How to cite this paper
Alkhateeb, A. (2023). HC-UAP: Outliers detection method based-on hierarchical clustering for universally aligned time-series RNA-Seq profiles.Decision Science Letters , 12(1), 89-96.
Refrences
Alkhateeb, A., Rezaeian, I., Singireddy, S., & Rueda, L. (2015, November). Obtaining biomarkers in cancer progression from outliers of time-series clusters. In 2015 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 889-896). IEEE.
Chai, S., Xu, X., Wang, Y., Zhou, Y., Zhang, C., Yang, Y., ... & Wang, K. (2015). Ca2+/calmodulin-dependent protein kinase IIγ enhances stem-like traits and tumorigenicity of lung cancer cells. Oncotarget, 6(18), 16069.
Chen, F., Wang, M., Bai, J., Liu, Q., Xi, Y., Li, W., & Zheng, J. (2014). Role of RUNX3 in suppressing metastasis and angiogenesis of human prostate cancer. PLoS one, 9(1), e86917.
Chira, C., Sedano, J., Villar, J. R., Camara, M., & Prieto, C. (2015). Shape-output gene clustering for time series microarrays. In 10th International Conference on Soft Computing Models in Industrial and Environmental Applications (pp. 241-250). Springer, Cham.
Chiu, T. Y., Hsu, T. C., Yen, C. C., & Wang, J. S. (2015). Interpolation based consensus clustering for gene expression time series. BMC bioinformatics, 16(1), 1-17.
Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE transactions on pattern analysis and machine intelligence, 2, 224-227.
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., and Gingeras, T. R. Star: ultrafast universal rna-seq aligner. Bioinformatics, 29(1), 15–21, 2013
Ernst, J., & Bar-Joseph, Z. (2006). STEM: a tool for the analysis of short time series gene expression data. BMC bioinformatics, 7(1), 1-11.
Ferrari, D. G., & De Castro, L. N. (2015). Clustering algorithm selection by meta-learning systems: A new distance-based problem characterization and ranking combination methods. Information Sciences, 301, 181-194.
Fijneman, R. J., Bade, L. K., Peham, J. R., Van De Wiel, M. A., Van Hinsbergh, V. W., Meijer, G. A., ... & Cormier, R. T. (2009). Pla2g2a attenuates colon tumorigenesis in azoxymethane-treated C57BL/6 mice; expression studies reveal Pla2g2a target genes and pathways. Analytical Cellular Pathology, 31(5), 345-356.
Gao, W., Lam, J. W. K., Li, J. Z. H., Chen, S. Q., Tsang, R. K. Y., Chan, J. Y. W., & Wong, T. S. (2017). MicroRNA-138-5p controls sensitivity of nasopharyngeal carcinoma to radiation by targeting EIF4EBP1. Oncology Reports, 37(2), 913-920.
Gu, Y., Chen, T., Meng, Z., Gan, Y., Xu, X., Lou, G., ... & Xu, R. (2012). CaMKII γ, a critical regulator of CML stem/progenitor cells, is a target of the natural product berbamine. Blood, The Journal of the American Society of Hematology, 120(24), 4829-4839.
Jaskowiak, P. A., Campello, R. J., & Costa, I. G. (2014, January). On the selection of appropriate distances for gene expression data clustering. In BMC bioinformatics, 15(2), 1-17.
Lee, J. H., Yoo, S. S., Hong, M. J., Choi, J. E., Lee, S. Y., & Park, J. Y. (2017). Association between polymorphisms in microRNA target sites and survival in early-stage non-small cell lung cancer. Annals of Oncology, 28, v456.
Li, B. and Dewey, C. N. Rsem: accurate transcript quantification from rna-seq data with or without a reference genome. BMC bioinformatics, 12(1), 1–16, 2011.
Long, Q., Xu, J., Osunkoya, A. O., Sannigrahi, S., Johnson, B. A., Zhou, W., ... & Moreno, C. S. (2014). Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence Biomarkers of Recurrence in Prostate Cancer. Cancer research, 74(12), 3228-3237.
Marghny, M. H., & Taloba, A. I. (2014). Outlier detection using improved genetic k-means. arXiv preprint arXiv:1402.6859.
