基本信息
浏览量:7
职业迁徙
个人简介
Research:
Systems genomics approaches to identify and validate biological mechanisms underlying cardio-metabolic disease. The association of DNA sequence variation (single nucleotide polymorphisms or SNPs) and gene expression with phenotypic traits represent the core of genome biology. However, the inadequacy of traditional SNP-centric analysis, or individual gene expression profiles for revealing biological mechanisms underlying susceptibility to common disorders necessitates alternative analytic approaches. We apply integrated, ensemble-based bioinformatic strategies (systems genomics) to interrogate the cumulative effects of genetic polymorphisms and gene-set expression patterns in biological mechanisms. These approaches lead to the identification of novel causal mechanisms underlying a variety of cardio-metabolic traits including obesity, type 2 diabetes and coronary artery disease. We follow-up on novel disease-related gene candidates by functional genomics analysis in cell-based and animal model systems.
Nutrigenomics studies to elucidate metabolic responses to nutrient variation. The response of the transcriptome to nutritional cues (e.g. excess or deficiency of nutrients, caloric restriction) allows one to infer metabolic adaptations to altered energy supply. We are broadly interested in understanding the effects of caloric restriction and dietary nutrient restriction in key metabolic tissues in humans and animal models. These studies generate important insights into tissue-specific transcriptomic responses to nutrients in the context of longevity and metabolic health.
Collaborations involving other disease areas. In addition to the above-mentioned research areas related to cardio-metabolic disease and nutrigenomics, we collaborate extensively with national and international investigators for bioinformatic analysis of first-generation ‘omics’ and next-generation sequencing data on diverse research projects in cancer, infectious disease, neurobiology and exercise physiology.
Systems genomics approaches to identify and validate biological mechanisms underlying cardio-metabolic disease. The association of DNA sequence variation (single nucleotide polymorphisms or SNPs) and gene expression with phenotypic traits represent the core of genome biology. However, the inadequacy of traditional SNP-centric analysis, or individual gene expression profiles for revealing biological mechanisms underlying susceptibility to common disorders necessitates alternative analytic approaches. We apply integrated, ensemble-based bioinformatic strategies (systems genomics) to interrogate the cumulative effects of genetic polymorphisms and gene-set expression patterns in biological mechanisms. These approaches lead to the identification of novel causal mechanisms underlying a variety of cardio-metabolic traits including obesity, type 2 diabetes and coronary artery disease. We follow-up on novel disease-related gene candidates by functional genomics analysis in cell-based and animal model systems.
Nutrigenomics studies to elucidate metabolic responses to nutrient variation. The response of the transcriptome to nutritional cues (e.g. excess or deficiency of nutrients, caloric restriction) allows one to infer metabolic adaptations to altered energy supply. We are broadly interested in understanding the effects of caloric restriction and dietary nutrient restriction in key metabolic tissues in humans and animal models. These studies generate important insights into tissue-specific transcriptomic responses to nutrients in the context of longevity and metabolic health.
Collaborations involving other disease areas. In addition to the above-mentioned research areas related to cardio-metabolic disease and nutrigenomics, we collaborate extensively with national and international investigators for bioinformatic analysis of first-generation ‘omics’ and next-generation sequencing data on diverse research projects in cancer, infectious disease, neurobiology and exercise physiology.
研究兴趣
论文共 247 篇作者统计合作学者相似作者
按年份排序按引用量排序主题筛选期刊级别筛选合作者筛选合作机构筛选
时间
引用量
主题
期刊级别
合作者
合作机构
Madhulika Tripathi,Karine Gauthier,Reddemma Sandireddy,Jin Zhou, Priyanka Gupta, Suganya Sakthivel, Nah Jiemin, Kabilesh Arul,Keziah Tikno,Sung-Hee Park, Lijin Wang,Lena Ho,
bioRxiv : the preprint server for biology (2024)
Heidi M. Batdorf, Luz de Luna Lawes, Gabrielle A. Cassagne, Molly S. Fontenot,Innocence C. Harvey, Jeremy T. Richardson,David H. Burk,Samuel D. Dupuy,Michael D. Karlstad,J. Michael Salbaum, Jaroslaw Staszkiewicz,Robbie Beyl,
DIABETES OBESITY & METABOLISM (2024)
Madhulika Tripathi,Karine Gauthier,Reddemma Sandireddy,Jin Zhou, Priyanka Gupta, Suganya Sakthivel, Wei Wen Teo, Yadanar Than Naing,Kabilesh Arul,Keziah Tikno,Sung-Hee Park,Yajun Wu,
biorxiv(2024)
Lidya H. Gebreyesus,Sora Choi, Prince Neequaye, Mattia Mahmoud, Mia Mahmoud, Malvin Ofosu-Boateng, Elizabeth Twum, Daniel O. Nnamani, Lijin Wang, Nour Yadak,Sujoy Ghosh,Frank J. Gonzalez,
Cellsno. 7 (2024): 588
ENDOCRINE PRACTICEno. 2 (2024): 128-134
Diabetesno. Supplement_1 (2023)
引用0浏览0引用
0
0
CRC Press eBookspp.173-206, (2023)
Vetrivel Sengottuvel,Monalisa Hota,Jeongah Oh,Dwight L Galam,Bernice H Wong,Markus R Wenk,Sujoy Ghosh,Federico Torta,David L Silver
Circulationno. Suppl_1 (2023)
引用0浏览0引用
0
0
加载更多
作者统计
合作学者
合作机构
D-Core
- 合作者
- 学生
- 导师
数据免责声明
页面数据均来自互联网公开来源、合作出版商和通过AI技术自动分析结果,我们不对页面数据的有效性、准确性、正确性、可靠性、完整性和及时性做出任何承诺和保证。若有疑问,可以通过电子邮件方式联系我们:report@aminer.cn