Добірка наукової літератури з теми "MiRNA target"
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Статті в журналах з теми "MiRNA target"
Li, Peng, Yi Chen, Conslata Awino Juma, Chengyong Yang, Jinfeng Huang, Xiaoxiao Zhang, and Yan Zeng. "Differential Inhibition of Target Gene Expression by Human microRNAs." Cells 8, no. 8 (July 30, 2019): 791. http://dx.doi.org/10.3390/cells8080791.
Повний текст джерелаKomatsu, Shintaro, Hiroki Kitai, and Hiroshi I. Suzuki. "Network Regulation of microRNA Biogenesis and Target Interaction." Cells 12, no. 2 (January 13, 2023): 306. http://dx.doi.org/10.3390/cells12020306.
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 джерелаMohebbi, Mohammad, Liang Ding, Russell L. Malmberg, Cory Momany, Khaled Rasheed, and Liming Cai. "Accurate prediction of human miRNA targets via graph modeling of the miRNA-target duplex." Journal of Bioinformatics and Computational Biology 16, no. 04 (August 2018): 1850013. http://dx.doi.org/10.1142/s0219720018500130.
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 джерелаPraher, Daniela, Bob Zimmermann, Rohit Dnyansagar, David J. Miller, Aurelie Moya, Vengamanaidu Modepalli, Arie Fridrich, et al. "Conservation and turnover of miRNAs and their highly complementary targets in early branching animals." Proceedings of the Royal Society B: Biological Sciences 288, no. 1945 (February 24, 2021): 20203169. http://dx.doi.org/10.1098/rspb.2020.3169.
Повний текст джерелаZHENG, YUN, and WEIXIONG ZHANG. "ANIMAL MICRORNA TARGET PREDICTION USING DIVERSE SEQUENCE-SPECIFIC DETERMINANTS." Journal of Bioinformatics and Computational Biology 08, no. 04 (August 2010): 763–88. http://dx.doi.org/10.1142/s0219720010004896.
Повний текст джерелаMcGeary, Sean E., Kathy S. Lin, Charlie Y. Shi, Thy M. Pham, Namita Bisaria, Gina M. Kelley, and David P. Bartel. "The biochemical basis of microRNA targeting efficacy." Science 366, no. 6472 (December 5, 2019): eaav1741. http://dx.doi.org/10.1126/science.aav1741.
Повний текст джерелаALKANLI, Nevra, and Arzu AY. "Kanser Gelişimi ve Progresyonunda miRNA’LAR VE miRNA Gen Varyasyonları." Gevher Nesibe Journal IESDR 6, no. 13 (July 25, 2021): 38–45. http://dx.doi.org/10.46648/gnj.226.
Повний текст джерелаChen, Jiajia, and Liangzhi Li. "Multiple Regression Analysis Reveals MicroRNA Regulatory Networks in Oryza sativa under Drought Stress." International Journal of Genomics 2018 (October 4, 2018): 1–12. http://dx.doi.org/10.1155/2018/9395261.
Повний текст джерелаДисертації з теми "MiRNA target"
Gebhardt, Marie Luise. "Enrichment of miRNA targets in REST-regulated genes allows filtering of miRNA target predictions." Doctoral thesis, Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät, 2016. http://dx.doi.org/10.18452/17407.
Повний текст джерелаPredictions of miRNA binding sites suffer from high false positive rates (24-70%) and measuring biological interactions of miRNAs and target transcripts on a genome wide scale remains challenging. In the thesis at hand the question was answered if the ever growing body of ChIP-sequencing data can be applied to filter miRNA target predictions by making use of the underlying regulatory network of miRNAs and transcription factors. First different methods for association of ChIP-sequencing peaks to target genes were tested. Target gene lists of the transcriptional repressor RE1-silencing transcription factor (REST/NRSF) were generated by means of ChIP-sequencing data. An enrichment analysis tool based on predictions from TargetScanHuman was developed and applied to find ‘enrichment’-miRNAs with over-represented targets in the REST gene lists. The detected miRNAs were shown to be part of a highly regulated REST-miRNA network. Possible functions could be assigned to them and their role in the regulatory network and special network motifs (incoherent feedforward loop of type 2) was analyzed. It turned out that miRNA target predictions of genes shared by enrichment-miRNAs and REST had a higher proportion of true positive associations than the TargetScanHuman background, thus the procedure made a filtering possible.
