Minireview: progress and challenges in proteomics data management, sharing, and integration.
The proteome represents the identity, expression levels, interacting partners, and posttranslational modifications of proteins expressed within any given cell. Proteomic studies aim to census the quantitative and qualitative factors regulating the biological relationships of proteins acting in concert as functional cellular networks. In the field of endocrinology, proteomics has been of considerable value in determining the function and mechanism of action of endocrine signaling molecules in the cell membrane, cytoplasm, and nucleus and for the discovery of proteins as candidates for clinical biomarkers. The volume of data that can be generated by proteomics methodologies, up to gigabytes of data within a few hours, brings with it its own logistical hurdles and presents significant challenges to realizing the full potential of these datasets. In this minireview, we describe selected current proteomics methodologies and their application in basic and translational endocrinology before focusing on mass spectrometry as a model for current progress and challenges in data analysis, management, sharing, and integration.
Department of Medicine, Hematology and Oncology, Baylor College of Medicine, 1 Baylor Plaza MS-BCM305, Houston, Texas 77030, USA. becnel@bcm.edu
Lauren B
LB
Becnel
Neil J
NJ
McKenna
D000818:Animals; D003627:Data Interpretation, Statistical; D006801:Humans; D033181:Information Dissemination; D019451:Information Management; D016247:Information Storage and Retrieval; D013058:Mass Spectrometry; D040081:Protein Array Analysis; D020543:Proteome / Q000737:chemistry / Q000378:metabolism; D040901:Proteomics; D015398:Signal Transduction; D057825:Two-Dimensional Difference Gel Electrophoresis
D020543:Proteome