Littérature scientifique sur le sujet « Transcriptomic analysi »
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Articles de revues sur le sujet "Transcriptomic analysi"
Ochsner, Scott A., Christopher M. Watkins, Apollo McOwiti, Xueping Xu, Yolanda F. Darlington, Michael D. Dehart, Austin J. Cooney, David L. Steffen, Lauren B. Becnel et Neil J. McKenna. « Transcriptomine, a web resource for nuclear receptor signaling transcriptomes ». Physiological Genomics 44, no 17 (1 septembre 2012) : 853–63. http://dx.doi.org/10.1152/physiolgenomics.00033.2012.
Texte intégralCallaway, Edward M., Hong-Wei Dong, Joseph R. Ecker, Michael J. Hawrylycz, Z. Josh Huang, Ed S. Lein, John Ngai et al. « A multimodal cell census and atlas of the mammalian primary motor cortex ». Nature 598, no 7879 (6 octobre 2021) : 86–102. http://dx.doi.org/10.1038/s41586-021-03950-0.
Texte intégralNesterenko, Maksim, et Aleksei Miroliubov. « From head to rootlet : comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea : Rhizocephala) ». F1000Research 11 (27 mai 2022) : 583. http://dx.doi.org/10.12688/f1000research.110492.1.
Texte intégralNesterenko, Maksim, et Aleksei Miroliubov. « From head to rootlet : comparative transcriptomic analysis of a rhizocephalan barnacle Peltogaster reticulata (Crustacea : Rhizocephala) ». F1000Research 11 (9 janvier 2023) : 583. http://dx.doi.org/10.12688/f1000research.110492.2.
Texte intégralChen, Wanze, Orane Guillaume-Gentil, Pernille Yde Rainer, Christoph G. Gäbelein, Wouter Saelens, Vincent Gardeux, Amanda Klaeger et al. « Live-seq enables temporal transcriptomic recording of single cells ». Nature 608, no 7924 (17 août 2022) : 733–40. http://dx.doi.org/10.1038/s41586-022-05046-9.
Texte intégralGui, Yu, Xiujing He, Jing Yu et Jing Jing. « Artificial Intelligence-Assisted Transcriptomic Analysis to Advance Cancer Immunotherapy ». Journal of Clinical Medicine 12, no 4 (6 février 2023) : 1279. http://dx.doi.org/10.3390/jcm12041279.
Texte intégralCheon, Seongmin, Sung-Gwon Lee, Hyun-Hee Hong, Hyun-Gwan Lee, Kwang Young Kim et Chungoo Park. « A guide to phylotranscriptomic analysis for phycologists ». Algae 36, no 4 (15 décembre 2021) : 333–40. http://dx.doi.org/10.4490/algae.2021.36.12.7.
Texte intégralChaudhuri, Roy R., Lu Yu, Alpa Kanji, Timothy T. Perkins, Paul P. Gardner, Jyoti Choudhary, Duncan J. Maskell et Andrew J. Grant. « Quantitative RNA-seq analysis of the Campylobacter jejuni transcriptome ». Microbiology 157, no 10 (1 octobre 2011) : 2922–32. http://dx.doi.org/10.1099/mic.0.050278-0.
Texte intégralOrtiz, Randy, Priyanka Gera, Christopher Rivera et Juan C. Santos. « Pincho : A Modular Approach to High Quality De Novo Transcriptomics ». Genes 12, no 7 (22 juin 2021) : 953. http://dx.doi.org/10.3390/genes12070953.
Texte intégralMacrander, Jason, Jyothirmayi Panda, Daniel Janies, Marymegan Daly et Adam M. Reitzel. « Venomix : a simple bioinformatic pipeline for identifying and characterizing toxin gene candidates from transcriptomic data ». PeerJ 6 (31 juillet 2018) : e5361. http://dx.doi.org/10.7717/peerj.5361.
Texte intégralThèses sur le sujet "Transcriptomic analysi"
Jousset, Agnès. « analyse génomique et transcriptomique de bactéries productrices de carbapénèmases ». Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS527.
