Academic literature on the topic 'HUMAN TRANSCRIPTOME'
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Journal articles on the topic "HUMAN TRANSCRIPTOME"
Brenner, Eric, Gayatri R. Tiwari, Manav Kapoor, Yunlong Liu, Amy Brock, and R. Dayne Mayfield. "Single cell transcriptome profiling of the human alcohol-dependent brain." Human Molecular Genetics 29, no. 7 (March 6, 2020): 1144–53. http://dx.doi.org/10.1093/hmg/ddaa038.
Full textLondin, Eric R., Eleftheria Hatzimichael, Phillipe Loher, Leonard C. Edelstein, Chad Shaw, Kathleen Delgrosso, Paolo M. Fortina, Paul F. Bray, Steven E. McKenzie, and Isidore Rigoutsos. "Towards a Reference Human Platelet Transcriptome: Evaluation Of Inter-Individual Correlations and Its Relationship With a Platelet Proteome." Blood 122, no. 21 (November 15, 2013): 2297. http://dx.doi.org/10.1182/blood.v122.21.2297.2297.
Full textHu, S., Y. Li, J. Wang, Y. Xie, K. Tjon, L. Wolinsky, R. R. O. Loo, J. A. Loo, and D. T. Wong. "Human Saliva Proteome and Transcriptome." Journal of Dental Research 85, no. 12 (December 2006): 1129–33. http://dx.doi.org/10.1177/154405910608501212.
Full textAn, Xiuli, Vincent P. Schulz, Jie Li, Kunlu Wu, Jing Liu, Fumin Xue, Jingping Hu, Narla Mohandas, and Patrick G. Gallagher. "Global transcriptome analyses of human and murine terminal erythroid differentiation." Blood 123, no. 22 (May 29, 2014): 3466–77. http://dx.doi.org/10.1182/blood-2014-01-548305.
Full textStrausberg, R. L., and G. J. Riggins. "Navigating the human transcriptome." Proceedings of the National Academy of Sciences 98, no. 21 (October 9, 2001): 11837–38. http://dx.doi.org/10.1073/pnas.221463598.
Full textRusk, Nicole. "The human transient transcriptome." Nature Methods 13, no. 8 (July 28, 2016): 612. http://dx.doi.org/10.1038/nmeth.3952.
Full textĐerke, Filip, and Niko Njirić. "Human transcriptome - molecular neurobiology." Gyrus 3, no. 3 (September 2015): 148–51. http://dx.doi.org/10.17486/gyr.3.1031.
Full textGoh, Sung-Ho, Matthew Josleyn, Y. Terry Lee, Robert L. Danner, Robert B. Gherman, Maggie C. Cam, and Jeffery L. Miller. "The human reticulocyte transcriptome." Physiological Genomics 30, no. 2 (July 2007): 172–78. http://dx.doi.org/10.1152/physiolgenomics.00247.2006.
Full textMercer, Tim R., Shane Neph, Marcel E. Dinger, Joanna Crawford, Martin A. Smith, Anne-Marie J. Shearwood, Eric Haugen, et al. "The Human Mitochondrial Transcriptome." Cell 146, no. 4 (August 2011): 645–58. http://dx.doi.org/10.1016/j.cell.2011.06.051.
Full textCheng, Xuanjin, Junran Yan, Yongxing Liu, Jiahe Wang, and Stefan Taubert. "eVITTA: a web-based visualization and inference toolbox for transcriptome analysis." Nucleic Acids Research 49, W1 (May 21, 2021): W207—W215. http://dx.doi.org/10.1093/nar/gkab366.
Full textDissertations / Theses on the topic "HUMAN TRANSCRIPTOME"
Werne, Solnestam Beata. "Interpreting the human transcriptome." Doctoral thesis, KTH, Genteknologi, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-158320.
