The Experts below are selected from a list of 137499 Experts worldwide ranked by ideXlab platform
Beste Calimlioglu - One of the best experts on this subject based on the ideXlab platform.
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Kazim Yalcin ArgaAbstract:Abstract Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a “systems medicine” approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein–Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein–Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common sig...
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
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Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein–Protein Interaction Data
OMICS: A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
Kazim Yalcin Arga - One of the best experts on this subject based on the ideXlab platform.
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Kazim Yalcin ArgaAbstract:Abstract Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a “systems medicine” approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein–Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein–Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common sig...
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
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Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein–Protein Interaction Data
OMICS: A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
Anne-claude Gingras - One of the best experts on this subject based on the ideXlab platform.
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a web tool for visualizing quantitative Protein Protein Interaction Data
Proteomics, 2015Co-Authors: James D.r. Knight, Guomin Liu, Jian Ping Zhang, Adrian Pasculescu, Hyungwon Choi, Anne-claude GingrasAbstract:Quantitative Interaction proteomics Data can be a challenge to efficiently analyze and subsequently present to an audience in a simple and easy to understand format that still conveys sufficient levels of information. Here we present freely accessible and open-source web tools for displaying multiple parameters from quantitative Protein-Protein Interaction Data sets in a visually intuitive format. Given a set of "bait" Proteins with detected "prey" Interactions, dot plots can be generated to display absolute spectral counts for the preys, relative spectral counts between baits and confidence levels for the Interactions (e.g. as determined by SAINTexpress). Additional tools are available for displaying fold change results between numerous baits with their associated confidence level (e.g. resulting from intensity measurements) and pairwise bait analyses displaying spectral counts, confidence score and fold change differences in a scatter plot format. These tools make it easy for the user to identify important Interaction changes, interpret their Data, and present this information to others in an intuitive way.
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A web‐tool for visualizing quantitative Protein–Protein Interaction Data
PROTEOMICS, 2015Co-Authors: James D.r. Knight, Guomin Liu, Jian Ping Zhang, Adrian Pasculescu, Hyungwon Choi, Anne-claude GingrasAbstract:Quantitative Interaction proteomics Data can be a challenge to efficiently analyze and subsequently present to an audience in a simple and easy to understand format that still conveys sufficient levels of information. Here we present freely accessible and open-source web tools for displaying multiple parameters from quantitative Protein-Protein Interaction Data sets in a visually intuitive format. Given a set of "bait" Proteins with detected "prey" Interactions, dot plots can be generated to display absolute spectral counts for the preys, relative spectral counts between baits and confidence levels for the Interactions (e.g. as determined by SAINTexpress). Additional tools are available for displaying fold change results between numerous baits with their associated confidence level (e.g. resulting from intensity measurements) and pairwise bait analyses displaying spectral counts, confidence score and fold change differences in a scatter plot format. These tools make it easy for the user to identify important Interaction changes, interpret their Data, and present this information to others in an intuitive way.
Kubra Karagoz - One of the best experts on this subject based on the ideXlab platform.
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Kazim Yalcin ArgaAbstract:Abstract Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a “systems medicine” approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein–Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein–Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common sig...
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
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Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein–Protein Interaction Data
OMICS: A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
Tuba Sevimoglu - One of the best experts on this subject based on the ideXlab platform.
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Kazim Yalcin ArgaAbstract:Abstract Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a “systems medicine” approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein–Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein–Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common sig...
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tissue specific molecular biomarker signatures of type 2 diabetes an integrative analysis of transcriptomics and Protein Protein Interaction Data
Omics A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
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Tissue-Specific Molecular Biomarker Signatures of Type 2 Diabetes: An Integrative Analysis of Transcriptomics and Protein–Protein Interaction Data
OMICS: A Journal of Integrative Biology, 2015Co-Authors: Beste Calimlioglu, Kubra Karagoz, Tuba Sevimoglu, Elif Kilic, Esra Gov, Kazim Yalcin ArgaAbstract:Type 2 diabetes mellitus is a major global public health burden. A complex metabolic disease, type 2 diabetes affects multiple different tissues, demanding a "systems medicine" approach to biomarker and novel diagnostic discovery, not to mention Data integration across omics-es. In the present study, transcriptomics Data from different tissues including beta-cells, pancreatic islets, arterial tissue, peripheral blood mononuclear cells, liver, and skeletal muscle of 228 samples were integrated with Protein-Protein Interaction Data and genome scale metabolic models to unravel the molecular and tissue-specific biomarker signatures of type 2 diabetes mellitus. Classifying differentially expressed genes, reconstruction and topological analysis of active Protein-Protein Interaction subnetworks indicated that genomic reprogramming depends on the type of tissue, whereas there are common signatures at different levels. Among all tissue and cell types, Mannosidase Alpha Class 1A Member 2 was the common signature at genome level, and activation-ppara reaction, which stimulates a nuclear receptor Protein, was found out as the mutual reporter at metabolic level. Moreover, miR-335 and miR-16-5p came into prominence in regulation of transcription at different tissues. On the other hand, distinct signatures were observed for different tissues at the metabolome level. Various coenzyme-A derivatives were significantly enriched metabolites in pancreatic islets, whereas skeletal muscle was enriched for cholesterol, malate, L-carnitine, and several amino acids. Results have showed utmost importance concerning relations between T2D and cancer, blood coagulation, neurodegenerative diseases, and specific metabolic and signaling pathways.