Bitetti, Angelo. "MiRNA degradation by a conserved target RNA regulates animal behavior." Thesis, Paris 6, 2017. http://www.theses.fr/2017PA066276.
Повний текст джерелаThe goal of my main thesis project was to determine the biological function of a deeply conserved zebrafish long noncoding RNAs (lncRNA) which we called libra. libra shows sequence similarity with the 3'UTR of the NREP a protein coding transcript. Both libra and Nrep contain a deeply conserved and unusually complementary microRNA (miRNA) binding site for miR-29. Using both the mouse model and mouse cell lines, we deciphered the regulatory relationship between this conserved transcript and the miRNA pathway. We showed that Nrep restricts the spatial expression domain of miR-29 in the cerebellum and that it destabilizes miR-29 through 3' trimming. Until now, only viral transcripts and artificial reporters engineered to contain highly complementary miRNA binding sites have been shown to regulate miRNAs in this fashion. Thus, our work uncovers the first example of endogenous target-directed miRNA degradation (TDMD). In addition, through a set of in vivo experiments in zebrafish and mouse, we showed that both libra and Nrep control normal animal behavior. By genetically disrupting the miR-29 binding site in Nrep in mouse, we showed that Nrep regulates miR-29 dosage through its miR-29 site and controls animal behavioral. In a second part of my thesis I describe a strategy to genetically downregulate lncRNAs in a minimally invasive manner. Approaches to knock-out lncRNAs that do not introduce vast sequence changes at the genomic level have not been adequately developed yet. I present our in vivo strategy applied to the zebrafish model using a genomic knock-in of a self-cleaving ribozyme sequence and a premature poly(A) signal to knock-out lncRNAs
Gebhardt, Marie Luise [Verfasser], Uwe [Akademischer Betreuer] Ohler, Miguel [Akademischer Betreuer] Andrade, and Ana [Akademischer Betreuer] Pombo. "Enrichment of miRNA targets in REST-regulated genes allows filtering of miRNA target predictions / Marie Luise Gebhardt. Gutachter: Uwe Ohler ; Miguel Andrade ; Ana Pombo." Berlin : Lebenswissenschaftliche Fakultät, 2016. http://d-nb.info/108141846X/34.
Повний текст джерелаGebhardt, Marie [Verfasser], Uwe [Akademischer Betreuer] Ohler, Miguel [Akademischer Betreuer] Andrade, and Ana [Akademischer Betreuer] Pombo. "Enrichment of miRNA targets in REST-regulated genes allows filtering of miRNA target predictions / Marie Luise Gebhardt. Gutachter: Uwe Ohler ; Miguel Andrade ; Ana Pombo." Berlin : Lebenswissenschaftliche Fakultät, 2016. http://d-nb.info/108141846X/34.
Повний текст джерелаFrampton, Adam. "The complex network of miRNA and mRNA target interactions in pancreatic cancer." Thesis, Imperial College London, 2014. http://hdl.handle.net/10044/1/24951.
Повний текст джерелаBosson, Andrew D. (Andrew David). "Modulation of Ago-miRNA regulatory networks by cis-sequence elements and target competition." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/89938.
Повний текст джерелаVita. Cataloged from PDF version of thesis.
Includes bibliographical references.