Texte intégralMultidrug resistant bacteria and in particular carbapenemase-producing Enterobacteriaceae remain a major health public challenge. Some successful clones are emerging globally, due to their high transmissibility and their ability to colonize and persist in patients over time. Genomic analyses revealed that the dissemination of KPC carbapenemase is closely related to the spread of Klebsiella pneumoniae of the sequence-type (ST) 258 and to few successful plasmids linked to IncFIIk family. However, the reasons of the association between K. pneumoniae ST258, IncFIIk plasmids and KPC that led to the rapid spread of this clone are currently unknown.Furthermore, there is no correlation between expression level of a carbapenemase-encoding gene, in vitro susceptibility to carbapenems and efficiency of a carbapenem-based treatment. Most of the time, KPC-producing K. pneumoniae exhibit a heteroresistant phenotype with carbapenems, but its clinical impact remains unknown. The mechanisms underlying the regulation of carbapenemases expression remain to be explored.The objectives of the thesis are to obtain deeper insights into genomic plasticity of carbapenemase–producing clones, and into the expression of their β-lactamases.The first part of this work was dedicated to the in vivo evolution of a single strain of KPC-producing K. pneumoniae ST258 that colonized a patient for almost 5 years. Genomic comparison of 17 isolates revealed a remarkable diversification with occurrence of several mutations with impact on bacterial virulence and susceptibility to antibiotics.Several studies extensively described the genetic structures of blaKPC-carrying plasmids, but information regarding gene expression at the whole plasmid level are lacking. Accordingly, we performed RNA-seq on Escherichia coli TOP10 transformed with an IncFIIk-IncFI blaKPC-2-carrying plasmid, with or without imipenem exposure. In both conditions, plasmid-encoded genes related to antimicrobial resistance and involved in plasmid replication were the most expressed. Imipenem exposure led to a more general response with overexpression of E. coli numerous chromosome-encoded genes involved in oxidative stress response. In addition, analysis of blaKPC-2 gene expression in several species using 5’RACE revealed the presence of several promoters whose strength depends on the bacterial genetic background. This could promote higher expression of blaKPC-2 gene and explain the association of some isoforms of Tn4401 in different species. The tools developed in the frame of this work were also applied to study a single Enterobacter kobei ST125 clone whose natural cephalosporinase (ACT-28) has increased hydrolytic activity towards imipenem. Finally, genomic analysis of the first ESBL-producing Shewanella sp. was performed. It revealed the presence of blaCTX-M-15 and blaSHV-2 genes carried on an IncA/C plasmid and a new chromosomally-encoded oxacillinase variant of OXA-48 with carbapenemase activity, called OXA-535. OXA-535 was found to be closely related to OXA-436, another carbapenemase which has recently spread in Enterobacteriaceae. Analysis of the genetic environment of both blaOXA-48-like genes confirmed the role of Shewanella spp. as progenitors of class D carbapenemases.Overall, this work contributes to a better comprehension of the diffusion of multi-drug resistant clones and of the mechanisms implicated in β-lactamase expression
Rodó, Morera Jordi. « Transcriptomic analysis of white and brown adipose tissue during non-shivering thermogenesis ». Doctoral thesis, Universitat Autònoma de Barcelona, 2019. http://hdl.handle.net/10803/667915.
Texte intégralObesity and type 2 diabetes (T2D) are two closely related diseases that represent a serious health, social and economic problem due to their high prevalence worldwide. Both diseases are also associated with other pathologies that present high mortality. The currently available therapies are not entirely effective. Thus, the development of new therapeutic strategies for obesity and T2D is crucial. Adipose tissue has been defined as an organ that plays a central role in the control of energy balance. The proved endocrine and thermogenic functions of adipocytes has renewed interest in the study of this tissue. Non-shivering thermogenesis has been described as occurring in brown adipose tissue of mice, but under certain stimuli, such as prolonged cold exposure, brown fat-like cells (beige adipocytes), appear in some white adipose tissue depots of rodents and humans. The activation of non-shivering thermogenesis in humans through cold-exposure increases resting energy expenditure, whole-body glucose disposal, insulin sensitivity, and ameliorates glucose metabolism independently of BMI. However, more gene expression studies to gain insight into the molecular mechanisms underlying the cold-induced enhancement of non-shivering thermogenesis, as