Maulik, U., & Bandyopadhyay, S. (2002). Performance evaluation of some clustering algorithms and validity indices. IEEE Transactions on pattern analysis and machine intelligence, 24(12), 1650-1654.
Meng, Z., Li, T., Ma, X., Wang, X., Van Ness, C., Gan, Y., ... & Huang, W. (2013). Berbamine Inhibits the Growth of Liver Cancer Cells and Cancer-Initiating Cells by Targeting Ca2+/Calmodulin-Dependent Protein Kinase IIBerbamine Inhibits Liver Cancer through CAMKII. Molecular cancer therapeutics, 12(10), 2067-2077.
Oleksowicz, L., Liu, Y., Bracken, R. B., Gaitonde, K., Burke, B., Succop, P., ... & Lu, S. (2012). Secretory phospholipase A2‐IIa is a target gene of the HER/HER2‐elicited pathway and a potential plasma biomarker for poor prognosis of prostate cancer. The Prostate, 72(10), 1140-1149.
Pamula, R., Deka, J. K., & Nandi, S. (2011, February). An outlier detection method based on clustering. In 2011 second international conference on emerging applications of information technology (pp. 253-256). IEEE.
Ren, S., Peng, Z., Mao, J. H., Yu, Y., Yin, C., Gao, X., ... & Sun, Y. (2012). RNA-seq analysis of prostate cancer in the Chinese population identifies recurrent gene fusions, cancer-associated long noncoding RNAs and aberrant alternative splicings. Cell research, 22(5), 806-821.
Rueda, L., & Bari, A. (2007, December). Clustering temporal gene expression data with unequal time intervals. In 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems (pp. 192-199). IEEE.
Sasaki, T., Matsumoto, N., Jinno, Y., Niikawa, N., Sakai, H., Kanetake, H., & Saito, Y. (1996). Assignment of the human β-microseminoprotein gene (MSMB) to chromosome 10q11. 2. Cytogenetic and Genome Research, 72(2-3), 177-178.
Sayagués, J. M., Fontanillo, C., Abad, M. D. M., Gonzalez-Gonzalez, M., Sarasquete, M. E., Chillon, M. D. C., ... & Orfao, A. (2010). Mapping of genetic abnormalities of primary tumours from metastatic CRC by high-resolution SNP arrays. PLoS One, 5(10), e13752.
Srivastava S. K., Dobi, A., Petrovics, G., Werner, T., Seifert, M., & Scherf, M. (2016). Prostate cancer gene profiles and methods of using the same. US Patent App. 15/108,909
Subhani, N., Rueda, L., Ngom, A., & Burden, C. J. (2010). Multiple gene expression profile alignment for microarray time-series data clustering. Bioinformatics, 26(18), 2281-2288.
Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., ... & Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature protocols, 7(3), 562-578.
Vedell, P. T., Lu, Y., Grubbs, C. J., Yin, Y., Jiang, H., Bland, K. I., ... & Lubet, R. (2013). Effects on gene expression in rat liver after administration of RXR agonists: UAB30, 4-methyl-UAB30, and Targretin (Bexarotene). Molecular pharmacology, 83(3), 698-708.
Wang, Y., Wan, F., Chang, K., Lu, X., Dai, B., & Ye, D. (2017). NUDT expression is predictive of prognosis in patients with clear cell renal cell carcinoma. Oncology letters, 14(5), 6121-6128.
Williams, K., Ghosh, R., Giridhar, P. V., Gu, G., Case, T., Belcher, S. M., & Kasper, S. (2012). Inhibition of Stathmin1 Accelerates the Metastatic ProcessSTMN1 Accelerates the Metastatic Process. Cancer research, 72(20), 5407-5417.
Xuan, J. W., Chin, J. L., Guo, Y., Chambers, A. F., Finkelman, M. A., & Clarke, M. W. (1995). Alternative splicing of PSP94 (prostatic secretory protein of 94 amino acids) mRNA in prostate tissue. Oncogene, 11(6), 1041-1047.
Zhang, Z., Xu, J., Tang, J., Zou, Q., & Guo, F. (2019). Diagnosis of brain diseases via multi-scale time-series model. Frontiers in Neuroscience, 13, 197.
