and mortality.Notably,approximately 40%of colon cancer cases harbor oncogenic KRAS mutations,resulting in the continuous activation of epidermal growth factor receptor signaling.AIM To investigate the key pathogenic genes in KRAS mutant colon cancer holds considerable importance.METHODS Weighted gene co-expression network analysis,in combination with additional bioinformatics analysis,were conducted to screen the key factors driving the progression of KRAS mutant colon cancer.Meanwhile,various in vitro experiments were also conducted to explore the biological function of transglutaminase 2(TGM2).RESULTS Integrated analysis demonstrated that TGM2 acted as an independent prognostic factor for progression-free survival.Immunohistochemical analysis on tissue microarrays revealed that TGM2 was associated with an elevated probability of perineural invasion in patients with KRAS mutant colon cancer.Additionally,biological roles of the key gene TGM2 was also assessed,suggesting that the downregulation of TGM2 attenuated the proliferation,invasion,and migration of the KRAS mutant colon cancer cell line.CONCLUSION This study underscores the potential significance of TGM2 in the progression of KRAS mutant colon cancer.This insight not only offers a theoretical foundation for therapeutic approaches but also highlights the need for additional clinical trials and fundamental research to support our preliminary findings.
基金Supported by School-Level Key Projects at Bengbu Medical College,No.2021byzd109。
文摘BACKGROUND The identification of specific gene expression patterns is crucial for understanding the mechanisms underlying primary biliary cholangitis(PBC)and finding relevant biomarkers for diagnosis and therapeutic evaluation.AIM To determine PBC-associated hub genes and assess their clinical utility for disease prediction.METHODS PBC expression data were obtained from the Gene Expression Omnibus database.Overlapping genes from differential expression analysis and weighted gene coexpression network analysis(WGCNA)were identified as key genes for PBC.Kyoto Encyclopedia of Genes and Genomes and Gene Ontology analyses were performed to explore the potential roles of key genes.Hub genes were identified in protein-protein interaction(PPI)networks using the Degree algorithm in Cytoscape software.The relationship between hub genes and immune cells was investigated.Finally,a Mendelian randomization study was conducted to determine the causal effects of hub genes on PBC.RESULTS We identified 71 overlapping key genes using differential expression analysis and WGCNA.These genes were primarily enriched in pathways related to cytokinecytokine receptor interaction,and Th1,Th2,and Th17 cell differentiation.We utilized Cytoscape software and identified five hub genes(CD247,IL10,CCL5,CCL3,and STAT3)in PPI networks.These hub genes showed a strong correlation with immune cell infiltration in PBC.However,inverse variance weighting analysis did not indicate the causal effects of hub genes on PBC risk.CONCLUSION Hub genes can potentially serve as valuable biomarkers for PBC prediction and treatment,thereby offering significant clinical utility.
文摘BACKGROUND The development and progression of hepatocellular carcinoma(HCC)have been reported to be associated with immune-related genes and the tumor microenvir-onment.Nevertheless,there are not enough prognostic biomarkers and models available for clinical use.Based on seven prognostic genes,this study calculated overall survival in patients with HCC using a prognostic survival model and revealed the immune status of the tumor microenvironment(TME).AIM To develop a novel immune cell-related prognostic model of HCC and depict the basic profile of the immune response in HCC.METHODS We obtained clinical information and gene expression data of HCC from The Cancer Genome Atlas(TCGA)and International Cancer Genome Consortium(ICGC)datasets.TCGA and ICGC datasets were used for screening prognostic genes along with developing and validating a seven-gene prognostic survival model by weighted gene coexpression network analysis and least absolute shrinkage and selection operator regression with Cox regression.The relative analysis of tumor mutation burden(TMB),TME cell infiltration,immune check-points,immune therapy,and functional pathways was also performed based on prognostic genes.RESULTS Seven prognostic genes were identified for signature construction.Survival receiver operating characteristic curve analysis showed the good performance of survival prediction.TMB could be regarded as an independent factor in HCC survival prediction.There was a significant difference in stromal score,immune score,and estimate score between the high-risk and low-risk groups stratified based on the risk score derived from the seven-gene prognostic model.Several immune checkpoints,including VTCN1 and TNFSF9,were found to be associated with the seven prognostic genes and risk score.Different combinations of checkpoint blockade targeting inhibitory CTLA4 and PD1 receptors and potential chemotherapy drugs hold great promise for specific HCC therapies.Potential pathways,such as cell cycle regulation and metabolism of some amino acids,were also identified and analyzed.CONCLUSION The novel seven-gene(CYTH3,ENG,HTRA3,PDZD4,SAMD14,PGF,and PLN)prognostic model showed high predictive efficiency.The TMB analysis based on the seven genes could depict the basic profile of the immune response in HCC,which might be worthy of clinical application.