well as to determine differences between BAT activation and browning of WAT, are needed. In this study, the transcriptomic response of epididymal and inguinal white adipose depots (eWAT and iWAT, respectively) as well as that of the interscapular brown adipose depot (iBAT) of mice either exposed to 22ºC or 4ºC for the period of 4 days were examined. Cold exposure increased the metabolic and thermogenic activity of iWAT. In this depot, genes related to glycolysis, tricarboxylic acid cycle, lipolysis, and the degradation of some amino acids presented a high upregulation to maintain the protonmotive power to generate heat. Moreover, the expression of thermogenic-related genes was also highly increased, demonstrating a cold-induced browning of iWAT. The eWAT depot has been reported to be resilient to browning. Thus, the observed metabolic activation of this depot was mild in comparison with that of iWAT, and no relevant enhancement of non-shivering thermogenesis was observed in this depot. Finally, iBAT already presented high expression levels of thermogenic genes because mice were not housed at thermoneutrality. The observation that genes related to thermogenesis and metabolism presented a similar expression pattern among samples endorsed the utilization of pattern matching analysis tools to unravel Atp4b and 1700040L02Rik as novel genes potentially involved in thermogenesis. The overexpression of Atp4b and 1700040L02Rik in adipose tissue by means of AAV vectors produced a body weight gain reduction, decreased eWAT, and liver weight, amelioration of white adipocytes hypertrophy, and reduced hepatic steatosis potentially as a result of the detected enhanced thermogenesis in iWAT. Overall, these results indicate a new potential anti-obesogenic role for these genes. The results from this thesis contributed to a better understanding of the induction of non-shivering thermogenesis in adipose tissue depots in mice. Among the different adipose depots, exploratory data analysis of the gene expression levels of mice exposed from 22ºC to 4ºC determined that iWAT was the depot that responded most significantly to cold exposure. Moreover, as observed in the pathway enrichment and gene ontology analysis, this response was highly coordinated, presenting a high number of genes related to metabolic pathways highly affected. The detailed study of the metabolic pathways led to the detection of a high induction of non-shivering thermogenesis, revealing that both energy production and energy consumption mechanisms were highly synchronized. This in detail study of the adipose tissue also allowed the identification of novel genes potentially involved in non-shivering thermogenesis.
Stranneheim, Henrik. « Enabling massive genomic and transcriptomic analysis ». Doctoral thesis, KTH, Genteknologi, 2011. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-45957.
Texte intégralQC 20111115
Braga, D. « TRANSCRIPTOMIC ANALYSIS IN SEPTIC SHOCK PATIENTS ». Doctoral thesis, Università degli Studi di Milano, 2017. http://hdl.handle.net/2434/473670.
Texte intégralLoe-mie, Yann. « Contribution bioinformatique à l' analyse du transcriptome humain ». Thesis, Aix-Marseille, 2012. http://www.theses.fr/2012AIXM4002/document.
Texte intégralIn first part of this thesis I have analysed small RNA-seq transcriptome data. I have noticed : - a large fraction of reads can't be aligned perfectly on reference genome - lot of reads are very short (15-18 nt) and don't match on previously known functionnal small RNAs. These experiments are designed for miRNA discovery and bioinformatics analysis of these data use alignments on genome or on known small RNA precursors sequences. I have eliminated the alignment and I have clustered these sequences. This clustering let me to observe these data with a new view in wich the genomic location is not central and open the gate to discover unconventional events. The second part is the analysis of deregulate genes by the silencing of the gene REST/NRSF in mouse N18 cell line. This gene is a transcription factor and it works as a repressor of neuronal genes in non neuronal cells. This deregulate genes repertoire potentially contains key genes in neuron biology. We found in this repertoire a network of genes centered on SWI/SNF complex including SMARCA2. This gene was associated to schizophrenia (SZ) in association studies and structural variation studies. In this network we found another genes associated to SZ. We show that these genes exhibit positive evolution in primate compare to rodents
Sidaway, Adam. « Transcriptomics analysis of differentiating erythroblasts ». Thesis, University of Bristol, 2016. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.715794.
Texte intégralBadawi, Sally. « Characterization of dynamic molecular networks in control ischemic-reperfused mouse heart ». Thesis, Lyon, 2019. http://www.theses.fr/2019LYSE1158.
