Relevant bibliographies by topics / MiRNA database

Academic literature on the topic 'MiRNA database'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "MiRNA database"

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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.

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Background: Determination of functional pathways regulated by microRNAs (miRNAs), while an essential step in developing therapeutics, is challenging. Some miRNAs have been studied extensively; others have limited information. In this study, we focus on 254 miRNAs previously identified as being associated with colorectal cancer and their database-identified validated target genes. Methods: We use RNA-Seq data to evaluate messenger RNA (mRNA) expression for 157 subjects who also had miRNA expression data. In the replication phase of the study, we replicated associations between 254 miRNAs associated with colorectal cancer and mRNA expression of database-identified target genes in normal colonic mucosa. In the discovery phase of the study, we evaluated expression of 18 miRNAs (those with 20 or fewer database-identified target genes along with miR-21-5p, miR-215-5p, and miR-124-3p which have more than 500 database-identified target genes) with expression of 17 434 mRNAs to identify new targets in colon tissue. Seed region matches between miRNA and newly identified targeted mRNA were used to help determine direct miRNA-mRNA associations. Results: From the replication of the 121 miRNAs that had at least 1 database-identified target gene using mRNA expression methods, 97.9% were expressed in normal colonic mucosa. Of the 8622 target miRNA-mRNA associations identified in the database, 2658 (30.2%) were associated with gene expression in normal colonic mucosa after adjusting for multiple comparisons. Of the 133 miRNAs with database-identified target genes by non-mRNA expression methods, 97.2% were expressed in normal colonic mucosa. After adjustment for multiple comparisons, 2416 miRNA-mRNA associations remained significant (19.8%). Results from the discovery phase based on detailed examination of 18 miRNAs identified more than 80 000 miRNA-mRNA associations that had not previously linked to the miRNA. Of these miRNA-mRNA associations, 15.6% and 14.8% had seed matches for CRCh38 and CRCh37, respectively. Conclusions: Our data suggest that miRNA target gene databases are incomplete; pathways derived from these databases have similar deficiencies. Although we know a lot about several miRNAs, little is known about other miRNAs in terms of their targeted genes. We encourage others to use their data to continue to further identify and validate miRNA-targeted genes.
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Hou, 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.

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Background. MicroRNAs (miRNAs) are confirmed to participate in occurrence, development, and prevention of membranous nephropathy (MN), but their mechanism of action is unclear. Objective. With the GEO database and the use of bioinformatics, miRNA-mRNA regulatory network genes relevant to MN were explored and their potential mechanism of action was explained. Methods. The MN-related miRNA chip data set (GSE51674) and mRNA chip data set (GSE108109) were downloaded from the GEO database. Differential analysis was performed using the GEO2R online tool. TargetScan, miRTarBase, and StarBase databases were used to predict potential downstream target genes regulated by differentially expressed miRNAs, and the intersection with differential genes were taken to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair was clarified and Cytoscape was used to construct a miRNA-mRNA regulatory network. WebGestalt was used to conduct enrichment analysis of the biological process of differential mRNAs in the regulatory network; FunRich analyzes the differential mRNA pathways in the miRNA-mRNA regulatory network. And the STRING database was used to construct a PPI network for candidate target genes, and Cytoscape visually analyzes the PPI network. Results. Experiments were conducted to screen differentially expressed miRNAs and mRNAs. There were 30 differentially expressed miRNAs, including 22 upregulated and 8 downregulated; and 1267 differentially expressed mRNAs, including 536 upregulated and 731 downregulated. Using TargetScan, miRTarBase, and StarBase databases to predict the downstream targets of differentially expressed miRNAs, 2957 downstream target genes coexisting in the 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 175 candidate target genes. Finally, 36 miRNA-mRNA relationship pairs comprising 10 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out, and the regulatory network was constructed. Further analysis revealed that the miRNA regulatory network genes may be involved in the development of membranous nephropathy by mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways. Conclusion. The miRNA regulatory network genes may participate in the regulation of podocyte autophagy, lipid metabolism, and renal fibrosis through mTOR, PDGFR-β, LKB1, and VEGF/VEGFR signaling pathways, thereby affecting the occurrence and development of membranous nephropathy.
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Li, 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.

