Relevant bibliographies by topics / RNAseq analysis

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'RNAseq analysis'

Author: Grafiati
Published: 2 November 2024
Last updated: 31 July 2025

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Journal articles on the topic "RNAseq analysis"

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PAI, TUN-WEN, BO-HAN SU, PEI-CHIH WU, et al. "UNIQUE PEPTIDE IDENTIFICATION OF RNaseA SUPERFAMILY SEQUENCES BASED ON REINFORCED MERGING ALGORITHMS." Journal of Bioinformatics and Computational Biology 04, no. 01 (2006): 75–92. http://dx.doi.org/10.1142/s0219720006001710.

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Human ribonuclease A (RNaseA) superfamily consists of eight RNases with high similarity in which RNase2 and RNase3 share 76.7% identity. The evolutionary variation of RNases results in differential structures and functions of the enzymes. To distinguish the characteristics of each RNase, we developed reinforced merging algorithms (RMA) to rapidly identify the unique peptide motifs for each member of the highly conserved human RNaseA superfamily. Many motifs in RNase3 identified by RMA correlated well with the antigenic regions predicted by DNAStar. Two unique peptide motifs were experimentally
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Colombo, Anthony R., Timothy J. Triche Jr, and Giridharan Ramsingh. "Arkas: Rapid reproducible RNAseq analysis." F1000Research 6 (April 27, 2017): 586. http://dx.doi.org/10.12688/f1000research.11355.1.

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The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments. We offer cloud-scale RNAseq pipelines Arkas-Quantification, which deploys Kallisto for parallel cloud computations, and Arkas-Analysis, which annotates the Kallisto results by extracting structured information directly from source FASTA files with per-contig metadata and calculates the differential expression and gene-set enrichment analysis on both coding genes and transcripts. The biologically informative downstream gene-set analysis maintains special focus
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Colombo, Anthony R., Timothy J. Triche Jr, and Giridharan Ramsingh. "Arkas: Rapid reproducible RNAseq analysis." F1000Research 6 (June 21, 2017): 586. http://dx.doi.org/10.12688/f1000research.11355.2.

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The recently introduced Kallisto pseudoaligner has radically simplified the quantification of transcripts in RNA-sequencing experiments. We offer cloud-scale RNAseq pipelines Arkas-Quantification, and Arkas-Analysis available within Illumina’s BaseSpace cloud application platform which expedites Kallisto preparatory routines, reliably calculates differential expression, and performs gene-set enrichment of REACTOME pathways. Due to inherit inefficiencies of scale, Illumina's BaseSpace computing platform offers a massively parallel distributive environment improving data management services and
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Lamping, Mario, Damian Tobias Rieke, Frederick Klauschen, et al. "Clinical impact of comprehensive versus targeted genomic analysis for precision oncology." Journal of Clinical Oncology 37, no. 15_suppl (2019): e13033-e13033. http://dx.doi.org/10.1200/jco.2019.37.15_suppl.e13033.

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e13033 Background: Panel sequencing (PS) has become a standard-of-care in cancer diagnostics. More comprehensive analyses such as whole-exome (WES) or RNA sequencing (RNAseq) allow for the detection of rare and unknown genetic aberrations that are not covered by predefined assays. The clinical impact of targeted versus comprehensive genomic assays were analyzed in patients presented at the Charité Molecular Tumor Board (MTB). Methods: Patients (pts) with advanced and/or metastatic cancer for whom no standard therapy was available were discussed in the MTB to allocate diagnostic profiling and g
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Guo, Yan, Shilin Zhao, Chung-I. Li, Quanhu Sheng, and Yu Shyr. "RNAseqPS: A Web Tool for Estimating Sample Size and Power for RNAseq Experiment." Cancer Informatics 13s6 (January 2014): CIN.S17688. http://dx.doi.org/10.4137/cin.s17688.

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Sample size and power determination is the first step in the experimental design of a successful study. Sample size and power calculation is required for applications for National Institutes of Health (NIH) funding. Sample size and power calculation is well established for traditional biological studies such as mouse model, genome wide association study (GWAS), and microarray studies. Recent developments in high-throughput sequencing technology have allowed RNAseq to replace microarray as the technology of choice for high-throughput gene expression profiling. However, the sample size and power
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Guo, Yan, Shilin Zhao, Fei Ye, Quanhu Sheng, and Yu Shyr. "MultiRankSeq: Multiperspective Approach for RNAseq Differential Expression Analysis and Quality Control." BioMed Research International 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/248090.