Full textMänniskokroppen är uppbyggd av miljarder celler och nästan alla innehåller samma arvsmassa. Trots detta finns det många olika celler med olika funktioner vilket är en följd av vilken del av arvsmassan som cellerna använder, dvs vilka RNA-molekyler som finns i varje cell. Den snabba utvecklingen av sekvenseringstekniker har gjort det möjligt att studera när, var och hur varje RNA-molekyl är uttryckt och att få en djupare förståelse för hur människans celler fungerar. Arbetet som presenteras i denna avhandling fokuserar på analys av RNA-molekyler i människans celler. I artikel I beskriver vi en automatiserad metod för att förbereda cellprov för RNA-sekvensering. Det automatiserade protokollet jämfördes med det manuella protokollet, och vi visade att det automatiserade protokollet överträffade det manuella när det gällde provkapacitet samtidigt som en höga reproducerbarheten behölls. I artikel II undersökte vi effekterna som RNA-molekyler från en del av cellen (cellkärnan) har på den totala mängden uttryckta RNA-molekyler. Vi jämförde RNA från hela cellen och från en del av cellen (cytoplasman) och visade att RNA-molekyler med långa och strukturerade 3'- och 5'-otranslaterade regioner och RNA-molekyler med långa proteinkodande sekvenser tenderade att hållas kvar i cellkärnan till en högre grad. Detta resulterade i en ökad komplexitet av RNA-molekylerna i hela cellen, medan vi i cytoplasma-fraktionen lättare kunde hitta de korta och svagt uttryckta RNA-molekyler. I Artikel III och IV studerar vi RNA-molekyler i människans skelettmuskler. I artikel III visar vi att andelen RNA-molekyler uttryckta i skelettmuskler är väldigt lika mellan muskler och mellan olika personer, men att ett stort antal RNA-molekyler var uttryckta i olika nivåer hos kvinnor och män. Artikel IV beskriver RNA-nivåer som svar på upprepade perioder av uthållighetsträning. Artikel V beskriver en metod för att studera ett fåtal utvalda RNA-molekyler. Vi valde RNA-molekyler vars uttryck är viktigt vid analys av bröstcancerceller, och optimerade metoden för analys av enskilda celler. Vi analyserade cancerceller från blodprov och använde metoden för att titta på RNA-nivåer i enskilda celler från en grupp av celler och visade på skillnader i RNA-nivåer inom gruppen.
QC 20150115
Natarajan, Sripriya 1978. "Defining the human endothelial transcriptome." Thesis, Massachusetts Institute of Technology, 2005. http://hdl.handle.net/1721.1/33082.
Full textIncludes bibliographical references (leaves 91-100).
Advances in microarray technology facilitate the study of biological systems at a genome-wide level. Meaningful analysis of these transcriptional profiling studies, however, demands the concomitant development of novel computational techniques that take into account the size and complexity of the data. We have devised statistical algorithms that use replicate microarrays to define a genome-wide expression profile of a given cell type and to determine a list of genes that are significantly differentially expressed between experimental conditions. Applying these algorithms to the study of cultured human umbilical vein endothelial cells (HUVEC), we have found approximately 54% of all genes to be expressed at a detectable level in HUVEC under basal conditions. The set of highest expressed genes is enriched in nucleic acid binding proteins, cytoskeletal proteins and isomerases as well as certain known markers of endothelium, and the complete list of genes can be found at ... We have also studied the effect of a 4-hour exposure of HUVEC to 10 U/mL of IL-1, and detected 491 upregulated and 259 downregulated statistically significant genes, including several chemokines and cytokines, as well as members of the TNFAIP3 family, the KLFfamily and the Notch pathway. Applying these rigorous statistical techniques to genome-wide expression datasets underscores known patterns of endothelial inflammatory gene regulation and unveils new pathways as well.
(cont.) Finally, we performed a direct comparison of direct-labeled microarrays with amplified RNA microarrays for an initial assessment of the effect of the additional noise of amplification on the outputs of the statistical algorithms. These techniques can be applied to additional genome-wide profiling studies of endothelium and other cell types to refine our understanding of transcriptomes and the gene regulatory network governing cellular function and pathophysiology.
by Sripriya Natarajan.
S.M.
