MCAM: A database to accelerate the identification of functional cell adhesion molecules

Anguraj Sadanandam, Sudipendra Nath Pal, Joe Ziskovsky, Prathibha Hegde, Rakesh K. Singh

Research output: Contribution to journalReview article

4 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)1-4
Number of pages4
JournalCancer Informatics
Volume6
StatePublished - Aug 22 2008

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Keywords

  • Cancer
  • Cell adhesion molecules
  • Classification of cell adhesion molecules
  • Database
  • Gene ontology
  • Organ-specific homing
  • Virtual gene expression

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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