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Background. After a decade of microarray technology dominating the field of high-throughput gene expression profiling, the introduction of RNAseq has revolutionized gene expression research. While RNAseq provides more abundant information than microarray, its analysis has proved considerably more complicated. To date, no consensus has been reached on the best approach for RNAseq-based differential expression analysis. Not surprisingly, different studies have drawn different conclusions as to the best approach to identify differentially expressed genes based upon their own criteria and scenario
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Mora-Márquez, Fernando, José Luis Vázquez-Poletti, and Unai López de Heredia. "NGScloud2: optimized bioinformatic analysis using Amazon Web Services." PeerJ 9 (April 16, 2021): e11237. http://dx.doi.org/10.7717/peerj.11237.

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Background NGScloud was a bioinformatic system developed to perform de novo RNAseq analysis of non-model species by exploiting the cloud computing capabilities of Amazon Web Services. The rapid changes undergone in the way this cloud computing service operates, along with the continuous release of novel bioinformatic applications to analyze next generation sequencing data, have made the software obsolete. NGScloud2 is an enhanced and expanded version of NGScloud that permits the access to ad hoc cloud computing infrastructure, scaled according to the complexity of each experiment. Methods NGSc
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Kalinina, Alena, and Diane Lagace. "Single-Cell and Single-Nucleus RNAseq Analysis of Adult Neurogenesis." Cells 11, no. 10 (2022): 1633. http://dx.doi.org/10.3390/cells11101633.

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The complexity of adult neurogenesis is becoming increasingly apparent as we learn more about cellular heterogeneity and diversity of the neurogenic lineages and stem cell niches within the adult brain. This complexity has been unraveled in part due to single-cell and single-nucleus RNA sequencing (sc-RNAseq and sn-RNAseq) studies that have focused on adult neurogenesis. This review summarizes 33 published studies in the field of adult neurogenesis that have used sc- or sn-RNAseq methods to answer questions about the three main regions that host adult neural stem cells (NSCs): the subventricul
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Guo, Yan, Chung-I. Li, Fei Ye, and Yu Shyr. "Evaluation of read count based RNAseq analysis methods." BMC Genomics 14, Suppl 8 (2013): S2. http://dx.doi.org/10.1186/1471-2164-14-s8-s2.

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Zakharova, Galina, Maria Suntsova, Elizaveta Rabushko, et al. "A New Approach of Detecting ALK Fusion Oncogenes by RNA Sequencing Exon Coverage Analysis." Cancers 16, no. 22 (2024): 3851. http://dx.doi.org/10.3390/cancers16223851.

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Background: In clinical practice, various methods are used to identify ALK gene rearrangements in tumor samples, ranging from “classic” techniques, such as IHC, FISH, and RT-qPCR, to more advanced highly multiplexed approaches, such as NanoString technology and NGS panels. Each of these methods has its own advantages and disadvantages, but they share the drawback of detecting only a restricted (although sometimes quite extensive) set of preselected biomarkers. At the same time, whole transcriptome sequencing (WTS, RNAseq) can, in principle, be used to detect gene fusions while simultaneously a
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Dissertations / Theses on the topic "RNAseq analysis"

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Liu, Oscar H. "RNAseq Analysis of Gastric Bacteria in Helicobacter pylori-Associated Carcinogenesis." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9937.

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Helicobacter pylori infects more than half of the world's population, and is known to be involved in several diseases including gastric cancer. Its close interactions with the stomach and host immune system serves as a good model to study the co-adaptation and co-evolution of the organisms in the stomach micro-environment. In this project, we utilized RNA-seq and data analysis tools to investigate differentially expressed genes by H. pylori in patients at different stages of early gastric cancer development. We also investigated the abundance and diversity of bacterial genera other than H. pyl
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Simon, Svenja [Verfasser]. "Visual Analysis of RNAseq Data : Discovering Genes in Bacteria / Svenja Simon." Konstanz : Bibliothek der Universität Konstanz, 2015. http://d-nb.info/1114886580/34.

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Aksamit, Matthew Stephen. "Bioinformatic analysis of pea aphid salivary gland transcripts." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/32836.

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Master of Science<br>Biochemistry and Molecular Biophysics Interdepartmental Program<br>Gerald Reeck<br>Pea aphids (Acyrthosiphon pisum) are sap-sucking insects that feed on the phloem sap of some plants of the family Fabaceae (legumes). Aphids feed on host plants by inserting their stylets between plant cells to feed from phloem sap in sieve elements. Their feeding is of major agronomical importance, as aphids cause hundreds of millions of dollars in crop damage worldwide, annually. Salivary gland transcripts from plant-fed and diet-fed pea aphids were studied by RNASeq to analyze
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Ahmed, Firdous. "Identification of potential biomarkers in lung cancer as possible diagnostic agents using bioinformatics and molecular approaches." University of the Western Cape, 2015. http://hdl.handle.net/11394/4862.

