蛋白质组学
代谢组学
计算生物学
鉴定(生物学)
重性抑郁障碍
组学
基因组学
生物标志物
疾病
表征(材料科学)
仿形(计算机编程)
生物标志物发现
生物
计算机科学
生物信息学
医学
化学
精神科
纳米技术
材料科学
生物化学
认知
基因
作者
Daniel Martins‐de‐Souza
标识
DOI:10.31887/dcns.2014.16.1/dmartins
摘要
Omics technologies emerged as complementary strategies to genomics in the attempt to understand human illnesses. In general, proteomics technologies emerged earlier than those of metabolomics for major depressive disorder (MDD) research, but both are driven by the identification of proteins and/or metabolites that can delineate a comprehensive characterization of MDD's molecular mechanisms, as well as lead to the identification of biomarker candidates of all types—prognosis, diagnosis, treatment, and patient stratification. Also, one can explore protein and metabolite interactomes in order to pinpoint additional molecules associated with the disease that had not been picked up initially. Here, results and methodological aspects of MDD research using proteomics, metabolomics, and protein interactomics are reviewed, focusing on human samples.
科研通智能强力驱动
Strongly Powered by AbleSci AI