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MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules
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 C...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Libertas Academica
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2623291/ https://www.ncbi.nlm.nih.gov/pubmed/19259402 |
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author | Sadanandam, Anguraj Pal, Sudipendra Nath Ziskovsky, Joe Hegde, Prathibha Singh, Rakesh K. |
author_facet | Sadanandam, Anguraj Pal, Sudipendra Nath Ziskovsky, Joe Hegde, Prathibha Singh, Rakesh K. |
author_sort | Sadanandam, Anguraj |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2623291 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Libertas Academica |
record_format | MEDLINE/PubMed |
spelling | pubmed-26232912009-02-24 MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules Sadanandam, Anguraj Pal, Sudipendra Nath Ziskovsky, Joe Hegde, Prathibha Singh, Rakesh K. Cancer Inform Software or Database Review 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. Libertas Academica 2008-03-31 /pmc/articles/PMC2623291/ /pubmed/19259402 Text en © 2008 by the authors http://creativecommons.org/licenses/by/3.0 This article is an open-access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/3.0/). |
spellingShingle | Software or Database Review Sadanandam, Anguraj Pal, Sudipendra Nath Ziskovsky, Joe Hegde, Prathibha Singh, Rakesh K. MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title | MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title_full | MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title_fullStr | MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title_full_unstemmed | MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title_short | MCAM: A Database to Accelerate the Identification of Functional Cell Adhesion Molecules |
title_sort | mcam: a database to accelerate the identification of functional cell adhesion molecules |
topic | Software or Database Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2623291/ https://www.ncbi.nlm.nih.gov/pubmed/19259402 |
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