The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Johannes Jaeger - One of the best experts on this subject based on the ideXlab platform.
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High-resolution gene Expression data from blastoderm embryos of the scuttle fly Megaselia abdita
Scientific Data, 2015Co-Authors: Karl R Wotton, Anton Crombach, Eva Jiménez-guri, Damjan Cicin-sain, Johannes JaegerAbstract:Design Type(s) parallel group design • RNA Interference Measurement Type(s) transcription profiling assay Technology Type(s) in-situ hybridization Factor Type(s) gene list Sample Characteristic(s) Megaselia abdita Machine-accessible metadata file describing the reported data (ISA-Tab format) Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene Expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include Expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries, and integrated Expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution.
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superfly a comparative database for Quantified spatio temporal gene Expression patterns in early dipteran embryos
Nucleic Acids Research, 2015Co-Authors: Damjan Cicinsain, Antonio Hermoso Pulido, Anton Crombach, Karl R Wotton, Eva Jimenezguri, Jeanfrancois Taly, Guglielmo Roma, Johannes JaegerAbstract:We present SuperFly (http://superfly.crg.eu), a relational database for Quantified spatio-temporal Expression data of segmentation genes during early development in different species of dipteran insects (flies, midges and mosquitoes). SuperFly has a special focus on emerging non-drosophilid model systems. The database currently includes data of high spatio-temporal resolution for three species: the vinegar fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata. At this point, SuperFly covers up to 9 genes and 16 time points per species, with a total of 1823 individual embryos. It provides an intuitive web interface, enabling the user to query and access original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries and integrated datasets, plus metadata and intermediate processing steps. SuperFly is a valuable new resource for the quantitative comparative study of gene Expression patterns across dipteran species. Moreover, it provides an interesting test set for systems biologists interested in fitting mathematical gene network models to data. Both of these aspects are essential ingredients for progress toward a more quantitative and mechanistic understanding of developmental evolution.
Karl R Wotton - One of the best experts on this subject based on the ideXlab platform.
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High-resolution gene Expression data from blastoderm embryos of the scuttle fly Megaselia abdita
'Springer Science and Business Media LLC', 2017Co-Authors: Karl R Wotton, Jiménez-guri E, Crombach A, Cicin-sain D, Jaeger JAbstract:This is the final version of the article. Available from the publisher via the DOI in this record.Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene Expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include Expression patterns in both wild-type and RNAi-treated embryos. The data-covering 10 genes, 10 time points, and over 1,000 individual embryos-consist of original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries, and integrated Expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution.This work was funded by the MEC-EMBL agreement for the EMBL/ CRG Research Unit in Systems Biology, by European Commission grant FP7-KBBE-2011-5/289434 (BioPreDyn), by Grant 153 (MOPDEV) of the ERANet: ComplexityNET programme, by AGAUR SGR Grant 406, as well as grants BFU2009-10184 and BFU2012-33775 from the Spanish Ministry of the Economy and Competitiveness (MINECO, formerly MICINN). The Centre for Genomic Regulation (CRG) acknowledges support from MINECO, 'Centro de Excelencia Severo Ochoa 2013-2017', SEV-2012-0208
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High-resolution gene Expression data from blastoderm embryos of the scuttle fly Megaselia abdita
Scientific Data, 2015Co-Authors: Karl R Wotton, Anton Crombach, Eva Jiménez-guri, Damjan Cicin-sain, Johannes JaegerAbstract:Design Type(s) parallel group design • RNA Interference Measurement Type(s) transcription profiling assay Technology Type(s) in-situ hybridization Factor Type(s) gene list Sample Characteristic(s) Megaselia abdita Machine-accessible metadata file describing the reported data (ISA-Tab format) Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene Expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include Expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries, and integrated Expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution.
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superfly a comparative database for Quantified spatio temporal gene Expression patterns in early dipteran embryos
Nucleic Acids Research, 2015Co-Authors: Damjan Cicinsain, Antonio Hermoso Pulido, Anton Crombach, Karl R Wotton, Eva Jimenezguri, Jeanfrancois Taly, Guglielmo Roma, Johannes JaegerAbstract:We present SuperFly (http://superfly.crg.eu), a relational database for Quantified spatio-temporal Expression data of segmentation genes during early development in different species of dipteran insects (flies, midges and mosquitoes). SuperFly has a special focus on emerging non-drosophilid model systems. The database currently includes data of high spatio-temporal resolution for three species: the vinegar fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata. At this point, SuperFly covers up to 9 genes and 16 time points per species, with a total of 1823 individual embryos. It provides an intuitive web interface, enabling the user to query and access original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries and integrated datasets, plus metadata and intermediate processing steps. SuperFly is a valuable new resource for the quantitative comparative study of gene Expression patterns across dipteran species. Moreover, it provides an interesting test set for systems biologists interested in fitting mathematical gene network models to data. Both of these aspects are essential ingredients for progress toward a more quantitative and mechanistic understanding of developmental evolution.
