The Experts below are selected from a list of 360 Experts worldwide ranked by ideXlab platform
Anil G Jegga - One of the best experts on this subject based on the ideXlab platform.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Background Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses. For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate Genes in a training-test schema. Using a list of known disease-related Genes from our earlier study as a training set ("seeds"), and the rest of the known Genes as a test list, we perform large-scale cross validation to rank the candidate Genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Even though network-based methods are Generally not as effective as integrated functional annotation-based methods for disease candidate Gene prioritization, in a one-to-one comparison, PPIN-based candidate Gene prioritization performs better than all other Gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate Gene prioritization.
Silvia Schauer - One of the best experts on this subject based on the ideXlab platform.
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growth retardation impaired triacylglycerol catabolism hepatic steatosis and lethal skin barrier defect in mice lacking comparative Gene Identification 58 cgi 58
Journal of Biological Chemistry, 2010Co-Authors: Franz P W Radner, Gerald Rechberger, Ingo Streith, Gabriele Schoiswohl, Martina Schweiger, Manju Kumari, Thomas O Eichmann, Harald Koefeler, Sandra Eder, Silvia SchauerAbstract:Comparative Gene Identification-58 (CGI-58), also designated as α/β-hydrolase domain containing-5 (ABHD-5), is a lipid droplet-associated protein that activates adipose triglyceride lipase (ATGL) and acylates lysophosphatidic acid. Activation of ATGL initiates the hydrolytic catabolism of cellular triacylglycerol (TG) stores to glycerol and nonesterified fatty acids. Mutations in both ATGL and CGI-58 cause “neutral lipid storage disease” characterized by massive accumulation of TG in various tissues. The analysis of CGI-58-deficient (Cgi-58−/−) mice, presented in this study, reveals a dual function of CGI-58 in lipid metabolism. First, systemic TG accumulation and severe hepatic steatosis in newborn Cgi-58−/− mice establish a limiting role for CGI-58 in ATGL-mediated TG hydrolysis and supply of nonesterified fatty acids as energy substrate. Second, a severe skin permeability barrier defect uncovers an essential ATGL-independent role of CGI-58 in skin lipid metabolism. The neonatal lethal skin barrier defect is linked to an impaired hydrolysis of epidermal TG. As a consequence, sequestration of fatty acids in TG prevents the synthesis of acylceramides, which are essential lipid precursors for the formation of a functional skin permeability barrier. This mechanism may also underlie the pathoGenesis of ichthyosis in neutral lipid storage disease patients lacking functional CGI-58.
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growth retardation impaired triacylglycerol catabolism hepatic steatosis and lethal skin barrier defect in mice lacking comparative Gene Identification 58 cgi 58
Journal of Biological Chemistry, 2010Co-Authors: Franz P W Radner, Gerald Rechberger, Ingo Streith, Gabriele Schoiswohl, Martina Schweiger, Manju Kumari, Thomas O Eichmann, Harald Koefeler, Sandra Eder, Silvia SchauerAbstract:Comparative Gene Identification-58 (CGI-58), also designated as alpha/beta-hydrolase domain containing-5 (ABHD-5), is a lipid droplet-associated protein that activates adipose triglyceride lipase (ATGL) and acylates lysophosphatidic acid. Activation of ATGL initiates the hydrolytic catabolism of cellular triacylglycerol (TG) stores to glycerol and nonesterified fatty acids. Mutations in both ATGL and CGI-58 cause "neutral lipid storage disease" characterized by massive accumulation of TG in various tissues. The analysis of CGI-58-deficient (Cgi-58(-/-)) mice, presented in this study, reveals a dual function of CGI-58 in lipid metabolism. First, systemic TG accumulation and severe hepatic steatosis in newborn Cgi-58(-/-) mice establish a limiting role for CGI-58 in ATGL-mediated TG hydrolysis and supply of nonesterified fatty acids as energy substrate. Second, a severe skin permeability barrier defect uncovers an essential ATGL-independent role of CGI-58 in skin lipid metabolism. The neonatal lethal skin barrier defect is linked to an impaired hydrolysis of epidermal TG. As a consequence, sequestration of fatty acids in TG prevents the synthesis of acylceramides, which are essential lipid precursors for the formation of a functional skin permeability barrier. This mechanism may also underlie the pathoGenesis of ichthyosis in neutral lipid storage disease patients lacking functional CGI-58.
