1-7 of 7
bioinformatics
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Meeting Abstracts

1464-P: Identification of Candidate Biomarkers for Type 1 Diabetes Mellitus by Bioinformatics Analysis of Pooled Microarray Gene Expression Datasets in Gene Expression Omnibus

KEVIN FENG, SR.
Journal: Diabetes
Diabetes 2023;72(Supplement_1):1464-P
https://doi.org/10.2337/db23-1464-P
Published: 20 June 2023
View article titled, 1464-P: Identification of Candidate Biomarkers for Type 1 Diabetes Mellitus by Bioinformatics Analysis of Pooled Microarray Gene Expression Datasets in Gene Expression Omnibus
Meeting Abstracts

1291-P: Bioinformatics Analysis of Gene Networks Associated with Glucose Variability and Inflammatory Pathways in Diabetes

OLGA V. SAIK, VADIM KLIMONTOV
Journal: Diabetes
Diabetes 2022;71(Supplement_1):1291-P
https://doi.org/10.2337/db22-1291-P
Published: 01 June 2022
View article titled, 1291-P: Bioinformatics Analysis of Gene Networks Associated with Glucose Variability and Inflammatory Pathways in Diabetes
Meeting Abstracts

384-P: Text Mining and Bioinformatic Identification of Genes Linking Glycemic Variability and Impaired Angiogenesis in Diabetes

OLGA V. SAIK, VADIM KLIMONTOV
Journal: Diabetes
Diabetes 2021;70(Supplement_1):384-P
https://doi.org/10.2337/db21-384-P
Published: 01 June 2021
View article titled, 384-P: Text Mining and Bioinformatic Identification of Genes Linking Glycemic Variability and Impaired Angiogenesis in Diabetes
Meeting Abstracts

2098-P: Transcriptomic Changes Associated with Oleate-Induced ß-Cell Proliferation in Rat Islets

ALEXIS VIVOLI, ANNE-LAURE CASTELL, ALAIN PACIS, ROBERT M. SLADEK, JULIEN GHISLAIN, VINCENT POITOUT
Journal: Diabetes
Diabetes 2020;69(Supplement_1):2098-P
https://doi.org/10.2337/db20-2098-P
Published: 01 June 2020
View article titled, 2098-P: Transcriptomic Changes Associated with Oleate-Induced ß-Cell Proliferation in Rat Islets
Meeting Abstracts

1325-P: Effectiveness of Comprehensive Gene Panel-Based Next-Generation Sequencing with Phenotype-Driven Bioinformatics Analysis for Diagnosis of Atypical Diabetes

JUN HOSOE, HIROKO KADOWAKI, FUYUKI MIYA, MINAKA TAKAKURA, HIRONORI WAKI, TAKAYOSHI SASAKO, TAKASHI KATO, TATSUHIKO TSUNODA, NOBUHIRO SHOJIMA, TOSHIMASA YAMAUCHI, TAKASHI KADOWAKI
Journal: Diabetes
Diabetes 2019;68(Supplement_1):1325-P
https://doi.org/10.2337/db19-1325-P
Published: 01 June 2019
View article titled, 1325-P: Effectiveness of Comprehensive Gene Panel-Based Next-Generation Sequencing with Phenotype-Driven Bioinformatics Analysis for Diagnosis of Atypical Diabetes
Journal Articles

Functional Investigations of HNF1A Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population

Laeya Abdoli Najmi, Ingvild Aukrust, Jason Flannick, Janne Molnes, Noel Burtt, Anders Molven, Leif Groop, David Altshuler, Stefan Johansson, Lise Bjørkhaug, Pål Rasmus Njølstad
Journal: Diabetes
Diabetes 2017;66(2):335–346
https://doi.org/10.2337/db16-0460
Published: 29 November 2016
View article titled, Functional Investigations of <em>HNF1A</em> Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population
Open the PDF for Functional Investigations of <em>HNF1A</em> Identify Rare Variants as Risk Factors for Type 2 Diabetes in the General Population in another window
Includes: Supplementary data
Journal Articles

Deep Resequencing Unveils Genetic Architecture of ADIPOQ and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation

Liling L. Warren, Li Li, Matthew R. Nelson, Margaret G. Ehm, Judong Shen, Dana J. Fraser, Jennifer L. Aponte, Keith L. Nangle, Andrew J. Slater, Peter M. Woollard, Matt D. Hall, Simon D. Topp, Xin Yuan, Lon R. Cardon, Stephanie L. Chissoe, Vincent Mooser, Andrew D. Morris, Colin N.A. Palmer, John R. Perry, Timothy M. Frayling, John C. Whittaker, Dawn M. Waterworth
Journal: Diabetes
Diabetes 2012;61(5):1297–1301
https://doi.org/10.2337/db11-0985
Published: 13 April 2012
View article titled, Deep Resequencing Unveils Genetic Architecture of <em>ADIPOQ</em> and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation
Open the PDF for Deep Resequencing Unveils Genetic Architecture of <em>ADIPOQ</em> and Identifies a Novel Low-Frequency Variant Strongly Associated With Adiponectin Variation in another window
Includes: Supplementary data