The Experts below are selected from a list of 50163 Experts worldwide ranked by ideXlab platform
Douglas J Lacount - One of the best experts on this subject based on the ideXlab platform.
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a Protein Interaction Network of the malaria parasite plasmodium falciparum
Nature, 2005Co-Authors: Rakesh Chettier, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, Douglas J Lacount, M. Vignali, Lori W. Schoenfeld, Sudhir SahasrabudheAbstract:A powerful approach for understanding Protein function is to identify which Proteins bind to each other, as Protein complexes are at the heart of most biological processes. Protein–Protein Interactions have now been mapped for one quarter of the malaria parasite's Proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium Network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel Protein Network, which therefore has a good chance of providing drug targets unique to the malaria parasite. Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually1. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein–Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations2 were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
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A Protein Interaction Network of the malaria parasite Plasmodium falciparum
Nature, 2005Co-Authors: Douglas J Lacount, Rakesh Chettier, Irene Ota, Sudhir Sahasrabudhe, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, M. Vignali, Lori W. Schoenfeld, Cornelia KurschnerAbstract:Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein-Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
Sudhir Sahasrabudhe - One of the best experts on this subject based on the ideXlab platform.
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a Protein Interaction Network of the malaria parasite plasmodium falciparum
Nature, 2005Co-Authors: Rakesh Chettier, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, Douglas J Lacount, M. Vignali, Lori W. Schoenfeld, Sudhir SahasrabudheAbstract:A powerful approach for understanding Protein function is to identify which Proteins bind to each other, as Protein complexes are at the heart of most biological processes. Protein–Protein Interactions have now been mapped for one quarter of the malaria parasite's Proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium Network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel Protein Network, which therefore has a good chance of providing drug targets unique to the malaria parasite. Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually1. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein–Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations2 were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
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A Protein Interaction Network of the malaria parasite Plasmodium falciparum
Nature, 2005Co-Authors: Douglas J Lacount, Rakesh Chettier, Irene Ota, Sudhir Sahasrabudhe, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, M. Vignali, Lori W. Schoenfeld, Cornelia KurschnerAbstract:Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein-Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
Lori W. Schoenfeld - One of the best experts on this subject based on the ideXlab platform.
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a Protein Interaction Network of the malaria parasite plasmodium falciparum
Nature, 2005Co-Authors: Rakesh Chettier, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, Douglas J Lacount, M. Vignali, Lori W. Schoenfeld, Sudhir SahasrabudheAbstract:A powerful approach for understanding Protein function is to identify which Proteins bind to each other, as Protein complexes are at the heart of most biological processes. Protein–Protein Interactions have now been mapped for one quarter of the malaria parasite's Proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium Network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel Protein Network, which therefore has a good chance of providing drug targets unique to the malaria parasite. Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually1. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein–Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations2 were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
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A Protein Interaction Network of the malaria parasite Plasmodium falciparum
Nature, 2005Co-Authors: Douglas J Lacount, Rakesh Chettier, Irene Ota, Sudhir Sahasrabudhe, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, M. Vignali, Lori W. Schoenfeld, Cornelia KurschnerAbstract:Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein-Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
Russell Bell - One of the best experts on this subject based on the ideXlab platform.
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a human Protein Interaction Network shows conservation of aging processes between human and invertebrate species
PLOS Genetics, 2009Co-Authors: Russell Bell, Rakesh Chettier, Alan Hubbard, Di Chen, John P Miller, Pankaj Kapahi, Mark A Tarnopolsky, Sudhir Sahasrabuhde, Simon MelovAbstract:We have mapped a Protein Interaction Network of human homologs of Proteins that modify longevity in invertebrate species. This Network is derived from a proteome-scale human Protein Interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity Network is composed of 175 human homologs of Proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human Proteins that interact with these homologs. Overall, the Network consists of 3,271 binary Interactions among 2,338 unique Proteins. A comparison of the average node degree of the human longevity homologs with random sets of Proteins in the Core Network indicates that human homologs of longevity Proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that Proteins in this Network are significantly more connected than would be expected by chance. To examine the relationship of this Network to human aging phenotypes, we compared the genes encoding longevity Network Proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity Protein homologs and their interactors, we observed enrichments for differentially expressed genes in the Network. To determine whether homologs of human longevity interacting Proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting Proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity Protein Interaction Network presented here is enriched for novel conserved longevity Proteins.
