Добірка наукової літератури з теми "MiRNA database"
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Статті в журналах з теми "MiRNA database"
Slattery, Martha L., Jennifer S. Herrick, John R. Stevens, Roger K. Wolff, and Lila E. Mullany. "An Assessment of Database-Validated microRNA Target Genes in Normal Colonic Mucosa: Implications for Pathway Analysis." Cancer Informatics 16 (January 1, 2017): 117693511771640. http://dx.doi.org/10.1177/1176935117716405.
Повний текст джерелаHou, Yawei, Yameng Li, Yichuan Wang, Wenpu Li, and Zhenwei Xiao. "Screening and Analysis of Key Genes in miRNA-mRNA Regulatory Network of Membranous Nephropathy." Journal of Healthcare Engineering 2021 (November 16, 2021): 1–13. http://dx.doi.org/10.1155/2021/5331948.
Повний текст джерелаLi, Yameng, Yukun Xu, Yawei Hou, and Rui Li. "Construction and Bioinformatics Analysis of the miRNA-mRNA Regulatory Network in Diabetic Nephropathy." Journal of Healthcare Engineering 2021 (November 18, 2021): 1–11. http://dx.doi.org/10.1155/2021/8161701.
Повний текст джерелаChen, Yuhao, and Xiaowei Wang. "miRDB: an online database for prediction of functional microRNA targets." Nucleic Acids Research 48, no. D1 (August 31, 2019): D127—D131. http://dx.doi.org/10.1093/nar/gkz757.
Повний текст джерелаLiu, Chun-Jie, Xin Fu, Mengxuan Xia, Qiong Zhang, Zhifeng Gu, and An-Yuan Guo. "miRNASNP-v3: a comprehensive database for SNPs and disease-related variations in miRNAs and miRNA targets." Nucleic Acids Research 49, no. D1 (September 29, 2020): D1276—D1281. http://dx.doi.org/10.1093/nar/gkaa783.
Повний текст джерелаPian, Cong, Guangle Zhang, Libin Gao, Xiaodan Fan, and Fei Li. "miR+Pathway: the integration and visualization of miRNA and KEGG pathways." Briefings in Bioinformatics 21, no. 2 (January 16, 2019): 699–708. http://dx.doi.org/10.1093/bib/bby128.
Повний текст джерелаPark, Sungjin, SeongRyeol Moon, Kiyoung Lee, Ie Byung Park, Dae Ho Lee, and Seungyoon Nam. "miR2Diabetes: A Literature-Curated Database of microRNA Expression Patterns, in Diabetic Microvascular Complications." Genes 10, no. 10 (October 9, 2019): 784. http://dx.doi.org/10.3390/genes10100784.
Повний текст джерелаHuang, Hsi-Yuan, Yang-Chi-Dung Lin, Shidong Cui, Yixian Huang, Yun Tang, Jiatong Xu, Jiayang Bao, et al. "miRTarBase update 2022: an informative resource for experimentally validated miRNA–target interactions." Nucleic Acids Research 50, no. D1 (November 30, 2021): D222—D230. http://dx.doi.org/10.1093/nar/gkab1079.
Повний текст джерелаKehl, Tim, Fabian Kern, Christina Backes, Tobias Fehlmann, Daniel Stöckel, Eckart Meese, Hans-Peter Lenhof, and Andreas Keller. "miRPathDB 2.0: a novel release of the miRNA Pathway Dictionary Database." Nucleic Acids Research 48, no. D1 (November 6, 2019): D142—D147. http://dx.doi.org/10.1093/nar/gkz1022.
Повний текст джерелаLiu, Xinhong, Feng Chen, Fang Tan, Fang Li, Ruokun Yi, Dingyi Yang, and Xin Zhao. "Construction of a Potential Breast Cancer-Related miRNA-mRNA Regulatory Network." BioMed Research International 2020 (November 4, 2020): 1–18. http://dx.doi.org/10.1155/2020/6149174.
Повний текст джерелаДисертації з теми "MiRNA database"
Bou, Zeidan Nadim Georges. "Human miRNA Sequence Based Variations Database." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5350.
Повний текст джерелаPrakash, Ashwin. "Evolution and Function of Compositional Patterns in Mammalian Genomes." University of Toledo Health Science Campus / OhioLINK, 2011. http://rave.ohiolink.edu/etdc/view?acc_num=mco1321301839.
Повний текст джерелаZhuang, Wen-Wei, and 莊文瑋. "An Integrated Database of miRNA-Regulated Disease-Associated Protein Complexes." Thesis, 2014. http://ndltd.ncl.edu.tw/handle/yg83rw.