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Background. MicroRNA (miRNA) has been confirmed to be involved in the occurrence, development, and prevention of diabetic nephropathy (DN), but its mechanism of action is still unclear. Objective. With the help of the GEO database, bioinformatics methods are used to explore the miRNA-mRNA regulatory relationship pairs related to diabetic nephropathy and explain their potential mechanisms of action. Methods. The DN-related miRNA microarray dataset (GSE51674) and mRNA expression dataset (GSE30122) are downloaded through the GEO database, online analysis tool GEO2R is used for data differential expression analysis, TargetScan, miRTarBase, and miRDB databases are used to predict potential downstream target genes regulated by differentially expressed miRNAs, and intersection with differential genes is used to obtain candidate target genes. According to the regulatory relationship between miRNA and mRNA, the miRNA-mRNA relationship pair is clarified, and the miRNA-mRNA regulatory network is constructed using Cytoscape. DAVID is used to perform GO function enrichment analysis and KEGG pathway analysis of candidate target genes. By GeneMANIA prediction of miRNA target genes and coexpressed genes, the protein interaction network is constructed. Results and Conclusions. A total of 67 differentially expressed miRNAs were screened in the experiment, of which 42 were upregulated and 25 were downregulated; a total of 448 differentially expressed mRNAs were screened, of which 93 were upregulated and 355 were downregulated. Using TargetScan, miRTarBase, and miRDB databases to predict downstream targets of differentially expressed miRNAs, 2283 downstream target genes coexisting in 3 databases were predicted to intersect with differentially expressed mRNAs to obtain 96 candidate target genes. Finally, 44 miRNA-mRNA relationship pairs consisting of 12 differentially expressed miRNAs and 27 differentially expressed mRNAs were screened out; further analysis showed that miRNA regulatory network genes may participate in the occurrence and development of diabetic nephropathy through PI3K/Akt, ECM-receptor interaction pathway, and RAS signaling pathway.
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Chen, 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.

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Abstract MicroRNAs (miRNAs) are small noncoding RNAs that act as master regulators in many biological processes. miRNAs function mainly by downregulating the expression of their gene targets. Thus, accurate prediction of miRNA targets is critical for characterization of miRNA functions. To this end, we have developed an online database, miRDB, for miRNA target prediction and functional annotations. Recently, we have performed major updates for miRDB. Specifically, by employing an improved algorithm for miRNA target prediction, we now present updated transcriptome-wide target prediction data in miRDB, including 3.5 million predicted targets regulated by 7000 miRNAs in five species. Further, we have implemented the new prediction algorithm into a web server, allowing custom target prediction with user-provided sequences. Another new database feature is the prediction of cell-specific miRNA targets. miRDB now hosts the expression profiles of over 1000 cell lines and presents target prediction data that are tailored for specific cell models. At last, a new web query interface has been added to miRDB for prediction of miRNA functions by integrative analysis of target prediction and Gene Ontology data. All data in miRDB are freely accessible at http://mirdb.org.
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Liu, 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.

