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Efficiency and Effectiveness Metrics in Evolutionary Algorithms and Their Application Read chapter Read first chapter

2015 | OriginalPaper | Chapter

Identification of Osteosarcoma-Related Genes Based on Bioinformatics Methods

Authors : Ze-Bing Si, Ji-Gong Wu

Published in: Intelligent Computing Theories and Methodologies

Publisher: Springer International Publishing

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Abstract

Osteosarcoma is one of the malignant cancers. Improving diagnosis and treatment of this disease is urgent. Microarray data have revealed abnormal expression of several genes implicated in osteosarcoma. From the mRNA data, differentially expressed (DE) genes were selected by Wilcox test. Using Endeavour online service, 200 DE genes were selected as osteosarcoma related genes. Combing the module extraction algorithm, we identified 90 osteosarcoma candidate genes. Nine (DCC, FGFR, Fzd1, NFKBIA, CCNE1, CASP3, APC, and LRP6) out of the 90 candidate genes have great potential roles in osteosarcoma.

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previous chapter Using Restricted Additive Tree Model for Identifying the Large-Scale Gene Regulatory Networks
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Metadata
Title
Identification of Osteosarcoma-Related Genes Based on Bioinformatics Methods
Authors
Ze-Bing Si
Ji-Gong Wu
Copyright Year
2015
Book
Intelligent Computing Theories and Methodologies

Print ISBN: 978-3-319-22185-4

Electronic ISBN: 978-3-319-22186-1

Copyright Year: 2015

DOI
https://doi.org/10.1007/978-3-319-22186-1_35

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