基金Guangxi Higher Education Undergraduate Teaching Reform Project,No.2021JGA142Guangxi Educational Science Planning Key Project,No.2022ZJY2791+1 种基金Guangxi Medical University Education and Teaching Reform Project,No.2021XJGA02Guangxi Zhuang Autonomous Region Health Commission Self-financed Scientific Research Project,No.Z20201147.
文摘BACKGROUND Transcatheter arterial embolisation(TACE)is the primary treatment for intermediate-stage hepatocellular carcinoma(HCC)patients while some HCC cases have shown resistance to TACE.AIM To investigate the key genes and potential mechanisms correlated with TACE refractoriness in HCC.METHODS The microarray datasets of TACE-treated HCC tissues,HCC and non-HCC tissues were collected by searching multiple public databases.The respective differentially expressed genes(DEGs)were attained via limma R package.Weighted gene co-expression network analysis was employed for identifying the significant modules related to TACE non-response.TACE refractoriness-related genes were obtained by intersecting up-regulated TACE-associated and HCC-associated DEGs together with the genes in significant modules related to TACE nonresponse.The key genes expression in the above two pairs of samples was compared respectively via Wilcoxon tests and standard mean differences model.The prognostic value of the key genes was evaluated by Kaplan-Meier curve.Multivariate analysis was utilised to investigate the independent prognostic factor in key genes.Single-cell RNA(scRNA)sequencing analysis was conducted to explore the cell types in HCC.TACE refractoriness-related genes activity was calculated via AUCell packages.The CellChat R package was used for the investigation of the cell–cell communication between the identified cell types.RESULTS HCC tissues of TACE non-responders(n=66)and TACE responders(n=81),HCC(n=3941)and non-HCC(n=3443)tissues were obtained.The five key genes,DLG associated protein 5(DLGAP5),Kinesin family member 20A(KIF20A),Assembly factor for spindle microtubules(ASPM),Kinesin family member 11(KIF11)and TPX2 microtubule nucleation factor(TPX2)in TACE refractoriness-related genes,were identified.The five key genes were all up-regulated in the TACE non-responders group and the HCC group.High expression of the five key genes predicted poor prognosis in HCC.Among the key genes,TPX2 was an independent prognostic factor.Four cell types,hepatocytes,embryonic stem cells,T cells and B cells,were identified in the HCC tissues.The TACE refractoriness-related genes expressed primarily in hepatocytes and embryonic stem cells.Hepatocytes,as the providers of ligands,had the strongest interaction with embryonic stem cells that provided receptors.CONCLUSION Five key genes(DLGAP5,KIF20A,ASPM,KIF11 and TPX2)were identified as promoting refractory TACE.Hepatocytes and embryonic stem cells were likely to boost TACE refractoriness.
文摘Although genome-wide association studies (GWAS) have successfully identified thousands of genomic loci associated with hun- dreds of complex traits in the past decade, the debate about such problems as missing heritabiUty and weak interpretability has been appealing for effective computational methods to facilitate the advanced analysis of the vast volume of existing and antici- pated genetic data. Towards this goal, gene-tevel integrative GWAS analysis with the assumption that genes associated with a phenotype tend to be enriched in biological gene sets or gene networks has recently attracted much attention, due to such advan- tages as straightforward interpretation, tess multiple testing burdens, and robustness across studies. However, existing methods in this category usually exploit non-tissue-specific gene networks and thus lack the ability to utilize informative tissue-specific characteristics. To overcome this limitation, we proposed a Bayesian approach called SIGNET (Simultaneously Inference of GeNEs and Tissues) to integrate GWAS data and multiple tissue-specific gene networks for the simultaneous inference of phenotype- associated genes and relevant tissues. Through extensive simulation studies, we showed the effectiveness of our method in find- ing both associated genes and relevant tissues for a phenotype. In applications to real GWAS data of 14 complex phenotypes, we demonstrated the power of our method in both deciphering genetic basis and discovering biological insights of a phenotype. With this understanding, we expect to see SIGNET as a valuable tool for integrative GWAS analysis, thereby boosting the preven- tion, diagnosis, and treatment of human inherited diseases and eventually facilitating precision medicine.