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Abstract MicroRNAs (miRNAs) related single-nucleotide variations (SNVs), including single-nucleotide polymorphisms (SNPs) and disease-related variations (DRVs) in miRNAs and miRNA-target binding sites, can affect miRNA functions and/or biogenesis, thus to impact on phenotypes. miRNASNP is a widely used database for miRNA-related SNPs and their effects. Here, we updated it to miRNASNP-v3 (http://bioinfo.life.hust.edu.cn/miRNASNP/) with tremendous number of SNVs and new features, especially the DRVs data. We analyzed the effects of 7 161 741 SNPs and 505 417 DRVs on 1897 pre-miRNAs (2630 mature miRNAs) and 3′UTRs of 18 152 genes. miRNASNP-v3 provides a one-stop resource for miRNA-related SNVs research with the following functions: (i) explore associations between miRNA-related SNPs/DRVs and diseases; (ii) browse the effects of SNPs/DRVs on miRNA-target binding; (iii) functional enrichment analysis of miRNA target gain/loss caused by SNPs/DRVs; (iv) investigate correlations between drug sensitivity and miRNA expression; (v) inquire expression profiles of miRNAs and their targets in cancers; (vi) browse the effects of SNPs/DRVs on pre-miRNA secondary structure changes; and (vii) predict the effects of user-defined variations on miRNA-target binding or pre-miRNA secondary structure. miRNASNP-v3 is a valuable and long-term supported resource in functional variation screening and miRNA function studies.
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Pian, 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.

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Abstract miRNAs represent a type of noncoding small molecule RNA. Many studies have shown that miRNAs are widely involved in the regulation of various pathways. The key to fully understanding the regulatory function of miRNAs is the determination of the pathways in which the miRNAs participate. However, the major pathway databases such as KEGG only include information regarding protein-coding genes. Here, we redesigned a pathway database (called miR+Pathway) by integrating and visualizing the 8882 human experimentally validated miRNA-target interactions (MTIs) and 150 KEGG pathways. This database is freely accessible at http://www.insect-genome.com/miR-pathway. Researchers can intuitively determine the pathways and the genes in the pathways that are regulated by miRNAs as well as the miRNAs that target the pathways. To determine the pathways in which targets of a certain miRNA or multiple miRNAs are enriched, we performed a KEGG analysis miRNAs by using the hypergeometric test. In addition, miR+Pathway provides information regarding MTIs, PubMed IDs and the experimental verification method. Users can retrieve pathways regulated by an miRNA or a gene by inputting its names.
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Park, 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.

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microRNAs (miRNAs) have been established as critical regulators of the pathogenesis of diabetes mellitus (DM), and diabetes microvascular complications (DMCs). However, manually curated databases for miRNAs, and DM (including DMCs) association studies, have yet to be established. Here, we constructed a user-friendly database, “miR2Diabetes,” equipped with a graphical web interface for simple browsing or searching manually curated annotations. The annotations in our database cover 14 DM and DMC phenotypes, involving 156 miRNAs, by browsing diverse sample origins (e.g., blood, kidney, liver, and other tissues). Additionally, we provide miRNA annotations for disease-model organisms (including rats and mice), of DM and DMCs, for the purpose of improving knowledge of the biological complexity of these pathologies. We assert that our database will be a comprehensive resource for miRNA biomarker studies, as well as for prioritizing miRNAs for functional validation, in DM and DMCs, with likely extension to other diseases.
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Huang, 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.

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Abstract MicroRNAs (miRNAs) are noncoding RNAs with 18–26 nucleotides; they pair with target mRNAs to regulate gene expression and produce significant changes in various physiological and pathological processes. In recent years, the interaction between miRNAs and their target genes has become one of the mainstream directions for drug development. As a large-scale biological database that mainly provides miRNA–target interactions (MTIs) verified by biological experiments, miRTarBase has undergone five revisions and enhancements. The database has accumulated >2 200 449 verified MTIs from 13 389 manually curated articles and CLIP-seq data. An optimized scoring system is adopted to enhance this update’s critical recognition of MTI-related articles and corresponding disease information. In addition, single-nucleotide polymorphisms and disease-related variants related to the binding efficiency of miRNA and target were characterized in miRNAs and gene 3′ untranslated regions. miRNA expression profiles across extracellular vesicles, blood and different tissues, including exosomal miRNAs and tissue-specific miRNAs, were integrated to explore miRNA functions and biomarkers. For the user interface, we have classified attributes, including RNA expression, specific interaction, protein expression and biological function, for various validation experiments related to the role of miRNA. We also used seed sequence information to evaluate the binding sites of miRNA. In summary, these enhancements render miRTarBase as one of the most research-amicable MTI databases that contain comprehensive and experimentally verified annotations. The newly updated version of miRTarBase is now available at https://miRTarBase.cuhk.edu.cn/.
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Kehl, 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.