Повний текст джерела國立虎尾科技大學
資訊工程研究所
102
In human, a large portion of genes undergoes alternative splicing then translates into different protein isoforms. Translated proteins are activated or repressed through post-translational modification (PTM). Biological processes are mediated by protein-protein interaction (PPI). Many research studies suggested that disease formation involves differential expression of isoforms. Furthermore, both of PTM and PPI are essential for the signal transduction mechanism where defects in such process may lead to disease formation. In this work, disease-associated genes, proteins, alternative products, PTM, Gene Ontology (GO) annotations, subcellular localization and PPI information are integrated to provide a sophisticated platform for disease studies. A total of 39 disease types and 47 subcellular localizations information are included in the platform. This platform also provided an index, Jaccard index; to quantify the portion of common proteins involved for any two of the diseases, which may be useful for comorbidity study. A few subcellular localization specific PPI information are available in Cytoscape display format. Using lung cancer associated genes as a case study, we demonstrate how to use the web server resource to discover further disease information. miRNA-regulated protein complexes were identified. Certain complexes are highly regulated by miRNAs. Given that a complex can perform specific biological function, one may expect miRNA-regulated complex may result in observed phenotypic effects. A web-based platform has been set up to display the results; it can be accessed at http://bioinfo.csie.nfu.edu.tw/Dis/index.php.
Bo-WenTu and 凃博文. "Construction of a database which provides disease-specific or tissue-specific miRNA-target relationships." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/30530423610941174335.
Повний текст джерела國立成功大學
電機工程學系
104
MicroRNAs (miRNAs) are functional RNA molecules which play important roles in post-transcriptional regulation. miRNAs regulate their targets by repressing translation or inducing degradation of target mRNAs. Several databases have been constructed to deposit predicted miRNA-target information by using different algorithms, but these databases usually contains lots of false positives. Besides, the validated databases provides only a few miRNA-target information compared to the predicted databases. To reduce incorrect records and increase the number of reliable records, many other databases integrate these predicted miRNA-target information from the databases mentioned above. However, the expression of the same miRNAs in different tissues are different, the realistic regulatory mechanisms could not be figured out in these databases. Moreover, they cannot return the common targets with multiple input miRNAs. To solve these two problems, we construct a database called CSmiRTar (Condition-Specific miRNA Targets). CSmiRTar collects computationally predicted targets of 2588 miRNAs in Human (or 1945 miRNAs in Mouse) from four existing databases (microRNA.org, TargetScan, DIANA-microT and miRDB), and it provides some biological filters which enabling users to search miRNA targets which are expressed only in a specific tissue or related to a specific disease. Moreover, CSmiRTar allows users to search the common targets of multiple miRNAs under a specific biological condition. We believe that CSmiRTar could be helpful for biologists whom want to study the regulatory mechanisms of miRNAs. The CSmiRTar database is available at http://cosbi.ee.ncku.edu.tw /CSmiRTar/.
Wen, Jiayu. "In silico prediction of active RNA genes in legumes." Phd thesis, 2007. http://hdl.handle.net/1885/49423.
Повний текст джерелаLee, Mei-Yu, and 李美漁. "Use of TCGA Database To study the Arm Selection Preference of MicroRNA in Lung Cancer: miRNA-5p and -3p might Have Distinct Role in Lung Cancer." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/29kwe5.
Повний текст джерела義守大學
生物科技學系
105
Lung cancer is the most common cancer in Taiwan. A major cause of the lethality of lung cancer is distant metastases at advance stage, which usually leading to poor survival rate. Therefore, investigating and improving diagnostic sensitivity of biomarkers for early stage tumors is beneficial for improving the survival rate of lung cancer patients. MicroRNA (miRNA) dysfunction, a critical hallmark of lung cancer, leads to tumor suppressive and oncogenic gene disorder during lung cancer progression. The selection of the 5p and 3p arms of miRNA is a mechanism that improves the modulation of the biological function diversity of miRNA and complicates its regulatory network in human cancers. Here, we used The Cancer Genome Atlas (TCGA) database to study the arm selection preference of miRNA in lung cancer and corresponding adjacent normal tissue. We found that 5p and 3p arm selection is consistent in most miRNAs in lung cancer. Only a few miRNAs showed significant changes in the arm selection preference in lung cancer. Our data revealed that the arm selection preference of 36 miRNAs significantly increased, whereas that of 19 miRNAs decreased in lung cancer compared with corresponding adjacent normal tissues. Among them, the biological function of the individual arm of miR-324, miR-335 and miR-455 were selected for further investigating in this study. Our data showed that both miR-324-5p and -3p were significantly overexpressed in lung cancer cells. Ectopic expression of miR-324-5p promoted the cell proliferation and invasion ability, whereas miR-324-3p overexpression increased the cell proliferation but did not influence the invasion ability of the cancer cells. The expression levels of miR-355-5p significantly decreased in lung cancer and played tumor suppressive role in silencing cancer cell growth and invasion ability. Otherwise, the miR-355-3p overexpressed in lung cancer and promoted lung cancer cell proliferation. In conclusion, the arm selection preference of miRNA might be a mechanism to modulate its biological function. The findings of this study provide a novel insight into lung cancer therapy.
Частини книг з теми "MiRNA database"
Dweep, Harsh, Norbert Gretz, and Carsten Sticht. "miRWalk Database for miRNA–Target Interactions." In RNA Mapping, 289–305. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1062-5_25.