Oldham, Michael Clark. "Transcriptome organization in human and chimpanzee brains." Diss., Restricted to subscribing institutions, 2009. http://proquest.umi.com/pqdweb?did=1872073991&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Full textWetterbom, Anna. "Genome and Transcriptome Comparisons between Human and Chimpanzee." Doctoral thesis, Uppsala universitet, Genomik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-112893.
Full textSymes, A. J. "Epithelial specific transcriptome map of the human prostate." Thesis, University College London (University of London), 2011. http://discovery.ucl.ac.uk/1302555/.
Full textCorral, Vázquez Celia. "Human sperm transcriptome: characterization, biological relevance, and biomarker functionality." Doctoral thesis, Universitat Autònoma de Barcelona, 2019. http://hdl.handle.net/10803/669365.
Full textThe biological relevance of sperm contribution to the embryo has been shown to go beyond a mere transmission of the paternal genome. Several findings revealed that human spermatozoa carry a complex population of coding and non-coding RNAs with potential implications in multiple fertility-related pathways. Accordingly, the consideration of these molecules as simple residual pools of earlier processes has been left behind. This new paradigm also opens the possibility for potential applications in the field of male fertility biomarkers. However, sperm transcriptomic analysis has several limitations due to the heterogeneity and delicate nature of these molecules, besides the small amount of RNA contained in spermatozoa. In this context, the objective of this Doctoral Thesis is to characterize the human sperm transcriptome to set up the basis for developing new biomarkers of male fertility. Within this goal, the following aims were undertaken: 1) To optimize specific methodologies of sperm RNA analysis using qRT-PCR and RNA-seq strategies; 2) To provide an integrative profiling and functional characterization of sperm mRNAs and lncRNAs by RNA-seq technologies; and 3) To establish new fertility biomarkers among the transcriptomic cargo of the human spermatozoa. For this purpose, the experimental protocols and data analysis were adapted to the inherent limitations of sperm RNA and to the used transcriptomic technology. Therefore, methods for the elimination of non-sperm cells from semen samples were implemented, together with strict quality controls for ensuring the absence of DNA and non-sperm RNA. Besides, an organic solvent-based method was used for qRT-PCR studies, and non-organic solvent kits were employed for RNA-seq. The obtained data were normalized by specific methods depending on the used technique. In particular, the normalization of sperm miRNA qRT-PCR singleplex studies required the determination of a suitable set of normalizing miRNAs molecules. This was achieved by comparing the results derived from a sperm miRNA expression dataset normalized by: i) the reference Mean Centering Restricted (MCR) method; and ii) the expression level of different miRNAs. The miRNAs hsa-miR-100-5p and hsa-miR-30a-5p showed ubiquitous and stable expressions, and data normalized by their mean expression led to results with an appropriate quality when compared to MCR. Therefore, this miRNA combination was suggested as the most suitable choice for data normalization in further sperm singleplex studies. RNA-seq analysis was used to characterize the sperm transcriptome cargo of fertile individuals. Results revealed a complex network of mRNAs and lncRNAs with a high fragmentation status, but containing a host of ubiquitous transcripts. Gene ontology analyses of the whole set of expressed mRNAs showed an enrichment of spermatogenesis and reproduction processes, which was more significant in the sets of highly expressed, ubiquitous, and highly stable mRNAs. Additionally, the functional profiling of potential cis-target genes of the observed lncRNAs showed a significant involvement in embryo development and cell adhesion. This implication became more evident in those cis-target genes that were not present among the sperm mRNA cargo. Finally, the detection of ubiquitous transcripts and pairs of RNAs with correlated expressions suggested a potential use of these molecules as fertility biomarkers. Accordingly, the presence of sperm miRNA pairs with a correlated expression in fertile individuals that was disrupted in infertile patients of different ethiologies (asthenozoospermia, teratozoospermia, oligozoospermia, and Unexplained Male Infertility or UMI) was evaluated and validated by qRT-PCR. The hsa-miR-942-5p/hsa-miR-1208 pair allowed correctly classifying the 85.71% of infertile individuals, thus achieving the highest potential for discerning infertility cases with seminal alterations. Additionally, the pair hsa-miR-34b-3p/hsa-miR-93-3p was highlighted due to its high potential for discerning UMI patients. Besides, several pairs of ubiquitous lncRNAs and mRNAs were also observed to display a correlated expression in fertile individuals, becoming potential candidates for further biomarker studies.