基金ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation of China (No.20673106).
文摘The feed forward loop (FFL), wherein a gene X can regulate target gene Z alone or cooperatively with gene Y, is one of the most important motifs in gene regulatory networks. Gene expression often involves a small number of reactant molecules and thus internal molecular fluctuation is considerable. Here we studied how an FFL responds to small external signal inputs at gene X, with particular attention paid to the fluctuation resonance (FR) phenomenon of gene Z. We found that for all coherent FFLs, where the sign of the direct regulation path from X to Z is the same as the overall sign of the indirect path via Y, the FR shows a regular single peak, while for incoherent FFLs, the FR exhibits distinct bimodal shapes. The results indicate that one could use small external signals to help identify the regulatory structure of an unknown FFL in complex gene networks.
基金This research is supported by the National Natural Science Foundation of China under Grant Nos. 60874036 and 60503002.
文摘The reverse construction and analysis of the networks of molecular interactions are essential for understanding their functions within cells. In this paper, a logic network model is constructed to investigate the complicated regulation mechanism of shoot genes of Arabidopsis Thaliana in response to stimuli. The dynamics of the complicated logic network is analyzed, discussed, and simulated. The simulation results show that the logic network of the active genes of shoot eventually evolves into eleven attractors under the stimuli, including five 1-periodic and six 2-periodic attractors. Our work provides valuable reference and guidance for biologists to understand and explain Arabidopsis' response to external stimuli by experiments.
基金supported by National Natural Science Foundation of China (Grant Nos. 60433020, 60175024 and 60773095)European Commission under grant No. TH/Asia Link/010 (111084)the Key Science-Technology Project of the National Education Ministry of China (Grant No. 02090),and the Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, P. R. China
文摘In the post-genomic biology era,the reconstruction of gene regulatory networks from microarray gene expression data is very important to understand the underlying biological system,and it has been a challenging task in bioinformatics.The Bayesian network model has been used in reconstructing the gene regulatory network for its advantages,but how to determine the network structure and parameters is still important to be explored.This paper proposes a two-stage structure learning algorithm which integrates immune evolution algorithm to build a Bayesian network.The new algorithm is evaluated with the use of both simulated and yeast cell cycle data.The experimental results indicate that the proposed algorithm can find many of the known real regulatory relationships from literature and predict the others unknown with high validity and accuracy.
文摘For many plant species ozone stress has become much more severe in the last decade. The accumulating evidence for the significant effects of ozone pollutant on crop and forest yield situate ozone as one of the most important environmental stress factors that limits plant productivity worldwide. Today, transcriptomic approaches seem to give the best coverage of genome level responses. Therefore, microarray serves as an invaluable tool for global gene expression analyses, unravelling new information about gene pathways, in-species and cross-species gene expression comparison, and for the characterization of unknown relationships between genes. In this review we summarize the recent progress in the transcriptomics of ozone to demonstrate the benefits that can be harvested from the application of integrative and systematic analytical approaches to study ozone stress response. We focused our consideration on microarray analyses identifying gene networks responsible for response and tolerance to elevated ozone concentration. From these analyses it is now possible to notice how plant ozone defense responses depend on the interplay between many complex signaling pathways and metabolite signals.
基金supported by the National Key Research and Development Program of China(2017YFA0505500)Strategic Priority Research Program of the Chinese Academy of Sciences(XDB38040400)+1 种基金National Science Foundation of China(31771476 and 31930022)Shanghai Municipal Science and Technology Major Project(2017SHZDZX01)。
文摘Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level.Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples.Here,we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.