Texte intégralCardiovascular diseases represent a major health burden worldwide. According to the World Health Organization, 17 million people are dying each year by heart diseases which account to 31% of total deaths globally. Among these diseases is myocardial infarction (MI). Several efforts have been made to decrease the associated mortality rates but unfortunately, only few has succeeded to date. This failure is contributed to several factors, among them is the misunderstanding of the mechanism responsible for the progression of the disease.Our understanding of the MI pathology has been greatly improved by the approaches that have been widely used in the previous decades, relying mainly on studying molecules/pathways separately. However, this knowledge was not enough to make a difference clinically. Therefore, deciphering the interconnections between molecules has become an urge for better understanding of the diseases’ progression. In this regard, the work in this doctoral thesis involves different aspects of the MI pathology. The general aim of this work is to improve the dynamic analytical approach using systems biology tools, where new mechanistic information is decoded. Firstly, in a 3D heart model, we propose a chain of methods using clarified mouse heart and fluorescence microscopy to molecularly characterize the area at risk in the myocardium of IR and cardioprotected mice based on its redox state. In addition, we aim to develop a new analytical approach using dynamical large-scale transcriptomic data for characterizing the dynamic transcripts expression. Applying this approach on a control mouse model (mice subjected to anesthesia and surgical interventions), we show that Il-6 is a major mediator of the activated inflammatory reaction. In conclusion, this analytical approach highlights the necessity of the sapatio-temporal analysis to characterize the molecular events occurring in response to MI
Schwalb, Björn. « Dynamic transcriptome analysis (DTA) ». Diss., lmu, 2012. http://nbn-resolving.de/urn:nbn:de:bvb:19-147748.
Texte intégralBERTOLAZZI, Giorgio. « MicroRNA Interaction Networks ». Doctoral thesis, Università degli Studi di Palermo, 2021. http://hdl.handle.net/10447/498927.
Texte intégralBertolazzi’s thesis focuses on developing and applying computational methods to predict microRNA binding sites located on messenger RNA molecules. MicroRNAs (miRNAs) regulate gene expression by binding target messenger RNA molecules (mRNAs). Therefore, the prediction of miRNA binding is important to investigate cellular processes. Moreover, alterations in miRNA activity have been associated with many human diseases, such as cancer. The thesis explores miRNA binding behavior and highlights fundamental information for miRNA target prediction. In particular, a machine learning approach is used to upgrade an existing target prediction algorithm named ComiR; the original version of ComiR considers miRNA binding sites located on mRNA 3’UTR region. The novel algorithm significantly improves the ComiR prediction capacity by including miRNA binding sites located on mRNA coding regions.
Crivelente, Horta Maria Augusta 1981. « Análise do transcriptoma de Trichoderma harzianum para a bioprospecção de enzimas hidrolíticas = Analysis of Trichoderma harzianum transcriptome for bioprospecting of hydrolytic enzymes ». [s.n.], 2014. http://repositorio.unicamp.br/jspui/handle/REPOSIP/316510.
Texte intégralTese (doutorado) - Universidade Estadual de Campinas, Instituto de Biologia
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Resumo: Buscando contribuir com o desenvolvimento da tecnologia de produção do etanol de segunda geração, o presente estudo analisa o transcriptoma de T. harzianum IOC-3844 utilizando técnicas de sequenciamento high-thoughput. O principal objetivo dessas análises foi identificar, caracterizar e catalogar os transcritos expressos por T. harzianum relacionados com a degradação de substratos complexos, como o bagaço de cana de açúcar, revelando o conjunto de genes envolvidos na degradação da biomassa. A análise do transcriptoma do fungo Trichoderma harzianum sob condições que induzem a degradação da biomassa permitiu a identificação de sequências de genes potencialmente eficazes no processo de biodegradação, uma etapa essencial à compreensão do processo de hidrólise enzimática. O sequenciamento resultou em 246 milhões de sequências com 72 pb, o que corresponde a 14,7 GPB analisados. Após a montagem , 32.494 contigs foram gerados, submetidos à identificação e classificados de acordo com sua identidade. Todas as sequências de contigs foram comparados com o banco de dados do NCBI, Gene Ontology (GO terms), Enciclopédia