regulators of gene expression in a wide range of organisms and biological processes. Each miRNA guides Argonaute (Ago) protein complexes to target and repress hundreds of genes in a sequence-dependent manner. To identify all targets of miRNA regulation, we performed UV crosslinking and immunoprecipitation (CLIP) of Ago complexes in mouse embryonic (ESC) and mesenchymal (MSC) stem cell lines. We also captured the genome-wide miRNA-independent binding footprint of Ago by performing CLIP in cells that lack Dicer, an enzyme required for mature miRNA biogenesis. We surprisingly found that Ago bound a similar set of genes in the absence of Dicer, and this overlap in target genes was due partially to residual, unprocessed miRNAs in the Dicer KO cells. Other potential sites of miRNA-independent Ago interactions, such as histone transcripts and poly-A cleavage and polyadenylation sites, were also identified. One Ago CLIP dataset revealed the enrichment for a G-rich sequence motif at Ago target sites. We later demonstrated that the G-motif is not directly bound to Ago but rather is enriched near miRNA-guided Ago binding sites. Its presence near miRNA target sites is associated with stronger repression of Ago-miRNA targets. Fortuitously, the original Ago CLIP dataset that identified the G-motif was later shown to likely contain target sites of another co-immunoprecipitating RNA binding protein (RBP). Using mass spectroscopy of Ago antibody immunoprecipitations from Ago KO cells, we identified a list of interacting RBPs that could potentially augment Ago-miRNA activity through the G-motif. To investigate target competition in miRNA networks, we related our CLIP analysis of genome-wide, quantitative Ago binding to measurements of absolute miRNA and target RNA concentrations. We found that all miRNAs other than the miR-290 family in ESCs and let-7 family in MSCs were expressed at concentrations below their total target pool. However, 8-12 miRNA families were expressed at near or greater than equimolar ratios with their pool of high affinity targets, and this affinity-partitioned stoichiometry led to significant Ago accumulation and repression of high affinity target sites despite little consequential binding at low affinity sites. Single-cell reporter assays demonstrated that high expressed miRNAs are not susceptible to physiological inductions of competing target transcripts but targets of lower expressed miRNAs are derepressed in a weakly threshold-like manner upon increased target pool levels. In summary, we identify a network of confidently bound targets of miRNA regulation in ESCs and MSCs, reveal the extent of miRNA-independent binding in these two cell types, provide a list of potential miRNA enhancer RBPs, and create a quantitative context for evaluating target competition in miRNA networks.
by Andrew D. Bosson.
Ph. D.
Warrander, Fiona. "The role of lin28, an FGF signalling target, in development and miRNA regulation." Thesis, University of York, 2012. http://etheses.whiterose.ac.uk/3389/.
Повний текст джерелаReimegård, Johan. "Making Sense of Antisense." Doctoral thesis, Uppsala universitet, Mikrobiologi, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-131168.
Повний текст джерелаSlaibi, Jinani Elias. "Targets of Hsa-miR-488* In Human Prostate Carcinoma Cells." Cleveland State University / OhioLINK, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=csu1273843449.
Повний текст джерелаHigashi, Susan. "MiRNA and co : methodologically exploring the world of small RNAs." Thesis, Lyon 1, 2014. http://www.theses.fr/2014LYO10252/document.
Повний текст джерелаThe main contribution of this thesis is the development of a reliable, robust, and much faster method for the prediction of pre-miRNAs. With this method, we aimed mainly at two goals: efficiency and flexibility. Efficiency was made possible by means of a quadratic algorithm. Flexibility relies on two aspects, the input type and the organism clade. Mirinho can receive as input both a genome sequence and small RNA sequencing (sRNA-seq) data of both animal and plant species. To change from one clade to another, it suffices to change the lengths of the stem-arms and of the terminal loop. Concerning the prediction of plant miRNAs, because their pre-miRNAs are longer, the methods for extracting the hairpin secondary structure are not as accurate as for shorter sequences. With Mirinho, we also addressed this problem, which enabled to provide pre-miRNA secondary structures more similar to the ones in miRBase than the other available methods. Mirinho served as the basis to two other issues we addressed. The first issue led to the treatment and analysis of sRNA-seq data of Acyrthosiphon pisum, the pea aphid. The goal was to identify the miRNAs that are expressed during the four developmental stages of this species, allowing further biological conclusions concerning the regulatory system of such an organism. For this analysis, we developed a whole pipeline, called MirinhoPipe, at the end of which Mirinho was aggregated. We then moved on to the second issue, that involved problems related to the prediction and analysis of non-coding RNAs (ncRNAs) in the bacterium Mycoplasma hyopneumoniae. A method, called Alvinho, was thus developed for the prediction of targets in this bacterium, together with a pipeline for the segmentation of a numerical sequence and detection of conservation among ncRNA sequences using a kpartite graph. We finally addressed a problem related to motifs, that is to patterns, that may be composed of one or more parts, that appear conserved in a set of sequences and may correspond to functional elements
Книги з теми "MiRNA target"
Schmidt, Marco F., ed. Drug Target miRNA. New York, NY: Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6563-2.
Повний текст джерелаSethi, Seema. miRNAs and Target Genes in Breast Cancer Metastasis. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-08162-5.
Повний текст джерелаSchmidt, Marco F. Drug Target MiRNA: Methods and Protocols. Springer New York, 2018.
Знайти повний текст джерелаSchmidt, Marco F. Drug Target Mirna: Methods and Protocols. Springer New York, 2016.