José L. Balibrea - One of the best experts on this subject based on the ideXlab platform.
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prognostic value of the Quantified Expression of p185c erbb2 in non small cell lung cancer
The Journal of Thoracic and Cardiovascular Surgery, 2000Co-Authors: Ramón Cantero, Antonio J. Torres, M.l. Maestro, F Hernando, M. Sanz, V. Del Barco, Ana M. Gómez, Cristina Fernández, José L. BalibreaAbstract:Abstract Background: We sought to assess the relationship between tissue concentration of erb -b-2 or neu oncogene-encoded protein (p185 neu ) with overall survival in patients with non–small cell lung cancer. Methods: Levels of protein p185 neu were determined in 102 patients with the diagnosis of non–small cell lung cancer. Concentration of p185 neu protein was determined by using enzyme immunoassay and evaluated by using several variables. The relative prognostic importance of this marker and its influence on other prognostic factors was evaluated by using the Cox regression model. Results: The mean p185 neu value in these samples was 250 ± 200 U/mg (95% confidence interval, 210-290). This distinguished two groups within the tumoral population: those with less than 350 U/mg and those with 350 U/mg or greater (80th percentile). Multivariable analysis established an independent prognostic value for protein p185 neu . Patients with p185 neu values of the 80th percentile or greater had a risk of death that was 2.11-fold (95% confidence interval, 1.10-4.05) that of patients with values of less than 350 U/mg ( P = .03), and increases in the neu oncogene of 100 U/mg increased the probability of death by 17% ( P = .02; 95% confidence interval, 1.04-1.31). Conclusion: This study shows that the p185 neu Expression is an objective and comparable variable for the assessment of phenotypic aggressivity in non–small cell lung cancer, and in the future, it could be included in daily clinical practice. (J Thorac Cardiovasc Surg 2000;119:1119-25)
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Prognostic value of the Quantified Expression of p185c-erbb2 in non–small cell lung cancer
The Journal of thoracic and cardiovascular surgery, 2000Co-Authors: Ramón Cantero, Antonio J. Torres, M.l. Maestro, F Hernando, M. Sanz, V. Del Barco, Ana M. Gómez, Cristina Fernández, José L. BalibreaAbstract:Abstract Background: We sought to assess the relationship between tissue concentration of erb -b-2 or neu oncogene-encoded protein (p185 neu ) with overall survival in patients with non–small cell lung cancer. Methods: Levels of protein p185 neu were determined in 102 patients with the diagnosis of non–small cell lung cancer. Concentration of p185 neu protein was determined by using enzyme immunoassay and evaluated by using several variables. The relative prognostic importance of this marker and its influence on other prognostic factors was evaluated by using the Cox regression model. Results: The mean p185 neu value in these samples was 250 ± 200 U/mg (95% confidence interval, 210-290). This distinguished two groups within the tumoral population: those with less than 350 U/mg and those with 350 U/mg or greater (80th percentile). Multivariable analysis established an independent prognostic value for protein p185 neu . Patients with p185 neu values of the 80th percentile or greater had a risk of death that was 2.11-fold (95% confidence interval, 1.10-4.05) that of patients with values of less than 350 U/mg ( P = .03), and increases in the neu oncogene of 100 U/mg increased the probability of death by 17% ( P = .02; 95% confidence interval, 1.04-1.31). Conclusion: This study shows that the p185 neu Expression is an objective and comparable variable for the assessment of phenotypic aggressivity in non–small cell lung cancer, and in the future, it could be included in daily clinical practice. (J Thorac Cardiovasc Surg 2000;119:1119-25)
Anton Crombach - One of the best experts on this subject based on the ideXlab platform.
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High-resolution gene Expression data from blastoderm embryos of the scuttle fly Megaselia abdita
Scientific Data, 2015Co-Authors: Karl R Wotton, Anton Crombach, Eva Jiménez-guri, Damjan Cicin-sain, Johannes JaegerAbstract:Design Type(s) parallel group design • RNA Interference Measurement Type(s) transcription profiling assay Technology Type(s) in-situ hybridization Factor Type(s) gene list Sample Characteristic(s) Megaselia abdita Machine-accessible metadata file describing the reported data (ISA-Tab format) Gap genes are involved in segment determination during early development in dipteran insects (flies, midges, and mosquitoes). We carried out a systematic quantitative comparative analysis of the gap gene network across different dipteran species. Our work provides mechanistic insights into the evolution of this pattern-forming network. As a central component of our project, we created a high-resolution quantitative spatio-temporal data set of gap and maternal co-ordinate gene Expression in the blastoderm embryo of the non-drosophilid scuttle fly, Megaselia abdita. Our data include Expression patterns in both wild-type and RNAi-treated embryos. The data—covering 10 genes, 10 time points, and over 1,000 individual embryos—consist of original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries, and integrated Expression patterns, plus metadata and intermediate processing steps. These data provide a valuable resource for researchers interested in the comparative study of gene regulatory networks and pattern formation, an essential step towards a more quantitative and mechanistic understanding of developmental evolution.