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Abstract Since the initial release of miRPathDB, tremendous progress has been made in the field of microRNA (miRNA) research. New miRNA reference databases have emerged, a vast amount of new miRNA candidates has been discovered and the number of experimentally validated target genes has increased considerably. Hence, the demand for a major upgrade of miRPathDB, including extended analysis functionality and intuitive visualizations of query results has emerged. Here, we present the novel release 2.0 of the miRNA Pathway Dictionary Database (miRPathDB) that is freely accessible at https://mpd.bioinf.uni-sb.de/. miRPathDB 2.0 comes with a ten-fold increase of pre-processed data. In total, the updated database provides putative associations between 27 452 (candidate) miRNAs, 28 352 targets and 16 833 pathways for Homo sapiens, as well as interactions of 1978 miRNAs, 24 898 targets and 6511 functional categories for Mus musculus. Additionally, we analyzed publications citing miRPathDB to identify common use-cases and further extensions. Based on this evaluation, we added new functionality for interactive visualizations and down-stream analyses of bulk queries. In summary, the updated version of miRPathDB, with its new custom-tailored features, is one of the most comprehensive and advanced resources for miRNAs and their target pathways.
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Liu, 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.

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Background. Breast cancer is a malignant tumor that occurs in the epithelial tissue of the breast gland and has become the most common malignancy in women. The regulation of the expression of related genes by microRNA (miRNA) plays an important role in breast cancer. We constructed a comprehensive breast cancer-miRNA-gene interaction map. Methods. Three miRNA microarray datasets (GSE26659, GSE45666, and GSE58210) were obtained from the GEO database. Then, the R software “LIMMA” package was used to identify differential expression analysis. Potential transcription factors and target genes of screened differentially expressed miRNAs (DE-miRNAs) were predicted. The BRCA GE-mRNA datasets (GSE109169 and GSE139038) were downloaded from the GEO database for identifying differentially expressed genes (DE-genes). Next, GO annotation and KEGG pathway enrichment analysis were conducted. A PPI network was then established, and hub genes were identified via Cytoscape software. The expression and prognostic roles of hub genes were further evaluated. Results. We found 6 upregulated differentially expressed- (DE-) miRNAs and 18 downregulated DE-miRNAs by analyzing 3 Gene Expression Omnibus databases, and we predicted the upstream transcription factors and downstream target genes for these DE-miRNAs. Then, we used the GEO database to perform differential analysis on breast cancer mRNA and obtained differentially expressed mRNA. We found 10 hub genes of upregulated DE-miRNAs and 10 hub genes of downregulated DE-miRNAs through interaction analysis. Conclusions. In this study, we have performed an integrated bioinformatics analysis to construct a more comprehensive BRCA-miRNA-gene network and provide new targets and research directions for the treatment and prognosis of BRCA.
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Dissertations / Theses on the topic "MiRNA database"

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Bou, Zeidan Nadim Georges. "Human miRNA Sequence Based Variations Database." Scholar Commons, 2014. https://scholarcommons.usf.edu/etd/5350.

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MicroRNAs (miRNAs) are studied as key genetic elements that regulate the gene expression involved in different human diseases. Clinical sequence based variations like copy number variations (CNVs) affect miRNA biogenesis, dosage and target recognition that may represent potentially functional variants and relevant target bindings. To systematically analyze miRNA-related CNVs and their effects on related genes, a user-friendly free online database was developed to provide further analysis of co-localization of miRNA loci with human genome CNV regions. Further analysis pipelines such as miRNA-target to estimate the levels or locations of variations for genetic duplications, insertions or deletions were also offered. Such information could support the simulation of miRNA-target interactions.
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Prakash, 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.