Знайти повний текст джерелаSethi, Seema. miRNAs and Target Genes in Breast Cancer Metastasis. Springer, 2014.
Знайти повний текст джерелаSethi, Seema. MiRNAs and Target Genes in Breast Cancer Metastasis. Springer, 2014.
Знайти повний текст джерелаReckman, Yolan J., and Yigal M. Pinto. The role of non-coding RNA/microRNAs in cardiac disease. Edited by José Maria Pérez-Pomares, Robert G. Kelly, Maurice van den Hoff, José Luis de la Pompa, David Sedmera, Cristina Basso, and Deborah Henderson. Oxford University Press, 2018. http://dx.doi.org/10.1093/med/9780198757269.003.0031.
Повний текст джерелаЧастини книг з теми "MiRNA target"
Zhang, Yan. "MiRNA Target." In Encyclopedia of Systems Biology, 1374–75. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4419-9863-7_324.
Повний текст джерелаHeyn, Jens, Ludwig Christian Hinske, Carola Ledderose, Elisabeth Limbeck, and Simone Kreth. "Experimental miRNA Target Validation." In MicroRNA Protocols, 83–90. Totowa, NJ: Humana Press, 2012. http://dx.doi.org/10.1007/978-1-62703-083-0_7.
Повний текст джерелаYounger, Scott T., and David R. Corey. "Identification and Validation of miRNA Target Sites Within Nontraditional miRNA Targets." In Methods in Molecular Biology, 53–67. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1369-5_5.
Повний текст джерелаFahlgren, Noah, and James C. Carrington. "miRNA Target Prediction in Plants." In Methods in Molecular Biology, 51–57. Totowa, NJ: Humana Press, 2009. http://dx.doi.org/10.1007/978-1-60327-005-2_4.
Повний текст джерелаLukasik, Anna, and Piotr Zielenkiewicz. "An Overview of miRNA and miRNA Target Analysis Tools." In Methods in Molecular Biology, 65–87. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9042-9_5.
Повний текст джерелаTang, Guiliang, Yu Xiang, Zhensheng Kang, Venugopal Mendu, Xiaohu Tang, Xiaoyun Jia, Qi-Jun Chen, and Xiaoqing Tang. "Small RNA Technologies: siRNA, miRNA, antagomiR, Target Mimicry, miRNA Sponge and miRNA Profiling." In Current Perspectives in microRNAs (miRNA), 17–33. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-8533-8_2.
Повний текст джерелаDweep, 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 джерелаRahman, Fazlur, Sajjadul Kadir Akand, Muniba Faiza, Shams Tabrez, and Abdur Rub. "miRNA Target Prediction: Overview and Applications." In Integrated Omics Approaches to Infectious Diseases, 241–53. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-0691-5_14.
Повний текст джерелаWang, Zhiguo. "Multiple-Target Anti-miRNA Antisense Oligonucleotides Technology." In MicroRNA Interference Technologies, 145–51. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-00489-6_8.
Повний текст джерелаAkhtar, Most Mauluda, Luigina Micolucci, Md Soriful Islam, Fabiola Olivieri, and Antonio Domenico Procopio. "A Practical Guide to miRNA Target Prediction." In Methods in Molecular Biology, 1–13. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9207-2_1.
Повний текст джерелаТези доповідей конференцій з теми "MiRNA target"
Zhang, Yanju, Jeroen S. de Bruin, and Fons J. Verbeek. "miRNA target prediction through mining of miRNA relationships." In 2008 8th IEEE International Conference on Bioinformatics and BioEngineering (BIBE). IEEE, 2008. http://dx.doi.org/10.1109/bibe.2008.4696695.
Повний текст джерелаMohebbi, Mohammad, Liang Ding, Russell L. Malmberg, Cory Momany, Khaled Rasheed, and Liming Cai. "Accurate prediction of human miRNA targets via graph modeling of miRNA-target duplex." In 2016 IEEE 6th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS). IEEE, 2016. http://dx.doi.org/10.1109/iccabs.2016.7802792.
Повний текст джерелаAhmed, Emad E., Sherin M. El-Gokhy, and Mohamed T. Faheem Saidahmed. "Enhanced framework for miRNA target prediction." In 2017 12th International Conference on Computer Engineering and Systems (ICCES). IEEE, 2017. http://dx.doi.org/10.1109/icces.2017.8275367.