Bruce J Aronow - One of the best experts on this subject based on the ideXlab platform.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Background Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses. For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate Genes in a training-test schema. Using a list of known disease-related Genes from our earlier study as a training set ("seeds"), and the rest of the known Genes as a test list, we perform large-scale cross validation to rank the candidate Genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Even though network-based methods are Generally not as effective as integrated functional annotation-based methods for disease candidate Gene prioritization, in a one-to-one comparison, PPIN-based candidate Gene prioritization performs better than all other Gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate Gene prioritization.
Jing Chen - One of the best experts on this subject based on the ideXlab platform.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Background Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses.
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disease candidate Gene Identification and prioritization using protein interaction networks
BMC Bioinformatics, 2009Co-Authors: Jing Chen, Bruce J Aronow, Anil G JeggaAbstract:Although most of the current disease candidate Gene Identification and prioritization methods depend on functional annotations, the coverage of the Gene functional annotations is a limiting factor. In the current study, we describe a candidate Gene prioritization method that is entirely based on protein-protein interaction network (PPIN) analyses. For the first time, extended versions of the PageRank and HITS algorithms, and the K-Step Markov method are applied to prioritize disease candidate Genes in a training-test schema. Using a list of known disease-related Genes from our earlier study as a training set ("seeds"), and the rest of the known Genes as a test list, we perform large-scale cross validation to rank the candidate Genes and also evaluate and compare the performance of our approach. Under appropriate settings – for example, a back probability of 0.3 for PageRank with Priors and HITS with Priors, and step size 6 for K-Step Markov method – the three methods achieved a comparable AUC value, suggesting a similar performance. Even though network-based methods are Generally not as effective as integrated functional annotation-based methods for disease candidate Gene prioritization, in a one-to-one comparison, PPIN-based candidate Gene prioritization performs better than all other Gene features or annotations. Additionally, we demonstrate that methods used for studying both social and Web networks can be successfully used for disease candidate Gene prioritization.
Martina Schweiger - One of the best experts on this subject based on the ideXlab platform.
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the n terminal region of comparative Gene Identification 58 cgi 58 is important for lipid droplet binding and activation of adipose triglyceride lipase
Journal of Biological Chemistry, 2010Co-Authors: Astrid Gruber, Gabriele Schoiswohl, Martina Schweiger, Manju Kumari, Irina Cornaciu, Achim Lass, Margret Poeschl, Christina Eder, Heimo Wolinski, Sepp D KohlweinAbstract:Abstract In mammals, excess energy is stored in the form of triacylglycerol primarily in lipid droplets of white adipose tissue. The first step of lipolysis (i.e. the mobilization of fat stores) is catalyzed by adipose triglyceride lipase (ATGL). The enzymatic activity of ATGL is strongly enhanced by CGI-58 (comparative Gene Identification-58), and the loss of either ATGL or CGI-58 function causes systemic triglyceride accumulation in humans and mice. However, the mechanism by which CGI-58 stimulates ATGL activity is unknown. To gain insight into CGI-58 function using structural features of the protein, we Generated a three-dimensional homology model based on sequence similarity with other proteins. Interestingly, the model of CGI-58 revealed that the N terminus forms an extension of the otherwise compact structure of the protein. This N-terminal region (amino acids 1–30) harbors a lipophilic tryptophan-rich stretch, which affects the localization of the protein. 1H NMR experiments revealed strong interaction between the N-terminal peptide and dodecylphosphocholine micelles as a lipid droplet-mimicking system. A role for this N-terminal region of CGI-58 in lipid droplet binding was further strengthened by localization studies in cultured cells. Although wild-type CGI-58 localizes to the lipid droplet, the N-terminally truncated fragments of CGI-58 are dispersed in the cytoplasm. Moreover, CGI-58 lacking the N-terminal extension loses the ability to stimulate ATGL, implying that the ability of CGI-58 to activate ATGL is linked to correct localization. In summary, our study shows that the N-terminal, Trp-rich region of CGI-58 is essential for correct localization and ATGL-activating function of CGI-58.