Khuder, Basil. "Human Genome and Transcriptome Analysis with Next-Generation Sequencing." University of Toledo Health Science Campus / OhioLINK, 2017. http://rave.ohiolink.edu/etdc/view?acc_num=mco1501886695490104.
Full textChen, Jenny (Jennifer). "Evolutionary signatures for unearthing functional elements in the human transcriptome." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/117792.
Full textThis electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.
Cataloged student-submitted from PDF version of thesis.
Includes bibliographical references (pages 141-156).
Comparative genomics is a powerful method for identifying functional genetic elements by their evolutionary patterns across species. However, current studies largely focus on analysis of genome sequences. The recent development of RNA-sequencing reveals dimensions of regulatory information previously inaccessible to us by sequence alone. The comparison of RNA-sequencing data across mammals has great potential for addressing two open problems in biology: identifying the regulatory mechanisms crucial to mammalian physiology, and deciphering how gene regulation contributes to the diversity of mammalian phenotypes. For my thesis, I developed two methodologies for interrogating comparative transcriptomic data for biological inference. First, I developed a framework for quantifying the evolutionary forces acting on gene expression and inferring evolutionarily optimal expression levels. I demonstrate how to use this framework to identify expression pathways underlying conserved, adaptive, and disease states of mammalian biology. Second, I developed novel metrics of transcriptional evolution to evaluate the conservation of long noncoding RNAs. These metrics further reveal that long noncoding RNAs harbor distinct evolutionary signatures, suggesting that they are not a homogenous class of molecules but rather a mixture of multiple functional classes with distinct biological roles. My thesis work provides fundamental quantitative tools for asking biological questions about transcriptome evolution. These tools provide a pivotal framework for interpreting transcriptional data across species and pave the way for deciphering the regulatory changes that lead to mammalian phenotypic variation.
by Jenny Chen.
Ph. D. in Bioinformatics and Integrative Genomics
Xu, Guorong. "Computational Pipeline for Human Transcriptome Quantification Using RNA-seq Data." ScholarWorks@UNO, 2011. http://scholarworks.uno.edu/td/343.
Full textSherwood, Karen. "Preparation, characterisation and transcriptome analysis of RNA from human vCJD brains." Thesis, University of Edinburgh, 2008. http://hdl.handle.net/1842/4226.
Full textBooks on the topic "HUMAN TRANSCRIPTOME"
Einson, Jonah. Common and rare genetic effects on the transcriptome and their contribution to human traits. [New York, N.Y.?]: [publisher not identified], 2022.
Find full textLeGrice, Stuart, and Matthias Gotte, eds. Human Immunodeficiency Virus Reverse Transcriptase. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-7291-9.
Full textGenome transcriptome and proteome analysis. Chichester: Wiley, 2004.
Find full textBernot, Alain. Genome Transcriptome and Proteome Analysis. New York: John Wiley & Sons, Ltd., 2005.
Find full textHo, Charmaine. Development of human immunodeficiency virus type-1 reverse transcriptase activity assays. Ottawa: National Library of Canada, 1993.
Find full textSchadt, Eric E. Network Methods for Elucidating the Complexity of Common Human Diseases. Edited by Dennis S. Charney, Eric J. Nestler, Pamela Sklar, and Joseph D. Buxbaum. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190681425.003.0002.
Full textBittner, Edward A., and Shawn P. Fagan. The host response to trauma and burns in the critically ill. Oxford University Press, 2016. http://dx.doi.org/10.1093/med/9780199600830.003.0304.
Full textGotte, Matthias, and Stuart LeGrice. Human Immunodeficiency Virus Reverse Transcriptase. Springer, 2015.