Chai, S., Xu, X., Wang, Y., Zhou, Y., Zhang, C., Yang, Y., ... & Wang, K. (2015). Ca2+/calmodulin-dependent protein kinase IIγ enhances stem-like traits and tumorigenicity of lung cancer cells. Oncotarget, 6(18), 16069.
Chen, F., Wang, M., Bai, J., Liu, Q., Xi, Y., Li, W., & Zheng, J. (2014). Role of RUNX3 in suppressing metastasis and angiogenesis of human prostate cancer. PLoS one, 9(1), e86917.
Chira, C., Sedano, J., Villar, J. R., Camara, M., & Prieto, C. (2015). Shape-output gene clustering for time series microarrays. In 10th International Conference on Soft Computing Models in Industrial and Environmental Applications (pp. 241-250). Springer, Cham.
Chiu, T. Y., Hsu, T. C., Yen, C. C., & Wang, J. S. (2015). Interpolation based consensus clustering for gene expression time series. BMC bioinformatics, 16(1), 1-17.
Davies, D. L., & Bouldin, D. W. (1979). A cluster separation measure. IEEE transactions on pattern analysis and machine intelligence, 2, 224-227.
Dobin, A., Davis, C. A., Schlesinger, F., Drenkow, J., Zaleski, C., Jha, S., Batut, P., Chaisson, M., and Gingeras, T. R. Star: ultrafast universal rna-seq aligner. Bioinformatics, 29(1), 15–21, 2013
Ernst, J., & Bar-Joseph, Z. (2006). STEM: a tool for the analysis of short time series gene expression data. BMC bioinformatics, 7(1), 1-11.
Ferrari, D. G., & De Castro, L. N. (2015). Clustering algorithm selection by meta-learning systems: A new distance-based problem characterization and ranking combination methods. Information Sciences, 301, 181-194.
Fijneman, R. J., Bade, L. K., Peham, J. R., Van De Wiel, M. A., Van Hinsbergh, V. W., Meijer, G. A., ... & Cormier, R. T. (2009). Pla2g2a attenuates colon tumorigenesis in azoxymethane-treated C57BL/6 mice; expression studies reveal Pla2g2a target genes and pathways. Analytical Cellular Pathology, 31(5), 345-356.
Gao, W., Lam, J. W. K., Li, J. Z. H., Chen, S. Q., Tsang, R. K. Y., Chan, J. Y. W., & Wong, T. S. (2017). MicroRNA-138-5p controls sensitivity of nasopharyngeal carcinoma to radiation by targeting EIF4EBP1. Oncology Reports, 37(2), 913-920.
Gu, Y., Chen, T., Meng, Z., Gan, Y., Xu, X., Lou, G., ... & Xu, R. (2012). CaMKII γ, a critical regulator of CML stem/progenitor cells, is a target of the natural product berbamine. Blood, The Journal of the American Society of Hematology, 120(24), 4829-4839.
Jaskowiak, P. A., Campello, R. J., & Costa, I. G. (2014, January). On the selection of appropriate distances for gene expression data clustering. In BMC bioinformatics, 15(2), 1-17.
Lee, J. H., Yoo, S. S., Hong, M. J., Choi, J. E., Lee, S. Y., & Park, J. Y. (2017). Association between polymorphisms in microRNA target sites and survival in early-stage non-small cell lung cancer. Annals of Oncology, 28, v456.
Li, B. and Dewey, C. N. Rsem: accurate transcript quantification from rna-seq data with or without a reference genome. BMC bioinformatics, 12(1), 1–16, 2011.
Long, Q., Xu, J., Osunkoya, A. O., Sannigrahi, S., Johnson, B. A., Zhou, W., ... & Moreno, C. S. (2014). Global Transcriptome Analysis of Formalin-Fixed Prostate Cancer Specimens Identifies Biomarkers of Disease Recurrence Biomarkers of Recurrence in Prostate Cancer. Cancer research, 74(12), 3228-3237.
Marghny, M. H., & Taloba, A. I. (2014). Outlier detection using improved genetic k-means. arXiv preprint arXiv:1402.6859.
Maulik, U., & Bandyopadhyay, S. (2002). Performance evaluation of some clustering algorithms and validity indices. IEEE Transactions on pattern analysis and machine intelligence, 24(12), 1650-1654.
