Your browser doesn't support javascript.
loading
Random Forests algoritm-based bioinformatic screening of functional genes involved in lymph metastasis of cervical cancer / 中国生化药物杂志
Article in Chinese | WPRIM | ID: wpr-486528
Responsible library: WPRO
ABSTRACT
Objective To screen the genes most relevant to lymph node metastasis of cervical cancer and identify the genes at the key knots of the regulatory network to provide the potential targets for cervical cancer intervention.Methods The transcriptional profiling database of TCGA was used, and random forests algorithm was adopted to rank the genes related to lymph node metastasis extracted from GeneCards database.STRING and Cytospace tolls were used to build the interactive regulatory network and identify the most weighted genes localized in the central of the network.DAVID platform was used to perform a functional annotation for the whole geneset.Results We ranked 2784 genes in respect to their potential contributions to lymph node metastasis of cervical cancer and identified the genes at the key knob.The genes related to cancer metastasis were enriched to cytokines pathway, MAPK pathway, wnt pathway, intercellular interaction, adhesive conjunction, cellular skeleton regulation, etc.Some of the identified key genes, like EGFR, NOTCH1, RHOA, etc. have been verified to be closely related cervical cancer metastasis in the basic and clinical research. Conclusion Random forests algorithm is useful, taking advantages of TCGA database, in enriching the genes playing significant role in cervical cancer metastasis.A majority of the genes in the analyzed geneset were indicated to be significantly correlated with lymph node metastasis.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Screening study Language: Chinese Journal: Chinese Journal of Biochemical Pharmaceutics Year: 2016 Type: Article

Similar

MEDLINE

...
LILACS

LIS

Full text: Available Index: WPRIM (Western Pacific) Type of study: Screening study Language: Chinese Journal: Chinese Journal of Biochemical Pharmaceutics Year: 2016 Type: Article