Find full textGotte, Matthias, and Stuart LeGrice. Human Immunodeficiency Virus Reverse Transcriptase. Springer, 2013.
Find full textGotte, Matthias, and Stuart LeGrice. Human Immunodeficiency Virus Reverse Transcriptase. Springer London, Limited, 2013.
Find full textBook chapters on the topic "HUMAN TRANSCRIPTOME"
Peres, Nalu T. A., Gabriela F. Persinoti, Elza A. S. Lang, Antonio Rossi, and Nilce M. Martinez-Rossi. "Transcriptome in Human Mycoses." In Transcriptomics in Health and Disease, 227–63. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11985-4_13.
Full textPeres, Nalu T. A., Tamires A. Bitencourt, Gabriela F. Persinoti, Elza A. S. Lang, Antonio Rossi, and Nilce M. Martinez-Rossi. "Transcriptome in Human Mycoses." In Transcriptomics in Health and Disease, 395–435. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-87821-4_17.
Full textMoreira-Filho, Carlos Alberto, Silvia Yumi Bando, Fernanda Bernardi Bertonha, and Magda Carneiro-Sampaio. "Functional Genomics of the Infant Human Thymus: AIRE and Minipuberty." In Thymus Transcriptome and Cell Biology, 235–45. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-12040-5_10.
Full textOkubo, Kousaku, and Teruyoshi Hishiki. "Knowledge Discovery from the Human Transcriptome." In Introduction to Bioinformatics, 693–710. Totowa, NJ: Humana Press, 2003. http://dx.doi.org/10.1007/978-1-59259-335-4_36.
Full textMarinotti, Osvaldo, and Anthony A. James. "The Transcriptome of Human Malaria Vectors." In Molecular Approaches to Malaria, 516–30. Washington, DC, USA: ASM Press, 2014. http://dx.doi.org/10.1128/9781555817558.ch27.
Full textRusso, Jose, and Irma H. Russo. "Methodological Approach for Studying the Human Breast." In Role of the Transcriptome in Breast Cancer Prevention, 243–68. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-4884-6_5.
Full textRusso, Jose, and Irma H. Russo. "The Role of Spliceosome in the Human Breast." In Role of the Transcriptome in Breast Cancer Prevention, 337–90. Boston, MA: Springer US, 2012. http://dx.doi.org/10.1007/978-1-4614-4884-6_8.
Full textOsada, Naoki. "An Overview of Transcriptome Studies in Non-Human Primates." In Post-Genome Biology of Primates, 9–22. Tokyo: Springer Tokyo, 2011. http://dx.doi.org/10.1007/978-4-431-54011-3_2.
Full textBombonato-Prado, Karina F., Adalberto L. Rosa, Paulo T. Oliveira, Janaína A. Dernowsek, Vanessa Fontana, Adriane F. Evangelista, and Geraldo A. Passos. "Transcriptome Analysis During Normal Human Mesenchymal Stem Cell Differentiation." In Transcriptomics in Health and Disease, 109–19. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11985-4_6.
Full textOuedraogo, Wend Yam Donald Davy, and Aida Ouangraoua. "Inferring Clusters of Orthologous and Paralogous Transcripts." In Comparative Genomics, 19–34. Cham: Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-36911-7_2.
Full textConference papers on the topic "HUMAN TRANSCRIPTOME"
Combs, Joseph, Tracy Mandichak, Elizabeth Ferree, and Aaron E. Hoffman. "Abstract 1798: The human mammary circadian transcriptome." In Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC. American Association for Cancer Research, 2013. http://dx.doi.org/10.1158/1538-7445.am2013-1798.
Full textWalters, Matthew S., Neil R. Hackett, Renat Shaykhiev, Rui Wang, Rachel K. Zwick, Jacqueline Salit, and Ronald G. Crystal. "The Human Airway Epithelial Basal Cell Transcriptome." In American Thoracic Society 2011 International Conference, May 13-18, 2011 • Denver Colorado. American Thoracic Society, 2011. http://dx.doi.org/10.1164/ajrccm-conference.2011.183.1_meetingabstracts.a6019.
