Sadanandam Anguraj, Pal Sudipendra Nath, Ziskovsky Joe, Hegde Prathibha, Singh Rakesh K
Department of Pathology and Microbiology, University of Nebraska Medical Center, Omaha, NE 68198-5845, USA.
Cancer Inform. 2008;6:47-50. doi: 10.4137/cin.s341. Epub 2008 Mar 31.
In the post-genomic era, computational identification of cell adhesion molecules (CAMs) becomes important in defining new targets for diagnosis and treatment of various diseases including cancer. Lack of a comprehensive CAM-specific database restricts our ability to identify and characterize novel CAMs. Therefore, we developed a comprehensive mammalian cell adhesion molecule (MCAM) database. The current version is an interactive Web-based database, which provides the resources needed to search mouse, human and rat-specific CAMs and their sequence information and characteristics such as gene functions and virtual gene expression patterns in normal and tumor tissues as well as cell lines. Moreover, the MCAM database can be used for various bioinformatics and biological analyses including identifying CAMs involved in cell-cell interactions and homing of lymphocytes, hematopoietic stem cells and malignant cells to specific organs using data from high-throughput experiments. Furthermore, the database can also be used for training and testing existing transmembrane (TM) topology prediction methods specifically for CAM sequences. The database is freely available online at http://app1.unmc.edu/mcam.
在后基因组时代，通过计算方法鉴定细胞黏附分子（CAMs）对于确定包括癌症在内的各种疾病的诊断和治疗新靶点变得至关重要。缺乏一个全面的CAM特异性数据库限制了我们鉴定和表征新型CAMs的能力。因此，我们开发了一个全面的哺乳动物细胞黏附分子（MCAM）数据库。当前版本是一个基于网络的交互式数据库，它提供了搜索小鼠、人类和大鼠特异性CAMs及其序列信息和特征所需的资源，这些特征包括正常组织和肿瘤组织以及细胞系中的基因功能和虚拟基因表达模式。此外，MCAM数据库可用于各种生物信息学和生物学分析，包括使用高通量实验数据鉴定参与细胞间相互作用以及淋巴细胞、造血干细胞和恶性细胞归巢到特定器官的CAMs。此外，该数据库还可用于专门针对CAM序列训练和测试现有的跨膜（TM）拓扑预测方法。该数据库可在网上免费获取，网址为http://app1.unmc.edu/mcam 。
