title: Analysis on differential gene expression data for prediction of new biological features in permanent atrial fibrillation.
abstract: Permanent Atrial fibrillation (pmAF) has largely remained incurable since the existing information for explaining precise mechanisms underlying pmAF is not sufficient. Microarray analysis offers a broader and unbiased approach to identify and predict new biological features of pmAF. By considering the unbalanced sample numbers in most microarray data of case - control, we designed an asymmetric principal component analysis algorithm and applied it to re - analyze differential gene expression data of pmAF patients and control samples for predicting new biological features. Finally, we identified 51 differentially expressed genes using the proposed method, in which 42 differentially expressed genes are new findings compared with two related works on the same data and the existing studies. The enrichment analysis illustrated the reliability of identified differentially expressed genes. Moreover, we predicted three new pmAF - related signaling pathways using the identified differentially expressed genes via the KO-Based Annotation System. Our analysis and the existing studies supported that the predicted signaling pathways may promote the pmAF progression. The results above are worthy to do further experimental studies. This work provides some new insights into molecular features of pmAF. It has also the potentially important implications for improved understanding of the molecular mechanisms of pmAF.
authors.affiliation: School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China.
authors.forename: Feng
authors.initials: F
authors.lastname: Ou
authors.forename: Nini
authors.initials: N
authors.lastname: Rao
authors.forename: Xudong
authors.initials: X
authors.lastname: Jiang
authors.forename: Mengyao
authors.initials: M
authors.lastname: Qian
authors.forename: Wei
authors.initials: W
authors.lastname: Feng
authors.forename: Lixue
authors.initials: L
authors.lastname: Yin
authors.forename: Xu
authors.initials: X
authors.lastname: Chen
mesh_terms: D001281:Atrial Fibrillation / Q000235:genetics* / Q000378:metabolism*; D020869:Gene Expression Profiling; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D006801:Humans; D008954:Models, Biological; D047492:Peroxisome Proliferator-Activated Receptors / Q000378:metabolism; D025341:Principal Component Analysis; D015398:Signal Transduction
chemical_list: D047492:Peroxisome Proliferator-Activated Receptors