Full textXu, Xiaoxiao, Arye Nehorai, and Joseph Dougherty. "Cell type specific analysis of human transcriptome data." In 2012 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2012. http://dx.doi.org/10.1109/gensips.2012.6507737.
Full textSchamberger, Andrea, Fien Verhamme, Michael Lindner, Jürgen Behr, and Oliver Eickelberg. "Transcriptome analysis of the human airway epithelium duringin vitrodifferentiation." In ERS International Congress 2016 abstracts. European Respiratory Society, 2016. http://dx.doi.org/10.1183/13993003.congress-2016.pa3993.
Full textGalatro, Thais Fernanda, Antonio M. Lerario, Sueli M. Oba-Shinjo, Bart J. Eggen, and Suely K. Marie. "Abstract 2958: Transcriptome analysis of astrocytomaversusnon-neoplastic human microglia." In Proceedings: AACR Annual Meeting 2017; April 1-5, 2017; Washington, DC. American Association for Cancer Research, 2017. http://dx.doi.org/10.1158/1538-7445.am2017-2958.
Full text"Transcriptome of failing human heart reveals atrial myocytes reprogramming." In Bioinformatics of Genome Regulation and Structure/Systems Biology (BGRS/SB-2022) :. Institute of Cytology and Genetics, the Siberian Branch of the Russian Academy of Sciences, 2022. http://dx.doi.org/10.18699/sbb-2022-450.
Full textDeng, Nan, and Dongxiao Zhu. "RNA-Seq analyses to reveal the human transcriptome landscape." In BCB'13: ACM-BCB2013. New York, NY, USA: ACM, 2013. http://dx.doi.org/10.1145/2506583.2506603.
Full textStaudt, Michelle R., Jennifer A. Fuller, Rui Wang, Rachel K. Zwick, Jacqueline Salit, Neil R. Hackett, and Ronald G. Crystal. "Whole Transcriptome Analysis Of Human Airway Epithelial Basal Cells." In American Thoracic Society 2010 International Conference, May 14-19, 2010 • New Orleans. American Thoracic Society, 2010. http://dx.doi.org/10.1164/ajrccm-conference.2010.181.1_meetingabstracts.a6402.
Full textNarozna, Beata, Wojciech Langwiński, Zuzanna Stachowiak, Ewelina Bukowska-Olech, and Aleksandra Szczepankiewicz. "Changes in human airway cells transcriptome during epithelial wound repair." In ERS International Congress 2021 abstracts. European Respiratory Society, 2021. http://dx.doi.org/10.1183/13993003.congress-2021.pa3685.
Full textSchreiter, Thomas, RobertK Gieseler, Ramiro Vílchez-Vargas, Ruy Jauregui, Jan-Peter Sowa, Susanne Klein-Scory, Ruth Broering, et al. "Age-related analysis of transcriptome-wide sequencing of human liver." In 38. Jahrestagung der Deutsche Arbeitsgemeinschaft zum Studium der Leber. Georg Thieme Verlag, 2022. http://dx.doi.org/10.1055/s-0041-1740685.
Full textReports on the topic "HUMAN TRANSCRIPTOME"
Libray, Spring. The Booming Field of Epitranscriptomics and its Role in Human Disease. Spring Library, April 2021. http://dx.doi.org/10.47496/sl.blog.26.
Full textMiller, Gad, and Jeffrey F. Harper. Pollen fertility and the role of ROS and Ca signaling in heat stress tolerance. United States Department of Agriculture, January 2013. http://dx.doi.org/10.32747/2013.7598150.bard.
Full textLers, Amnon, Majid R. Foolad, and Haya Friedman. genetic basis for postharvest chilling tolerance in tomato fruit. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7600014.bard.
Full textFridman, Eyal, and Eran Pichersky. Tomato Natural Insecticides: Elucidation of the Complex Pathway of Methylketone Biosynthesis. United States Department of Agriculture, December 2009. http://dx.doi.org/10.32747/2009.7696543.bard.
Full text