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Zhuang, 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.

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碩士
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.
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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.

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碩士
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/.
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Wen, Jiayu. "In silico prediction of active RNA genes in legumes." Phd thesis, 2007. http://hdl.handle.net/1885/49423.

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Accumulating evidence suggests that non-coding RNAs (ncRNAs) play key roles in gene regulation and may form the basis of an inter-gene communication system. MicroRNAs are a class of small non-coding RNAs found in both plants and animals that regulate the expression of other genes. Identification and analysis of microRNAs enhances our understanding of the important roles that microRNAs play in this complex regulatory network. The work presented in this thesis constitutes the first large-scale prediction and characterization of both ncRNAs and miRNAs in the model legume Medicago truncatula and Lotus japonicus, and provides a basis for further research on elucidating ncRNA function in legume genomics...
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Lee, 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.

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碩士
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.
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Book chapters on the topic "MiRNA database"

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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.

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Hinske, 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.

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Lv, 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.

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Zhang, 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.

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Kumaran, 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.

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de 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.

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Bansal, 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.

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Kelarev, 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.

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Periwal, 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.

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Thi 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.

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Breast cancer (BC) is the leading type of cancer among women. Findings have revolutionized current knowledge of microRNA (miRNA) in breast tumorigenesis. The seed region of miRNA regulates the process of gene expression negatively. The presence of SNPs in the seed regions of miRNA dramatically alters the mature miRNA function. Additionally, SNPs in the out-seed region of miRNAs have a significant impact on miRNA targeting. This study focuses on the in silico analysis procedure of mature miRNA SNPs and their impact on BC risk. The database annotated SNPs on mature miRNAs was used. Also, target gene alterations, miRNAs function in BC, and the interaction of miRNAs with targets were predicted. A list of 101 SNPs in 100 miRNAs with functional targets in BC was indicated. Under the SNPs allele variation, 10 miRNAs changed function, 6 miRNAs lost targets, 15 miRNAs gained targets, 48 onco-miRNAs remained unchanged, and 21 tumor suppressor miRNAs remained unchanged. At last, a list of 89 SNPs, which alter miRNA function and miRNA-mRNA interaction, were shown to be potentially associated with BC risk. This research theoretically generated a list of possible causative SNPs in the mature miRNA gene that might be used in future BC management studies.
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Conference papers on the topic "MiRNA database"

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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.

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Introduction: Breast cancer (BC) is the most common type of cancer after non-melanoma skin tumors among Brazilian women, with 61.61 cases estimated for 100 thousand women in 2020. New biomarkers, such as miRNAs and selected proteins, are essential in personalized medicine. Objectives: To evaluate the expression and possible role of miR-146a-5p in subtypes of BC. Methods: miRNAs selection was performed using in silico analysis from the TCGA (The Cancer Genome Atlas) database. Data from the miRNAs expression of 1,085 patients were accessed and compared among BC subtypes. After normalization, the Bayesian Student t-test evaluated differential expression (DE) analysis via the limma R package. Lists with DE miRNAs were divided between up and down-regulated status (FC = ±2). A second approach was to submit the data obtained from BC samples´ mass spectrometry to IPA software to predict the activation/inhibition of upstream regulators in DE proteins lists in the tumor (T) versus contralateral tissue (CT). Results: A total of 206 upstream regulators were discovered at p <0.05; 12.6% of them were predicted with z-score values. In a TCGA analysis, miR-146a-5p was found up-regulated in triple-negative (TNBC) in comparison to other subtypes as a hormonal receptor (HR)+, HER2+, and non-TNBC (HR+ plus HER2+). The same was observed in TNBC cell lines by RT-qPCR. This miRNA was also predicted as an indirect regulator of CAT, LTF, CFH, and PGLYRP2 proteins in an IPA analysis. The proteomic analysis also demonstrated these molecules´ relation with cancer hallmarks such as invasion, inflammation, and immune response. Conclusions: The results suggest that miR-146a-5p deregulation has a role in BC, mainly in TNBC, via the regulation of essential proteins. A better understanding of these molecules in BC is critical to define new biomarkers.
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Teixeira, 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.