de Genes Kyoto (KEGG), Carbohydrate Active-Enzymes (CAZYmes). Foram identificados 487 CAZymes no transcriptoma, inclusive aquelas ligadas as reações químicas de despolimerização de celulose e hemicelulose. As sequências classificadas como atividade catalítica (6.975) e atividade reguladora (143) podem estar envolvidas com esse tipo de reação.A análise permitiu definir o principal conjunto de genes envolvidos na degradação da celulose e de hemicelulose do T. harzianum , e genes acessórios relativos à despolimerização de biomassa. Uma análise dos níveis de expressão permitiu determinar os conjuntos de genes diferencialmente expressos em diferentes condições de cultivo. Os resultados obtidos acrescentam conhecimento sobre a constituição do genoma, as atividades de expressão gênica do fungo Trichoderma harzianum e fornece informações importantes a respeito dos mecanismos genéticos de degradação de biomassa que o fungo utiliza. As informações obtidas poderão ser utilizadas para outras espécies de fungos filamentosos com potencial para a biodegradação
Abstract: In order to contribute to the development of second-generation ethanol technology, this study analyzes the transcriptome of T. harzianum IOC-3844 using high-thoughput sequencing techniques. The main objective of this analysis was to identify, characterize and catalog the transcripts expressed by T. harzianum related to the degradation of complex substrates such as sugar cane bagasse, revealing the set of genes involved in the degradation of biomass. The analysis of the transcriptome of the fungus Trichoderma harzianum under conditions that induce the degradation of biomass allowed the identification of genes potentially effective in the biodegradation process, an essential step for understanding the enzymatic process. Sequencing resulted in 246 million sequences with 72 bp, which corresponds to 14.7 GBP analyzed. After assembly, 32,494 contigs were generated, identified and classified according to their identity. All sequence contigs were compared with NCBI database, Gene Ontology (GO terms), Kyoto Encyclopedia of Genes (KEGG), Carbohydrate Active-Enzymes (CAZYmes). 487 CAZymes were identified in the transcriptome, including those related to reactions of cellulose and hemicellulose depolymerization. Sequences classified as catalytic activity (6,975) and regulatory activity (143) may be involved with this type of reaction. This analysis define the set of genes involved in the degradation of cellulose and hemicellulose of T. harzianum, and accessories genes related to depolymerization of the biomass. An analysis of expression levels was used to calculate the set of differentially expressed genes in different culture conditions. The results add to knowledge about the composition of the genome and gene expression activity of the fungus Trichoderma harzianum, and provides important information regarding the genetic mechanisms of biomass degradation that the fungus uses. The information obtained may be used for other species of filamentous fungi with potential for biodegradation
Doutorado
Genetica Vegetal e Melhoramento
Doutora em Genética e Biologia Molecular
Livres sur le sujet "Transcriptomic analysi"
Cellerino, Alessandro, et Michele Sanguanini. Transcriptome Analysis. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1.
Texte intégralWang, Yejun, et Ming-an Sun, dir. Transcriptome Data Analysis. New York, NY : Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4939-7710-9.
Texte intégralGenome transcriptome and proteome analysis. Chichester : Wiley, 2004.
Trouver le texte intégralBernot, Alain. Genome Transcriptome and Proteome Analysis. New York : John Wiley & Sons, Ltd., 2005.
Trouver le texte intégralKrizay, Daniel Kyle. Transcriptomic and Functional Analysis of Neuronal Activity and Disease. [New York, N.Y.?] : [publisher not identified], 2022.
Trouver le texte intégralLee, Albert Kim. Characterizing Immune Responses to Marburg Virus Infection in Animal Hosts Using Statistical Transcriptomic Analysis. [New York, N.Y.?] : [publisher not identified], 2018.
Trouver le texte intégralScanfeld, Daniel. Exploring the Plasmodium falciparum Transcriptome Using Hypergeometric Analysis of Time Series (HATS). [New York, N.Y.?] : [publisher not identified], 2013.
Trouver le texte intégralauthor, Tuimala Jarno, Somervuo Panu author, Huss Mikael author et Wong Garry author, dir. RNA-seq data analysis : A practical approach. Boca Raton : CRC Press, Taylor & Francis Group, 2015.
Trouver le texte intégralBlumenberg, Miroslav, dir. Transcriptome Analysis. IntechOpen, 2019. http://dx.doi.org/10.5772/intechopen.77860.
Texte intégralTranscriptome Analysis. IntechOpen, 2019.