Meng, Z., Li, T., Ma, X., Wang, X., Van Ness, C., Gan, Y., ... & Huang, W. (2013). Berbamine Inhibits the Growth of Liver Cancer Cells and Cancer-Initiating Cells by Targeting Ca2+/Calmodulin-Dependent Protein Kinase IIBerbamine Inhibits Liver Cancer through CAMKII. Molecular cancer therapeutics, 12(10), 2067-2077.
Oleksowicz, L., Liu, Y., Bracken, R. B., Gaitonde, K., Burke, B., Succop, P., ... & Lu, S. (2012). Secretory phospholipase A2‐IIa is a target gene of the HER/HER2‐elicited pathway and a potential plasma biomarker for poor prognosis of prostate cancer. The Prostate, 72(10), 1140-1149.
Pamula, R., Deka, J. K., & Nandi, S. (2011, February). An outlier detection method based on clustering. In 2011 second international conference on emerging applications of information technology (pp. 253-256). IEEE.
Ren, S., Peng, Z., Mao, J. H., Yu, Y., Yin, C., Gao, X., ... & Sun, Y. (2012). RNA-seq analysis of prostate cancer in the Chinese population identifies recurrent gene fusions, cancer-associated long noncoding RNAs and aberrant alternative splicings. Cell research, 22(5), 806-821.
Rueda, L., & Bari, A. (2007, December). Clustering temporal gene expression data with unequal time intervals. In 2007 2nd Bio-Inspired Models of Network, Information and Computing Systems (pp. 192-199). IEEE.
Sasaki, T., Matsumoto, N., Jinno, Y., Niikawa, N., Sakai, H., Kanetake, H., & Saito, Y. (1996). Assignment of the human β-microseminoprotein gene (MSMB) to chromosome 10q11. 2. Cytogenetic and Genome Research, 72(2-3), 177-178.
Sayagués, J. M., Fontanillo, C., Abad, M. D. M., Gonzalez-Gonzalez, M., Sarasquete, M. E., Chillon, M. D. C., ... & Orfao, A. (2010). Mapping of genetic abnormalities of primary tumours from metastatic CRC by high-resolution SNP arrays. PLoS One, 5(10), e13752.
Srivastava S. K., Dobi, A., Petrovics, G., Werner, T., Seifert, M., & Scherf, M. (2016). Prostate cancer gene profiles and methods of using the same. US Patent App. 15/108,909
Subhani, N., Rueda, L., Ngom, A., & Burden, C. J. (2010). Multiple gene expression profile alignment for microarray time-series data clustering. Bioinformatics, 26(18), 2281-2288.
Trapnell, C., Roberts, A., Goff, L., Pertea, G., Kim, D., Kelley, D. R., ... & Pachter, L. (2012). Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks. Nature protocols, 7(3), 562-578.
Vedell, P. T., Lu, Y., Grubbs, C. J., Yin, Y., Jiang, H., Bland, K. I., ... & Lubet, R. (2013). Effects on gene expression in rat liver after administration of RXR agonists: UAB30, 4-methyl-UAB30, and Targretin (Bexarotene). Molecular pharmacology, 83(3), 698-708.
Wang, Y., Wan, F., Chang, K., Lu, X., Dai, B., & Ye, D. (2017). NUDT expression is predictive of prognosis in patients with clear cell renal cell carcinoma. Oncology letters, 14(5), 6121-6128.
Williams, K., Ghosh, R., Giridhar, P. V., Gu, G., Case, T., Belcher, S. M., & Kasper, S. (2012). Inhibition of Stathmin1 Accelerates the Metastatic ProcessSTMN1 Accelerates the Metastatic Process. Cancer research, 72(20), 5407-5417.
Xuan, J. W., Chin, J. L., Guo, Y., Chambers, A. F., Finkelman, M. A., & Clarke, M. W. (1995). Alternative splicing of PSP94 (prostatic secretory protein of 94 amino acids) mRNA in prostate tissue. Oncogene, 11(6), 1041-1047.
Zhang, Z., Xu, J., Tang, J., Zou, Q., & Guo, F. (2019). Diagnosis of brain diseases via multi-scale time-series model. Frontiers in Neuroscience, 13, 197.