ANALYSIS OF FASTNCAALGORITHM BASED ON TRANSCRIPTIONAL REGULATION OF BREAST CANCER
Keywords:
Breast cancer, single nucleotide polymorphism, rapid network component analysis, transcriptional regulation.Abstract
Single Nucleotide Polymorphisms ( SNPs ) Can Control Transcription Factors TF ( transcription factor ) on the allele-specific binding , in order to Control the expression of specific genes , quantitatively deduce TF The activity and its regulatory strength will play an important role in the analysis of differential genes and their regulatory effects. Book Research using Rapid Network Composition Analysis fast NCA ( fast network component analysis ) algorithm to derive breast cancer BC ( breast cancer ) poor different expression TF activity and its effect on target gene TG ( transcription gene ) and construct its transcriptional regulatory network. At the same time , considering the micro Arrayed gene expression data and next-generation sequencing technologies. This study adopts the method of comparing the two kinds of data with differential genes. Fusion method to explore the function of transcriptional regulation. Molecular biology analysis found that the shared significant TF regulated by the same or not same TG have participated with The biological processes and pathways closely related to BC pathogenesis have also proved that through the fusion analysis of multiple data , it is possible to make up for the single data Insufficient data , more comprehensive and full exploration BC pathogenic mechanism.References
[1] 1. Barabasi AL , and Oltvai ZN , 2004 , network biology: understand ing the cell's functional organization , Nature Reviews Ge- netics , 5 ( 2 ) : 101-113. 2. Bishop EA , Lightfoot S. , Thavathiru E. , and Benbrook DM , 2014 , Insulin exerts direct effects on carcinogenic transform- mation of human endometrial organotypic cultures , Cancer Investigation , 32 ( 3 ) : 63-70. 3. Chang C. , Ding Z. , Hung YS , and Fung PC , 2008 , Fast net work component analysis ( fastnca ) for gene regulatory net- work reconstruction from microarray data , Bioinformatics , 24 ( 11 ) : 1349-1358. 4. Flanagan JM , fun JM , Henderson S. , Wild L. , Carey N. , and Boshoff C. , 2009 , Genomics screen in transformed stem cells reveal RNASEH2A , PPAP2C , and ADARB1 as puta- tive anticancer drug targets , Molecular Cancer Therapeutics , 8 ( 1 ) : 249-260.