Trouver le texte intégralChapitres de livres sur le sujet "Transcriptomic analysi"
Cellerino, Alessandro, et Michele Sanguanini. « A primer on data distributions and their visualisation ». Dans Transcriptome Analysis, 1–10. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_1.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Next-generation RNA sequencing ». Dans Transcriptome Analysis, 11–25. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_2.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « RNA-seq raw data processing ». Dans Transcriptome Analysis, 27–44. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_3.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Differentially expressed gene detection and analysis ». Dans Transcriptome Analysis, 45–58. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_4.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Unbiased clustering methods ». Dans Transcriptome Analysis, 59–83. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_5.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Knowledge-based clustering methods ». Dans Transcriptome Analysis, 85–98. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_6.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Network analysis ». Dans Transcriptome Analysis, 99–119. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_7.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Mesoscale transcriptome analysis ». Dans Transcriptome Analysis, 121–39. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_8.
Texte intégralCellerino, Alessandro, et Michele Sanguanini. « Microscale transcriptome analysis ». Dans Transcriptome Analysis, 141–68. Pisa : Scuola Normale Superiore, 2018. http://dx.doi.org/10.1007/978-88-7642-642-1_9.
Texte intégralYonekura-Sakakibara, Keiko, et Kazuki Saito. « Transcriptome Coexpression Analysis Using ATTED-II for Integrated Transcriptomic/Metabolomic Analysis ». Dans Methods in Molecular Biology, 317–26. Totowa, NJ : Humana Press, 2013. http://dx.doi.org/10.1007/978-1-62703-414-2_25.
Texte intégralActes de conférences sur le sujet "Transcriptomic analysi"
Collar, Giovanna Carello, Marco Antônio De Bastiani et Eduardo R. Zimmer. « HUNTINGTON’S DISEASE AND EARLYONSET ALZHEIMER’S DISEASE SHARE A TRANSCRIPTOMIC SIGNATURE ». Dans XIII Meeting of Researchers on Alzheimer's Disease and Related Disorders. Zeppelini Editorial e Comunicação, 2021. http://dx.doi.org/10.5327/1980-5764.rpda082.
Texte intégralKusakin, P. G., T. A. Serova, N. E. Gogoleva, Yu V. Gogolev et V. E. Tsyganov. « Transcriptome analysis of pea (Pisum sativum L.) symbiotic nodules using laser capture microdissection ». Dans 2nd International Scientific Conference "Plants and Microbes : the Future of Biotechnology". PLAMIC2020 Organizing committee, 2020. http://dx.doi.org/10.28983/plamic2020.146.
Texte intégralOlsen, E., L. Perez, B. Franca, Y. Li, R. Schluger, I. Sulaiman, J. Carpenito, B. Wu, L. N. Segal et J. J. Tsay. « Transcriptomic Analysis of Lower Airway Dysbiosis ». Dans American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a5410.
Texte intégralVetchinkina, E. P., V. Yu Gorshkov, N. E. Gogoleva, Yu V. Gogolev et V. E. Nikitina. « Comparative analysis of transcriptomes of different morphological structures of the basidiomycete Lentinus edodes ». Dans 2nd International Scientific Conference "Plants and Microbes : the Future of Biotechnology". PLAMIC2020 Organizing committee, 2020. http://dx.doi.org/10.28983/plamic2020.270.
Texte intégralPavlenko, O. S., N. S. Sadovskaya, O. N. Mustafayev, Yu V. Akashkina et I. V. Goldenkova-Pavlova. « Transcriptome analysis of Euonymus europaeus fruits at different stages of development ». Dans 2nd International Scientific Conference "Plants and Microbes : the Future of Biotechnology". PLAMIC2020 Organizing committee, 2020. http://dx.doi.org/10.28983/plamic2020.193.
Texte intégralLangston, Michael A., Andy D. Perkins, Arnold M. Saxton, Jon A. Scharff et Brynn H. Voy. « Innovative computational methods for transcriptomic data analysis ». Dans the 2006 ACM symposium. New York, New York, USA : ACM Press, 2006. http://dx.doi.org/10.1145/1141277.1141319.
Texte intégralCai, Hong, et Yufeng Wang. « Transcriptomic analysis using SVD clustering and SVM classification ». Dans 2011 IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS). IEEE, 2011. http://dx.doi.org/10.1109/gensips.2011.6169476.
