The Experts below are selected from a list of 244515 Experts worldwide ranked by ideXlab platform
Marie-laure Martin-magniette - One of the best experts on this subject based on the ideXlab platform.
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DiCoExpress: a tool to process multifactorial RNAseq experiments from quality Controls to co-expression analysis through Differential analysis based on contrasts inside GLM models
Plant Methods, 2020Co-Authors: Ilana Lambert, Christine Paysant-le Roux, Stefano Colella, Marie-laure Martin-magnietteAbstract:Background RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realised neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis. Results DiCoExpress is a script-based tool implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses pre-existing R packages including FactoMineR, edgeR and coseq, to perform quality Control, Differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality Control step, the user can move on to the Differential expression analysis performed using generalized linear models thanks to the automated contrast writing function. A co-expression analysis is implemented using the coseq package. Lists of Differentially expressed genes and identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user. We used DiCoExpress to analyze a publicly available RNAseq dataset on the transcriptional response of Brassica napus L. to silicon treatment in plant roots and mature leaves. This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress. Conclusions DiCoExpress is an R script-based tool allowing users to perform a full RNAseq analysis from quality Controls to co-expression analysis through Differential analysis based on contrasts inside generalized linear models. DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results.
Judy Kantor - One of the best experts on this subject based on the ideXlab platform.
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admixture of a recombinant vaccinia virus containing the gene for the costimulatory molecule b7 and a recombinant vaccinia virus containing a tumor associated antigen gene results in enhanced specific t cell responses and antitumor immunity
Cancer Research, 1995Co-Authors: James W Hodge, Joanne P Mclaughlin, Scott I Abrams, W L Shupert, Jeffrey Schlom, Judy KantorAbstract:At least two signals are required for the activation of naive T cells by antigen-bearing target cells: an antigen-specific signal, delivered through the T-cell receptor, and a costimulatory signal delivered through the T-cell surface molecule CD28 by its natural ligand B7-1. The immunological benefit of coexpression of B7 with target antigen has been demonstrated with the use of several retroviral systems to transfect antigen-bearing cells. Although engineering recombinant constructs with genes for two or more antigens can mediate the dual expression of those antigens, disadvantages of this approach include the time for construction of each desirable combination and the inability to Control Differential expression levels of each gene product. An alternative approach would utilize separate constructs that could be admixed appropriately before administration. In this report we describe the functional consequences of the admixture of recombinant vaccinia murine B7-1 (rV-B7) to recombinant vaccinia expressing the human carcinoembryonic antigen gene (rV-CEA). Coinfection of cells resulted in high levels of cell surface expression of both the CEA and B7 molecules. Immunization of mice with various ratios (1:3, 1:1, 3:1) of rV-CEA and rV-B7 demonstrated that an admixture of rV-CEA and rV-B7 at a 3:1 ratio resulted in the generation of optimal CEA-specific T-cell responses. Next, we examined the efficacy of this admixture on antitumor activity. Typically, injection of murine carcinoma cells expressing CEA leads to the death of the host. One immunization of C57BL/6 mice with rV-CEA:rV-B7 (3:1) resulted in no tumor establishment. In contrast, administration of rV-CEA or rV-B7 alone had little or no antitumor effects. These studies demonstrate the advantages of the use of recombinant vaccinia viruses to deliver B7 molecules in combination with a tumor-associated antigen. The availability of the rV-B7 single construct and the ability to alter the B7 ratio could also have potential utility when coinfecting rV-B7 with recombinant vaccinia viruses containing genes for infectious agents or other tumor-associated antigen genes.
Ilana Lambert - One of the best experts on this subject based on the ideXlab platform.
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DiCoExpress: a tool to process multifactorial RNAseq experiments from quality Controls to co-expression analysis through Differential analysis based on contrasts inside GLM models
Plant Methods, 2020Co-Authors: Ilana Lambert, Christine Paysant-le Roux, Stefano Colella, Marie-laure Martin-magnietteAbstract:Background RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realised neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis. Results DiCoExpress is a script-based tool implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses pre-existing R packages including FactoMineR, edgeR and coseq, to perform quality Control, Differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality Control step, the user can move on to the Differential expression analysis performed using generalized linear models thanks to the automated contrast writing function. A co-expression analysis is implemented using the coseq package. Lists of Differentially expressed genes and identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user. We used DiCoExpress to analyze a publicly available RNAseq dataset on the transcriptional response of Brassica napus L. to silicon treatment in plant roots and mature leaves. This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress. Conclusions DiCoExpress is an R script-based tool allowing users to perform a full RNAseq analysis from quality Controls to co-expression analysis through Differential analysis based on contrasts inside generalized linear models. DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results.