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superfly a comparative database for Quantified spatio temporal gene Expression patterns in early dipteran embryos
Nucleic Acids Research, 2015Co-Authors: Damjan Cicinsain, Antonio Hermoso Pulido, Anton Crombach, Karl R Wotton, Eva Jimenezguri, Jeanfrancois Taly, Guglielmo Roma, Johannes JaegerAbstract:We present SuperFly (http://superfly.crg.eu), a relational database for Quantified spatio-temporal Expression data of segmentation genes during early development in different species of dipteran insects (flies, midges and mosquitoes). SuperFly has a special focus on emerging non-drosophilid model systems. The database currently includes data of high spatio-temporal resolution for three species: the vinegar fly Drosophila melanogaster, the scuttle fly Megaselia abdita and the moth midge Clogmia albipunctata. At this point, SuperFly covers up to 9 genes and 16 time points per species, with a total of 1823 individual embryos. It provides an intuitive web interface, enabling the user to query and access original embryo images, Quantified Expression profiles, extracted positions of Expression boundaries and integrated datasets, plus metadata and intermediate processing steps. SuperFly is a valuable new resource for the quantitative comparative study of gene Expression patterns across dipteran species. Moreover, it provides an interesting test set for systems biologists interested in fitting mathematical gene network models to data. Both of these aspects are essential ingredients for progress toward a more quantitative and mechanistic understanding of developmental evolution.
Ramón Cantero - One of the best experts on this subject based on the ideXlab platform.
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prognostic value of the Quantified Expression of p185c erbb2 in non small cell lung cancer
The Journal of Thoracic and Cardiovascular Surgery, 2000Co-Authors: Ramón Cantero, Antonio J. Torres, M.l. Maestro, F Hernando, M. Sanz, V. Del Barco, Ana M. Gómez, Cristina Fernández, José L. BalibreaAbstract:Abstract Background: We sought to assess the relationship between tissue concentration of erb -b-2 or neu oncogene-encoded protein (p185 neu ) with overall survival in patients with non–small cell lung cancer. Methods: Levels of protein p185 neu were determined in 102 patients with the diagnosis of non–small cell lung cancer. Concentration of p185 neu protein was determined by using enzyme immunoassay and evaluated by using several variables. The relative prognostic importance of this marker and its influence on other prognostic factors was evaluated by using the Cox regression model. Results: The mean p185 neu value in these samples was 250 ± 200 U/mg (95% confidence interval, 210-290). This distinguished two groups within the tumoral population: those with less than 350 U/mg and those with 350 U/mg or greater (80th percentile). Multivariable analysis established an independent prognostic value for protein p185 neu . Patients with p185 neu values of the 80th percentile or greater had a risk of death that was 2.11-fold (95% confidence interval, 1.10-4.05) that of patients with values of less than 350 U/mg ( P = .03), and increases in the neu oncogene of 100 U/mg increased the probability of death by 17% ( P = .02; 95% confidence interval, 1.04-1.31). Conclusion: This study shows that the p185 neu Expression is an objective and comparable variable for the assessment of phenotypic aggressivity in non–small cell lung cancer, and in the future, it could be included in daily clinical practice. (J Thorac Cardiovasc Surg 2000;119:1119-25)
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Prognostic value of the Quantified Expression of p185c-erbb2 in non–small cell lung cancer
The Journal of thoracic and cardiovascular surgery, 2000Co-Authors: Ramón Cantero, Antonio J. Torres, M.l. Maestro, F Hernando, M. Sanz, V. Del Barco, Ana M. Gómez, Cristina Fernández, José L. BalibreaAbstract:Abstract Background: We sought to assess the relationship between tissue concentration of erb -b-2 or neu oncogene-encoded protein (p185 neu ) with overall survival in patients with non–small cell lung cancer. Methods: Levels of protein p185 neu were determined in 102 patients with the diagnosis of non–small cell lung cancer. Concentration of p185 neu protein was determined by using enzyme immunoassay and evaluated by using several variables. The relative prognostic importance of this marker and its influence on other prognostic factors was evaluated by using the Cox regression model. Results: The mean p185 neu value in these samples was 250 ± 200 U/mg (95% confidence interval, 210-290). This distinguished two groups within the tumoral population: those with less than 350 U/mg and those with 350 U/mg or greater (80th percentile). Multivariable analysis established an independent prognostic value for protein p185 neu . Patients with p185 neu values of the 80th percentile or greater had a risk of death that was 2.11-fold (95% confidence interval, 1.10-4.05) that of patients with values of less than 350 U/mg ( P = .03), and increases in the neu oncogene of 100 U/mg increased the probability of death by 17% ( P = .02; 95% confidence interval, 1.04-1.31). Conclusion: This study shows that the p185 neu Expression is an objective and comparable variable for the assessment of phenotypic aggressivity in non–small cell lung cancer, and in the future, it could be included in daily clinical practice. (J Thorac Cardiovasc Surg 2000;119:1119-25)
