Systems analysis of salivary gland development and disease.
Systems analysis of salivary gland development and disease.
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DOI：
10.1002/wsbm.94
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发表时间：
2010-11
影响因子：
7.9
通讯作者：
Musselmann, Kurt
中科院分区：
文献类型：
--
作者：
Larsen, Melinda;Yamada, Kenneth M.;Musselmann, Kurt
分支形态发生是脊椎动物器官在保持紧凑尺寸的同时产生广泛上皮表面积的关键发育过程。在脊椎动物的下颌下唾液腺中，分支形态发生对于产生足够唾液所需的大表面积至关重要。然而，在许多唾液腺疾病中，产生唾液的腺泡细胞被破坏，导致口干和继发性健康状况。基于系统的方法可以为了解唾液腺发育，功能和疾病提供见解。传统的方法来理解这些过程是识别的分子信号，使用还原论的方法，我们审查目前的进展与这种方法在了解唾液腺的发展。采取更全球化的方法，多个小组目前正在分析发育中的小鼠组织和人类患者样本中的转录组、蛋白质组和其他“组”。计算方法已经成功地破译了大型数据集，数学模型开始预测分子对形态发生和细胞功能的物理过程的贡献。未来的一个挑战将是建立全面的、可公开访问的唾液腺数据库，涵盖所有基因和蛋白质;正在计划将这些资源提供给集中存储库中的研究人员。未来最大的挑战将是开发现实的模型，整合多种类型的数据来描述和预测胚胎发育和人类疾病。
Branching morphogenesis is a crucial developmental process in which vertebrate organs generate extensive epithelial surface area while retaining a compact size. In the vertebrate submandibular salivary gland, branching morphogenesis is crucial for generation of the large surface area necessary to produce sufficient saliva. However, in many salivary gland diseases, saliva-producing acinar cells are destroyed, resulting in dry mouth and secondary health conditions. Systems-based approaches can provide insights into understanding salivary gland development, function, and disease. The traditional approach to understanding these processes is identification of molecular signals using reductionist approaches; we review current progress with such methods in understanding salivary gland development. Taking a more global approach, multiple groups are currently profiling the transcriptome, the proteome, and other “omes” in both developing mouse tissues and in human patient samples. Computational methods have been successful in deciphering large data sets, and mathematical models are starting to make predictions regarding the contribution of molecules to the physical processes of morphogenesis and of cellular function. A challenge for the future will be to establish comprehensive, publicly accessible salivary gland databases spanning the full range of genes and proteins; plans are underway to provide these resources to researchers in centralized repositories. The greatest challenge for the future will be to develop realistic models that integrate multiple types of data to both describe and predict embryonic development and human disease.
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影响因子：
--
作者：
Hu, Shen;Zhou, Michael;Jiang, Jiang;Wang, Jianghua;Elashoff, David;Gorr, Sven;Michie, Sara A.;Spijkervet, Fred K. L.;Bootsma, Hendrika;Kallenberg, Cees G. M.;Vissink, Arjan;Horvath, Steve;Wong, David T.
通讯作者：
Wong, David T.
影响因子：
2.7
作者：
Gill, Sean E.;Pape, M. Cynthia;Leco, Kevin J.
通讯作者：
Leco, Kevin J.
影响因子：
4.6
作者：
Hoffman, MP;Kidder, BL;Larsen, M
通讯作者：
Larsen, M
影响因子：
5.8
作者：
Demir, C;Gultekin, SH;Yener, B
通讯作者：
Yener, B
DOI：
10.1002/ar.a.10045
发表时间：
2003-04-01
期刊：
ANATOMICAL RECORD PART A-DISCOVERIES IN MOLECULAR CELLULAR AND EVOLUTIONARY BIOLOGY
影响因子：
--
作者：
Jaskoll, T;Zhou, YM;Melnick, M
通讯作者：
Melnick, M