Subhransu Sekhar Dash - One of the best experts on this subject based on the ideXlab platform.
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a hybrid stochastic fractal search and local unimodal sampling based multistage pdf plus 1 pi Controller for automatic generation Control of power systems
Journal of The Franklin Institute-engineering and Applied Mathematics, 2017Co-Authors: Raghuraman Sivalingam, Subramani Chinnamuthu, Subhransu Sekhar DashAbstract:Abstract This paper proposes to use a hybrid Stochastic Fractal Search (SFS) and Local Unimodal Sampling (LUS) based multistage Proportional Integral Derivative (PID) Controller consisting of Proportional Derivative Controller with derivative Filter (PDF) plus (1 + Proportional Integral) for Automatic Generation Control (AGC) of power systems. Initially, a single area multi-source power system consisting of thermal hydro and gas power plants is considered and parameters of Integral (I) Controller is optimized by Stochastic Fractal Search (SFS) algorithm. The superiority of SFS algorithm over some recently proposed approaches such as optimal Control, Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO) is demonstrated. To improve the system performance further, LUS is subsequently employed. The study is further extended for different Controllers like PID, and proposed multistage PID Controller and the superiority of multistage PID Controller over conventional PID Controller structure is demonstrated. The study is further extended to a two-area six unit multi-source interconnected power system and the superiority of proposed approach over, TLBO and optimal Control is demonstrated. Finally the study is extended to a three unequal area system power system with appropriate nonlinearities such as Generation Rate Constraint (GRC), Governor Dead Band (GDB) and time delay. From the analysis, it is found that hybrid SFS–LUS algorithm is superior to the original SFS algorithm and substantial improvement in system performance are realized with proposed multistage PID Controller over conventional PID Controller structure.
Stefano Colella - One of the best experts on this subject based on the ideXlab platform.
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DiCoExpress: a tool to process multifactorial RNAseq experiments from quality Controls to co-expression analysis through Differential analysis based on contrasts inside GLM models
Plant Methods, 2020Co-Authors: Ilana Lambert, Christine Paysant-le Roux, Stefano Colella, Marie-laure Martin-magnietteAbstract:Background RNAseq is nowadays the method of choice for transcriptome analysis. In the last decades, a high number of statistical methods, and associated bioinformatics tools, for RNAseq analysis were developed. More recently, statistical studies realised neutral comparison studies using benchmark datasets, shedding light on the most appropriate approaches for RNAseq data analysis. Results DiCoExpress is a script-based tool implemented in R that includes methods chosen based on their performance in neutral comparisons studies. DiCoExpress uses pre-existing R packages including FactoMineR, edgeR and coseq, to perform quality Control, Differential, and co-expression analysis of RNAseq data. Users can perform the full analysis, providing a mapped read expression data file and a file containing the information on the experimental design. Following the quality Control step, the user can move on to the Differential expression analysis performed using generalized linear models thanks to the automated contrast writing function. A co-expression analysis is implemented using the coseq package. Lists of Differentially expressed genes and identified co-expression clusters are automatically analyzed for enrichment of annotations provided by the user. We used DiCoExpress to analyze a publicly available RNAseq dataset on the transcriptional response of Brassica napus L. to silicon treatment in plant roots and mature leaves. This dataset, including two biological factors and three replicates for each condition, allowed us to demonstrate in a tutorial all the features of DiCoExpress. Conclusions DiCoExpress is an R script-based tool allowing users to perform a full RNAseq analysis from quality Controls to co-expression analysis through Differential analysis based on contrasts inside generalized linear models. DiCoExpress focuses on the statistical modelling of gene expression according to the experimental design and facilitates the data analysis leading the biological interpretation of the results.