Texte intégralNurhani, A. R. Siti, A. M. Abdul Munir, S. Mohd Wahid et A. B. Farah Diba. « A preliminary transcriptomic analysis of lichen Dirinaria sp. » Dans THE 2013 UKM FST POSTGRADUATE COLLOQUIUM : Proceedings of the Universiti Kebangsaan Malaysia, Faculty of Science and Technology 2013 Postgraduate Colloquium. AIP Publishing LLC, 2013. http://dx.doi.org/10.1063/1.4858665.
Texte intégralAlexander-Brett, J., D. Steinberg, E. Katz, C. E. Kluender, E. Roberson, S. C. Tzeng et B. Evans. « Proteomic and Transcriptomic Analysis of Exosomes in COPD ». Dans American Thoracic Society 2020 International Conference, May 15-20, 2020 - Philadelphia, PA. American Thoracic Society, 2020. http://dx.doi.org/10.1164/ajrccm-conference.2020.201.1_meetingabstracts.a4019.
Texte intégralChen, Minyu. « The Genomic and Transcriptomic Analysis of Stomach Cancer ». Dans ICBBS 2019 : 2019 8th International Conference on Bioinformatics and Biomedical Science. New York, NY, USA : ACM, 2019. http://dx.doi.org/10.1145/3369166.3369193.
Texte intégralRapports d'organisations sur le sujet "Transcriptomic analysi"
Hildebrand, Mark. Development of Renewable Biofuels Technology by Transcriptomic Analysis and Metabolic Engineering of Diatoms. Office of Scientific and Technical Information (OSTI), novembre 2013. http://dx.doi.org/10.2172/1227375.
Texte intégralTien, Ming. Transcriptome and Biochemical Analyses of Fungal Degradation of Wood. Office of Scientific and Technical Information (OSTI), mars 2009. http://dx.doi.org/10.2172/1056641.
Texte intégralGhanim, Murad, Joe Cicero, Judith K. Brown et Henryk Czosnek. Dissection of Whitefly-geminivirus Interactions at the Transcriptomic, Proteomic and Cellular Levels. United States Department of Agriculture, février 2010. http://dx.doi.org/10.32747/2010.7592654.bard.
Texte intégralWisniewski, Michael E., Samir Droby, John L. Norelli, Noa Sela et Elena Levin. Genetic and transcriptomic analysis of postharvest decay resistance in Malus sieversii and the characterization of pathogenicity effectors in Penicillium expansum. United States Department of Agriculture, janvier 2014. http://dx.doi.org/10.32747/2014.7600013.bard.
Texte intégralWisniewski, Michael, Samir Droby, John Norelli, Dov Prusky et Vera Hershkovitz. Genetic and transcriptomic analysis of postharvest decay resistance in Malus sieversii and the identification of pathogenicity effectors in Penicillium expansum. United States Department of Agriculture, janvier 2012. http://dx.doi.org/10.32747/2012.7597928.bard.
Texte intégralKatzir, Nurit, James Giovannoni, Marla Binzel, Efraim Lewinsohn, Joseph Burger et Arthur Schaffer. Genomic Approach to the Improvement of Fruit Quality in Melon (Cucumis melo) and Related Cucurbit Crops II : Functional Genomics. United States Department of Agriculture, janvier 2010. http://dx.doi.org/10.32747/2010.7592123.bard.
Texte intégralLidstrom, Mary E., Ludmila Chistoserdova, Marina G. Kalyuzhnaya, Victoria J. Orphan et David A. Beck. Systems level insights into alternate methane cycling modes in a freshwater lake via community transcriptomics, metabolomics and nano-SIMS analysis. Office of Scientific and Technical Information (OSTI), août 2014. http://dx.doi.org/10.2172/1149958.
Texte intégralLibray, Spring. The Booming Field of Epitranscriptomics and its Role in Human Disease. Spring Library, avril 2021. http://dx.doi.org/10.47496/sl.blog.26.
Texte intégralRon, Eliora, et Eugene Eugene Nester. Global functional genomics of plant cell transformation by agrobacterium. United States Department of Agriculture, mars 2009. http://dx.doi.org/10.32747/2009.7695860.bard.
Texte intégralWestwood, James H., Yaakov Tadmor et Hanan Eizenberg. Identifying the genes involved in host root perception by root parasitic weeds : Genetic and transcriptomic analysis of Orobanche hybrids differing in signal response specificity. United States Department of Agriculture, janvier 2013. http://dx.doi.org/10.32747/2013.7598145.bard.
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