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- 저자 : Hai-ying Cao (검색결과 4 건)
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Hai-ying Cao,Ling Wu 보안공학연구지원센터 2016 International Journal of u- and e- Service, Scienc Vol.9 No.10
In the field of application prediction, there are two kinds of common methods to establish the prediction model: prediction model established by artificial data analysis relying on expert experience, and prediction model achieved by statistical model exploiting data analysis. However, the prediction accuracy of the model based on expert is restricted by the experiences, while the model based on statistical analysis is limited by the quality and scale of the training data. In view of the advantages and disadvantages of these two kinds of models, this paper presents a prediction model by integrating Analytic Hierarchy Process and Logistic Regression. The proposed prediction model uses the Analytic Hierarchy Process, which are based on the training data and expert experience to obtain the rank of predominant factor in a specific domain, and exploits the logistical regression model to learn the weights of each influencing factor. Finally, the linear combination of the two models is used to obtain the prediction model. Further, we take agricultural land contractual management transfer prediction as an example to test the proposed hybrid prediction model.
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Zhao Xiao-yu,Wu Ying-ping,Li Hai-ying,Cao Yan,Mei Zhi-yong,Li Jia-hui 한국유전학회 2022 Genes & Genomics Vol.44 No.10
Background: Ovarian development is regulated by genes that are expressed dynamically and stage-specifically. Circular RNA (circRNA) has been proven to play a significant role in the regulation of animal reproduction. Objective: Studying the expression characteristics of circRNAs in goose ovaries at various egg-laying stages can provide a reference for the molecular regulation mechanism of ovary development in geese that is mediated by circRNAs. Methods: In this study, the expression profiles of circRNAs were compared in ovary tissues from Yili geese in three different breeding periods, namely the prelaying period (KL), laying period (CL), and ceased period (XL), and differentially expressed circRNAs related to ovarian development in Yili geese were screened. The potential biological functions of differential circRNAs were predicted by bioinformatics, and the differential circRNA-miRNA regulatory network was constructed. Results: The results showed that a total of 4483 circRNAs were identified in 12 ovarian tissue samples from Yili geese at different laying stages. In the KL vs. CL, XL vs. CL, and XL vs. KL groups, 159, 455, and 383 differentially expressed circRNAs were identified, respectively. The host genes of the differential circRNAs were mostly enriched in the signal transduction, metabolism, and other related pathways, such as those for phototransduction, glycerophospholipid metabolism, aminoacyl-tRNA biosynthesis, and retinol metabolism. Finally, we constructed circRNA-miRNA regulation networks. Nine differential circRNAs were randomly selected for qRT-PCR verification, and the expression trends were consistent with the sequencing results. Conclusions: Our results indicated that significant differences in the expression profiles of circRNAs in the ovaries of Yili geese at different egg-laying stages. Meanwhile, through analyzing the differential circRNA-miRNA interaction network, core regulators such as circRNA NW_013186107.1:36835|52,574 and gga-miR-34b-5p were screened. This study provides a reference for the further analysis of the molecular regulatory mechanism of the circRNAs regulating goose ovary development and enriches the theory of genetic regulation during goose ovary development.
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Five miRNAs as Novel Diagnostic Biomarker Candidates for Primary Nasopharyngeal Carcinoma
Tang, Jin-Feng,Yu, Zhong-Hua,Liu, Tie,Lin, Zi-Ying,Wang, Ya-Hong,Yang, La-Wei,He, Hui-Juan,Cao, Jun,Huang, Hai-Li,Liu, Gang Asian Pacific Journal of Cancer Prevention 2014 Asian Pacific journal of cancer prevention Vol.15 No.18
MicroRNAs (miRNAs) play an essential role in the development and progression of nasopharyngeal carcinomas (NPC). Despite advances in the field of cancer molecular biology and biomarker discovery, the development of clinically validated biomarkers for primary NPC has remained elusive. In this study, we investigated the expression and clinical significance of miRNAs as novel primary NPC diagnostic biomarkers. We used an array containing 2, 500 miRNAs to identify 22 significant miRNAs, and these candidate miRNAs were validated using 67 fresh NPC and 25 normal control tissues via quantitative real-time PCR (qRT-PCR). Expression and correlation analyses were performed with various statistical approaches, in addition to logistic regression and receiver operating characteristic curve analyses to evaluate diagnostic efficacy. qRT-PCR revealed five differentially expressed miRNAs (miR-93-5p, miR-135b-5p, miR-205-5p and miR-183-5p) in NPC tissue samples relative to control samples (p<0.05), with miR-135b-5p and miR-205-5p being of significant diagnostic value (p<0.01). Moreover, comparison of NPC patient clinicopathologic data revealed a negative correlation between miR-93-5p and miR-183-5p expression levels and lymph node status (p<0.05). These findings display an altered expression of many miRNAs in NPC tissues, thus providing information pertinent to pathophysiological and diagnostic research. Ultimately, miR-135b-5p and miR-205-5p may be implicated as novel NPC candidate biomarkers, while miR-93-5p, miR-650 and miR-183-5p may find application as relevant clinical pathology and diagnostic candidate biomarkers.
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