Повний текст джерелаNing Wang, Yang Wang, Yaodong Yang, Yi Shen, and Ao Li. "miRNA Target Prediction Based on Gene Ontology." In 2013 6th International Symposium on Computational Intelligence and Design (ISCID). IEEE, 2013. http://dx.doi.org/10.1109/iscid.2013.113.
Повний текст джерелаZahid, Muhammad Ammar, and Abdelali Agouni. "Identification of a miRNA signature as a diagnostic and prognostic marker in renal cell carcinoma." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2021. http://dx.doi.org/10.29117/quarfe.2021.0109.
Повний текст джерелаHui Liu, Dong Yue, Lin Zhang, and Yu-Fei Huang. "A SVM based approach for miRNA target prediction." In 2008 International Conference on Machine Learning and Cybernetics (ICMLC). IEEE, 2008. http://dx.doi.org/10.1109/icmlc.2008.4621103.
Повний текст джерелаHui Liu, Dong Yue, Lin Zhang, Shou-Jiang Gao, and Yufei Huang. "A machine learning approach for miRNA target prediction." In 2008 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2008. http://dx.doi.org/10.1109/gensips.2008.4555655.
Повний текст джерелаPapamichail, Dimitris, and Georgios Papamichail. "Incorporating miRNA target sites in protein-coding RNA." In 2010 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW). IEEE, 2010. http://dx.doi.org/10.1109/bibmw.2010.5703832.
Повний текст джерелаJung, Daekyoung, Sehi L'Yi, Bohyoung Kim, and Jinwook Seo. "Interactive visual analysis of miRNA target prediction results." In 2017 IEEE International Conference on Big Data and Smart Computing (BigComp). IEEE, 2017. http://dx.doi.org/10.1109/bigcomp.2017.7881694.
Повний текст джерелаBeretta, Stefano, Lucia Morganti, Elena Corni, Andrea Ferraro, Daniele Cesini, Daniele D'Agostino, Luciano Milanesi, and Ivan Merelli. "Low-Power Architectures for miRNA-Target Genome Wide Analysis." In 2017 25th Euromicro International Conference on Parallel, Distributed and Network-based Processing (PDP). IEEE, 2017. http://dx.doi.org/10.1109/pdp.2017.88.
Повний текст джерелаЗвіти організацій з теми "MiRNA target"
Arazi, Tzahi, Vivian Irish, and Asaph Aharoni. Micro RNA Targeted Transcription Factors for Fruit Quality Improvement. United States Department of Agriculture, July 2008. http://dx.doi.org/10.32747/2008.7592651.bard.
Повний текст джерелаLers, Amnon, and Pamela J. Green. Analysis of Small RNAs Associated with Plant Senescence. United States Department of Agriculture, March 2013. http://dx.doi.org/10.32747/2013.7593393.bard.
Повний текст джерелаSun, Lina, Yanan Han, Hua Wang, Huanyu Liu, Shan Liu, Hongbin Yang, Xiaoxia Ren, and Ying Fang. MicroRNAs as Potential Biomarkers for the Diagnosis of Inflammatory Bowel Disease: A Systematic Review and Meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, February 2022. http://dx.doi.org/10.37766/inplasy2022.2.0027.
Повний текст джерелаWhitham, Steven A., Amit Gal-On, and Victor Gaba. Post-transcriptional Regulation of Host Genes Involved with Symptom Expression in Potyviral Infections. United States Department of Agriculture, June 2012. http://dx.doi.org/10.32747/2012.7593391.bard.
Повний текст джерелаGreen, Pamela J. Genome-Wide Analysis of miRNA targets in Brachypodium and Biomass Energy Crops. Office of Scientific and Technical Information (OSTI), August 2015. http://dx.doi.org/10.2172/1209217.
Повний текст джерелаGrumet, Rebecca, Rafael Perl-Treves, and Jack Staub. Ethylene Mediated Regulation of Cucumis Reproduction - from Sex Expression to Fruit Set. United States Department of Agriculture, February 2010. http://dx.doi.org/10.32747/2010.7696533.bard.
Повний текст джерелаWhitham, Steven A., Amit Gal-On, and Tzahi Arazi. Functional analysis of virus and host components that mediate potyvirus-induced diseases. United States Department of Agriculture, March 2008. http://dx.doi.org/10.32747/2008.7591732.bard.
Повний текст джерела