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Background: The increased incidence of Type 2 Diabetes Mellitus (T2DM) in the 21st century, along with the higher risk of developing Alzheimer’s disease (AD) in diabetic patients have stimulated the search for pathways that link glycemic disorders to neurodegeneration. MicroRNAs (miRNAs) are non-coding RNAs that play key roles in regulating gene expression. Objective: To identify miRNAs, genes and their regulatory pathways in common in AD and T2DM. Methods: Literature search was carried out to find miRNAs commonly expressed in AD and T2DM. MiRTarBase database was used to provide experimentally validated information on the interactions between miRNAs and their target genes. The functional enrichment of molecular pathways differentially regulated by these miRNAs was performed using EnrichR with Reactome gene set annotation. Results: We found six circulating miRNAs commonly expressed in both diseases (hsa-mir-21; hsamir-103a-1; hsa-mir-103a-2; hsa-mir-107; hsa-mir-146a and hsa-mir-144), which regulate 129 target genes. The common pathways between AD and T2DM were related to inflammatory mediators, cell death and axon formation signalling with p-adjust <10-5. Conclusion: Our study provides evidence that AD and T2DM share common pathophysiological mechanisms and regulators miRNAs, and suggests miRNAs as potential markers related to both diseases.
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"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.

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Yafen 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.

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Chakraborty, 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.

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Reports on the topic "MiRNA database"

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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.

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Review question / Objective: Background and aim: Increasing evidence has revealed the valuable diagnostic and prognostic applications of dysregulated microRNAs (miRNAs) in hepatoblastoma (HB), the most common hepatic malignancy during childhood. However, these results are inconsistent and remain to be elucidated. In the present study, we aimed to systematically compile up-to-date information regarding the clinical value of miRNAs in HB. Methods: Articles concerning the diagnostic and prognostic value of single miRNAs for HB were searched from databases. The sensitivity (SEN), specificity (SPE), positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), area under the curve (AUC), and hazard ratios (HRs) were separately pooled to explore the diagnostic and prognostic performance of miRNA. Subgroup and meta-regression analyses were further carried out only in the event of heterogeneity. Results: In all, 20 studies, involving 264 HB patients and 206 healthy individuals, met the inclusion criteria in the six included literature articles. For the diagnostic analysis of miRNAs in HB, the pooled SEN and SPE were 0.76 (95% CI: 0.72–0.80) and 0.75 (95% CI: 0.70–0.80), respectively. Moreover, the pooled PLR was 2.79 (95% CI: 2.12–3.66), NLR was 0.34 (95% CI: 0.26–0.45), DOR was 10.24 (95% CI: 6.55–16.00), and AUC was 0.83, indicating that miRNAs had moderate diagnostic value in HB. For the prognostic analysis of miRNAs in HB, the abnormal expressions of miR-21, miR-34a, miR-34b, miR-34c, miR-492, miR-193, miR-222, and miR-224 in patients were confirmed to be associated with a worse prognosis. The pooled HR was 1.74 (95% CI: 1.20–2.29) for overall survival (OS) and 1.74 (95% CI: 1.31–2.18) for event-free survival (EFS), suggesting its potential as a prognostic indicator for HB. Conclusion: To the best of our knowledge, this is the first comprehensive systematic review and meta-analysis that examines the diagnostic and prognostic role of dysregulated miRNAs in HB patients. The combined meta-analysis results supported the previous individual finds that miRNAs might provide a new, noninvasive method for the diagnostic and prognostic analyses ofHB.
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