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a Protein Interaction Network of the malaria parasite plasmodium falciparum
Nature, 2005Co-Authors: Rakesh Chettier, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, Douglas J Lacount, M. Vignali, Lori W. Schoenfeld, Sudhir SahasrabudheAbstract:A powerful approach for understanding Protein function is to identify which Proteins bind to each other, as Protein complexes are at the heart of most biological processes. Protein–Protein Interactions have now been mapped for one quarter of the malaria parasite's Proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium Network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel Protein Network, which therefore has a good chance of providing drug targets unique to the malaria parasite. Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually1. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein–Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations2 were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
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A Protein Interaction Network of the malaria parasite Plasmodium falciparum
Nature, 2005Co-Authors: Douglas J Lacount, Rakesh Chettier, Irene Ota, Sudhir Sahasrabudhe, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, M. Vignali, Lori W. Schoenfeld, Cornelia KurschnerAbstract:Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein-Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
Rakesh Chettier - One of the best experts on this subject based on the ideXlab platform.
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a human Protein Interaction Network shows conservation of aging processes between human and invertebrate species
PLOS Genetics, 2009Co-Authors: Russell Bell, Rakesh Chettier, Alan Hubbard, Di Chen, John P Miller, Pankaj Kapahi, Mark A Tarnopolsky, Sudhir Sahasrabuhde, Simon MelovAbstract:We have mapped a Protein Interaction Network of human homologs of Proteins that modify longevity in invertebrate species. This Network is derived from a proteome-scale human Protein Interaction Core Network generated through unbiased high-throughput yeast two-hybrid searches. The longevity Network is composed of 175 human homologs of Proteins known to confer increased longevity through loss of function in yeast, nematode, or fly, and 2,163 additional human Proteins that interact with these homologs. Overall, the Network consists of 3,271 binary Interactions among 2,338 unique Proteins. A comparison of the average node degree of the human longevity homologs with random sets of Proteins in the Core Network indicates that human homologs of longevity Proteins are highly connected hubs with a mean node degree of 18.8 partners. Shortest path length analysis shows that Proteins in this Network are significantly more connected than would be expected by chance. To examine the relationship of this Network to human aging phenotypes, we compared the genes encoding longevity Network Proteins to genes known to be changed transcriptionally during aging in human muscle. In the case of both the longevity Protein homologs and their interactors, we observed enrichments for differentially expressed genes in the Network. To determine whether homologs of human longevity interacting Proteins can modulate life span in invertebrates, homologs of 18 human FRAP1 interacting Proteins showing significant changes in human aging muscle were tested for effects on nematode life span using RNAi. Of 18 genes tested, 33% extended life span when knocked-down in Caenorhabditis elegans. These observations indicate that a broad class of longevity genes identified in invertebrate models of aging have relevance to human aging. They also indicate that the longevity Protein Interaction Network presented here is enriched for novel conserved longevity Proteins.
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a Protein Interaction Network of the malaria parasite plasmodium falciparum
Nature, 2005Co-Authors: Rakesh Chettier, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, Douglas J Lacount, M. Vignali, Lori W. Schoenfeld, Sudhir SahasrabudheAbstract:A powerful approach for understanding Protein function is to identify which Proteins bind to each other, as Protein complexes are at the heart of most biological processes. Protein–Protein Interactions have now been mapped for one quarter of the malaria parasite's Proteins. This large data set sheds new light on how parasites infect red blood cells and will be a vital tool for the development of new antimalarial drugs and vaccines. The primary data are freely available on the PlasmoDB database. Suthram et al. have used this new resource and find that the Plasmodium Network has significantly less cross-species similarity than other eukaryotes. Its novel life style is reflected in a novel Protein Network, which therefore has a good chance of providing drug targets unique to the malaria parasite. Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually1. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein–Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations2 were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
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A Protein Interaction Network of the malaria parasite Plasmodium falciparum
Nature, 2005Co-Authors: Douglas J Lacount, Rakesh Chettier, Irene Ota, Sudhir Sahasrabudhe, Amit Phansalkar, Russell Bell, Jay R. Hesselberth, M. Vignali, Lori W. Schoenfeld, Cornelia KurschnerAbstract:Plasmodium falciparum causes the most severe form of malaria and kills up to 2.7 million people annually. Despite the global importance of P. falciparum, the vast majority of its Proteins have not been characterized experimentally. Here we identify P. falciparum Protein-Protein Interactions using a high-throughput version of the yeast two-hybrid assay that circumvents the difficulties in expressing P. falciparum Proteins in Saccharomyces cerevisiae. From more than 32,000 yeast two-hybrid screens with P. falciparum Protein fragments, we identified 2,846 unique Interactions, most of which include at least one previously uncharacterized Protein. Informatic analyses of Network connectivity, coexpression of the genes encoding interacting fragments, and enrichment of specific Protein domains or Gene Ontology annotations were used to identify groups of interacting Proteins, including one implicated in chromatin modification, transcription, messenger RNA stability and ubiquitination, and another implicated in the invasion of host cells. These data constitute the first extensive description of the Protein Interaction Network for this important human pathogen.