Повний текст джерелаHinske, Ludwig Christian, Jens Heyn, Pedro A. F. Galante, Lucila Ohno-Machado, and Simone Kreth. "Setting Up an Intronic miRNA Database." In MicroRNA Protocols, 69–76. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-083-0_5.
Повний текст джерелаLv, Hao, Jin Li, Sai Zhang, Kun Yue, and Shaoyu Wei. "Meta-path Based MiRNA-Disease Association Prediction." In Database Systems for Advanced Applications, 34–48. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-18590-9_3.
Повний текст джерелаZhang, Jingjing, Ruiqi Liu, and Guanglin Li. "Constructing CircRNA–miRNA–mRNA by Using Database." In Methods in Molecular Biology, 173–79. New York, NY: Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1645-1_10.
Повний текст джерелаKumaran, A. "MIRA: Multilingual Information Processing on Relational Architecture." In Current Trends in Database Technology - EDBT 2004 Workshops, 12–23. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-30192-9_2.
Повний текст джерелаde Hoon, Michiel Jan Laurens. "Atlas of miRNAs and Their Promoters in Human and Mouse." In Practical Guide to Life Science Databases, 57–75. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-5812-9_3.
Повний текст джерелаBansal, Parveen, Ashish Kumar, Sudhir Chandna, Malika Arora, and Renu Bansal. "Method for Detection of miRNAs in Non-Model Organisms with Unreported Database." In Methods in Molecular Biology, 197–208. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-8624-8_15.
Повний текст джерелаKelarev, Andrei, Jennifer Seberry, Leanne Rylands, and Xun Yi. "Combinatorial Algorithms and Methods for Security of Statistical Databases Related to the Work of Mirka Miller." In Lecture Notes in Computer Science, 383–94. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-78825-8_31.
Повний текст джерелаPeriwal, Vinita, and Vinod Scaria. "Machine Learning Approaches Toward Building Predictive Models for Small Molecule Modulators of miRNA and Its Utility in Virtual Screening of Molecular Databases." In Methods in Molecular Biology, 155–68. New York, NY: Springer New York, 2016. http://dx.doi.org/10.1007/978-1-4939-6563-2_11.
Повний текст джерелаThi Ngoc Nguyen, Thanh, Thu Huynh Ngoc Nguyen, Luan Huu Huynh, Hoang Ngo Phan, and Hue Thi Nguyen. "Predicting SNPs in Mature MicroRNAs Dysregulated in Breast Cancer." In Recent Advances in Non-Coding RNAs [Working Title]. IntechOpen, 2022. http://dx.doi.org/10.5772/intechopen.105514.
Повний текст джерелаТези доповідей конференцій з теми "MiRNA database"
Jukoski, Tayana Schultz, Talita Helen B. Gomig, Tamyres MIngorance Carvalho, Cicero Andrade Urban, and Enilze Maria Souza Fonseca Ribeiro. "IN SILICO AND PROTEOMICS APPROACHES SUGGEST UPREGULATION OF miR-146a-5p IN TNBC AND MODULATION OF CRITICAL PROTEINS." In Scientifc papers of XXIII Brazilian Breast Congress - 2021. Mastology, 2021. http://dx.doi.org/10.29289/259453942021v31s1051.
Повний текст джерелаTeixeira, Lívia, Izabela Conceição, Paulo Caramelli, Marcelo Luizon, and Karina Gomes. "ALZHEIMER’S DISEASE AND TYPE 2 DIABETES MELLITUS: COMMON MIRNAS, GENES AND REGULATORY BIOLOGICAL PATHWAYS." In XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda066.
Повний текст джерела"Databases and computer resources on plant miRNA to study its role in abiotic stress response." In Plant Genetics, Genomics, Bioinformatics, and Biotechnology. Institute of Cytology and Genetics, Siberian Branch of the Russian Academy of Sciences, 2019. http://dx.doi.org/10.18699/plantgen2019-132.
Повний текст джерелаYafen Chen, Yafen, Xiaoai Xiaoai Chen, Rong Rong Wang, Yiwei Yiwei Wang, Ping Ping Zhou, and Ke Ke Wang. "A Data Mining Method to Find Differentially Expressed miRNAs Using Access Database Language." In 2015 International Conference on Mechanical Science and Engineering. Paris, France: Atlantis Press, 2016. http://dx.doi.org/10.2991/mse-15.2016.43.
Повний текст джерелаChakraborty, Rajkumar, and Yasha Hasija. "miDerma: An Integrated Database and Tool for Analysis of miRNAs associated with Dermatological Disorders." In 2018 International Conference on Bioinformatics and Systems Biology (BSB). IEEE, 2018. http://dx.doi.org/10.1109/bsb.2018.8770557.
Повний текст джерелаЗвіти організацій з теми "MiRNA database"
Wu, Bin, Lixia Guo, Kaikai Zhen, and Chao Sun. Diagnostic and prognostic value of miRNAs in hepatoblastoma: A systematic review with meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, November 2021. http://dx.doi.org/10.37766/inplasy2021.11.0045.
Повний текст джерела