about
Insulin signaling regulates fatty acid catabolism at the level of CoA activationPrediction of overall survival for patients with metastatic castration-resistant prostate cancer: development of a prognostic model through a crowdsourced challenge with open clinical trial data.Data integration and visualization system for enabling conceptual biology.An integrative approach for biological data mining and visualisation.Detection of molecular paths associated with insulitis and type 1 diabetes in non-obese diabetic mouseAssociation of lipidome remodeling in the adipocyte membrane with acquired obesity in humans.Metabolic regulation in progression to autoimmune diabetesHeterogeneous biological network visualization system: case study in context of medical image data.Mitofusin 2 (Mfn2) links mitochondrial and endoplasmic reticulum function with insulin signaling and is essential for normal glucose homeostasis.Metabolite profiling of the carnivorous pitcher plants Darlingtonia and Sarracenia.Accumulated Metabolites of Hydroxybutyric Acid Serve as Diagnostic and Prognostic Biomarkers of Ovarian High-Grade Serous Carcinomas.Characterization of microbial metabolism of Syrah grape products in an in vitro colon model using targeted and non-targeted analytical approaches.Cord serum lipidome in prediction of islet autoimmunity and type 1 diabetesPrediction of non-alcoholic fatty-liver disease and liver fat content by serum molecular lipidsEarly metabolic markers identify potential targets for the prevention of type 2 diabetesSeed-effect modeling improves the consistency of genome-wide loss-of-function screens and identifies synthetic lethal vulnerabilities in cancer cells.C-SPADE: a web-tool for interactive analysis and visualization of drug screening experiments through compound-specific bioactivity dendrograms.From drug response profiling to target addiction scoring in cancer cell models.Noninvasive Detection of Nonalcoholic Steatohepatitis Using Clinical Markers and Circulating Levels of Lipids and Metabolites.The gut microbiota modulates host energy and lipid metabolism in mice.Erratum: Crowdsourced assessment of common genetic contribution to predicting anti-TNF treatment response in rheumatoid arthritis.A Community Challenge for Inferring Genetic Predictors of Gene Essentialities through Analysis of a Functional Screen of Cancer Cell Lines.Circulating triacylglycerol signatures in nonalcoholic fatty liver disease associated with the I148M variant in PNPLA3 and with obesity.Dynamic network topology changes in functional modules predict responses to oxidative stress in yeast.Drug metabolome of the simvastatin formed by human intestinal microbiota in vitro.Drug Target Commons: A Community Effort to Build a Consensus Knowledge Base for Drug-Target Interactions.Algorithms and tools for the preprocessing of LC–MS metabolomics dataMPEA—metabolite pathway enrichment analysisValidation and Automation of a High-Throughput Multitargeted Method for Semiquantification of Endogenous Metabolites from Different Biological Matrices Using Tandem Mass Spectrometry1-Hour Post-OGTT Glucose Improves the Early Prediction of Type 2 Diabetes by Clinical and Metabolic Markers
P50
Q27334898-246203E3-C2A3-4270-8DEE-1A9CBB8729B6Q30490354-78A054DB-C1C9-438C-A146-5974AEF959EFQ30992240-95FB5B71-9B12-480E-BD3C-5B2BE85C537DQ31152043-3704695E-08D8-4DC5-9D19-CE893DD02ED7Q33508234-7A71868C-25D6-401E-B857-212ADE5D34ADQ33930538-74EDBA12-5945-4271-9223-CCAA11670BFCQ34064185-D49F05A9-7C91-44DF-8371-59ECA52A1F3AQ34097213-FA30EF72-6B2F-40BD-AE0B-8E16C4FBF462Q35887283-BB76DE79-04E3-43DD-82D8-A3F6E5E1BE2AQ36286446-7603A9B8-8B1E-47C3-A339-19CD4B6E2163Q36603235-6240ED4E-7458-4B7F-84F2-E27CFD2F8F53Q36611920-3AB95D46-8269-45BE-A2A5-FE0EED913F85Q37110596-1DA3DF11-D36D-4A90-880F-9485EBED7134Q37150162-6E4A88ED-BB3E-4F2F-9B33-85544D23FA9FQ38673034-731139B3-3668-4D08-B53E-E23380D272F6Q38676328-D7E5B983-B656-4F61-B38D-CBD2283C2B86Q38803953-5452B0EB-8247-4FDA-AC01-38B49AD1EEBCQ38830137-A9E324C1-C6CC-4E60-88E1-97B771D59E1AQ39673566-3E888435-5AD5-41E7-B87C-4BC1F415F9B4Q39993460-BC0289E5-E73B-4FED-B20F-8F6525649732Q41449798-9336A750-F34A-457A-A5AA-6C7356BC3525Q42695612-91BA30D4-F2C4-4A22-8D36-467CC73AC1CFQ43491389-40D7C8DC-937B-48E8-AD8B-66EF333FF0EAQ45281809-4841384D-3A22-420B-A018-556FD7B8F7AFQ46231097-93495855-B02C-42A8-A267-6C596996378EQ47252031-3DB5CCBB-95E9-45D9-909F-4423587B19AFQ57012158-F549C936-2F63-4405-88E3-E4DABC6183DFQ57012182-E299E801-C0CB-43A2-B47E-335204091432Q58799949-0B6EE130-B1FA-4250-922B-3BD2B0934B68Q93177055-2D9C1FCE-12A5-4B22-B498-367E2D21B7B7
P50
description
researcher
@en
wetenschapper
@nl
հետազոտող
@hy
name
Peddinti V. Gopalacharyulu
@ast
Peddinti V. Gopalacharyulu
@en
Peddinti V. Gopalacharyulu
@es
Peddinti V. Gopalacharyulu
@nl
Peddinti V. Gopalacharyulu
@sl
type
label
Peddinti V. Gopalacharyulu
@ast
Peddinti V. Gopalacharyulu
@en
Peddinti V. Gopalacharyulu
@es
Peddinti V. Gopalacharyulu
@nl
Peddinti V. Gopalacharyulu
@sl
altLabel
Gopalacharyulu Peddinti
@en
Peddinti Gopalacharyulu
@en
Peddinti V Gopalacharyulu
@en
Venkata Gopalacharyulu Peddinti
@en
prefLabel
Peddinti V. Gopalacharyulu
@ast
Peddinti V. Gopalacharyulu
@en
Peddinti V. Gopalacharyulu
@es
Peddinti V. Gopalacharyulu
@nl
Peddinti V. Gopalacharyulu
@sl
P1053
G-4872-2016
P106
P1153
10039154200
P2456
P31
P3829
P3835
gopal-peddinti
P496
0000-0002-8767-968X