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growth retardation impaired triacylglycerol catabolism hepatic steatosis and lethal skin barrier defect in mice lacking comparative Gene Identification 58 cgi 58
Journal of Biological Chemistry, 2010Co-Authors: Franz P W Radner, Gerald Rechberger, Ingo Streith, Gabriele Schoiswohl, Martina Schweiger, Manju Kumari, Thomas O Eichmann, Harald Koefeler, Sandra Eder, Silvia SchauerAbstract:Comparative Gene Identification-58 (CGI-58), also designated as α/β-hydrolase domain containing-5 (ABHD-5), is a lipid droplet-associated protein that activates adipose triglyceride lipase (ATGL) and acylates lysophosphatidic acid. Activation of ATGL initiates the hydrolytic catabolism of cellular triacylglycerol (TG) stores to glycerol and nonesterified fatty acids. Mutations in both ATGL and CGI-58 cause “neutral lipid storage disease” characterized by massive accumulation of TG in various tissues. The analysis of CGI-58-deficient (Cgi-58−/−) mice, presented in this study, reveals a dual function of CGI-58 in lipid metabolism. First, systemic TG accumulation and severe hepatic steatosis in newborn Cgi-58−/− mice establish a limiting role for CGI-58 in ATGL-mediated TG hydrolysis and supply of nonesterified fatty acids as energy substrate. Second, a severe skin permeability barrier defect uncovers an essential ATGL-independent role of CGI-58 in skin lipid metabolism. The neonatal lethal skin barrier defect is linked to an impaired hydrolysis of epidermal TG. As a consequence, sequestration of fatty acids in TG prevents the synthesis of acylceramides, which are essential lipid precursors for the formation of a functional skin permeability barrier. This mechanism may also underlie the pathoGenesis of ichthyosis in neutral lipid storage disease patients lacking functional CGI-58.
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growth retardation impaired triacylglycerol catabolism hepatic steatosis and lethal skin barrier defect in mice lacking comparative Gene Identification 58 cgi 58
Journal of Biological Chemistry, 2010Co-Authors: Franz P W Radner, Gerald Rechberger, Ingo Streith, Gabriele Schoiswohl, Martina Schweiger, Manju Kumari, Thomas O Eichmann, Harald Koefeler, Sandra Eder, Silvia SchauerAbstract:Comparative Gene Identification-58 (CGI-58), also designated as alpha/beta-hydrolase domain containing-5 (ABHD-5), is a lipid droplet-associated protein that activates adipose triglyceride lipase (ATGL) and acylates lysophosphatidic acid. Activation of ATGL initiates the hydrolytic catabolism of cellular triacylglycerol (TG) stores to glycerol and nonesterified fatty acids. Mutations in both ATGL and CGI-58 cause "neutral lipid storage disease" characterized by massive accumulation of TG in various tissues. The analysis of CGI-58-deficient (Cgi-58(-/-)) mice, presented in this study, reveals a dual function of CGI-58 in lipid metabolism. First, systemic TG accumulation and severe hepatic steatosis in newborn Cgi-58(-/-) mice establish a limiting role for CGI-58 in ATGL-mediated TG hydrolysis and supply of nonesterified fatty acids as energy substrate. Second, a severe skin permeability barrier defect uncovers an essential ATGL-independent role of CGI-58 in skin lipid metabolism. The neonatal lethal skin barrier defect is linked to an impaired hydrolysis of epidermal TG. As a consequence, sequestration of fatty acids in TG prevents the synthesis of acylceramides, which are essential lipid precursors for the formation of a functional skin permeability barrier. This mechanism may also underlie the pathoGenesis of ichthyosis in neutral lipid storage disease patients lacking functional CGI-58.