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>Magister Scientiae - MSc<br>Lung cancer remains the leading cause of cancer deaths worldwide, with the majority of cases attributed to non-small cell lung carcinomas. At the time of diagnosis, a large percentage of patients present with advanced stage of disease, ultimately resulting in a poor prognosis. The identification circulatory markers, overexpressed by the tumour tissue, could facilitate the discovery of an early, specific, non-invasive diagnostic tool as well as improving prognosis and treatment protocols. The aim was to analyse gene expression data from both microarray and RNA seque
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Sadacca, Benjamin. "Pharmacogenomic and High-Throughput Data Analysis to Overcome Triple Negative Breast Cancers Drug Resistance." Thesis, Université Paris-Saclay (ComUE), 2017. http://www.theses.fr/2017SACLS538/document.

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Devant le grand nombre de tumeurs du sein triple négatif résistant aux traitements, il est essentiel de comprendre les mécanismes de résistance et de trouver de nouvelles molécules efficaces. En premier lieu, nous analysons deux ensembles de données pharmacogénomiques à grande échelle. Nous proposons une nouvelle classification basée sur des profils transcriptomiques de lignées cellulaires, selon un processus de sélection de gènes basé sur des réseaux biologiques. Notre classification moléculaire montre une plus grande homogénéité dans la réponse aux médicaments que lorsque l’on regroupe les l
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Grosse-Holz, Friederike. "Proteases and inhibitors in the interaction between Nicotiana benthamiana and Agrobacterium tumefaciens : systematic analysis and emerging solutions for molecular farming." Thesis, University of Oxford, 2017. https://ora.ox.ac.uk/objects/uuid:6146918c-3749-4604-88fa-01d426e4a817.

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Nicotiana benthamiana is now an established platform for molecular farming, the production of biopharmaceuticals in plants. Infiltration with Agrobacterium tumefaciens (agroinfiltration) is commonly used to transiently express one or multiple transgenes in N. benthamiana leaves. Agroinfiltrated N. benthamiana is a flexible and scalable recombinant protein (RP) production platform, but is impeded by low RP yields. Plant proteases can degrade RPs and thus limit RP accumulation. To inform, design and implement strategies for enhancing RP accumulation, I present four papers about proteases and pro
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DAS, VIVEK. "LEVERAGING TRANSCRIPTOMIC ANALYSIS TO IDENTIFY TRANSCRIPTION FACTORS ORCHESTRATING CANCER PROGRESSION." Doctoral thesis, Università degli Studi di Milano, 2018. http://hdl.handle.net/2434/559711.

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Next generation sequencing (NGS) technology is currently employed to explore the molecular profiles associated to different biological contexts. The application of this technology provides at same time a high-resolution and global view of the genome and epigenome phenomena, enabling us to study the molecular events underlying many human diseases, including cancer. Our lab tries to exploit the utility of high throughput sequencing technologies generating genomic, transcriptomic and epigenomic data from patient's cohort to study the underlying molecular mechanisms that characterize the specific
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Couto, Joana Manuel Gonçalves Teixeira. "Transcriptomic analysis of Anopheles Stephensi salivary glands during the infection with Plasmodium Berghei." Master's thesis, Universidade de Aveiro, 2015. http://hdl.handle.net/10773/14639.

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Mestrado em Biologia Molecular e Celular<br>Malaria remains the leading cause of morbidity and mortality in tropical and subtropical regions, contributing to the emergence of 198 million clinical cases in 2013. The mosquito Anopheles stephensi is one of the most prevalent malaria vectors in the Asian region having recently been implicated in malaria resurgence in Djibouti. Using techniques as RNA sequencing, differentially expressed genes in the salivary glands of the mosquito in response to infection by Plasmodium berghei were identified. Some of these genes can be selected to evaluate
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Ahmed, Fathima Zuba. "Unravelling genes responsible for successful anthocyanin production in Nicotiana benthamiana." Thesis, Queensland University of Technology, 2022. https://eprints.qut.edu.au/230763/1/Fathima%20Zuba_Ahmed_Thesis.pdf.

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This thesis utilised two approaches, forward genetics and comparative transcriptomic analysis, to investigate the contrasting response to anthocyanin production observed in two distinct Nicotiana benthamiana ecotypes, LAB and QLD. The thesis is a step forward in utilising N. benthamiana as a candidate in forward genetics, currently limited due to its large complex genome and polyploid nature. The study utilised a cross-population between LAB and QLD to investigate the nature of inheritance of the contrasting parental phenotypes in its progeny. Additionally, expression profiles of anthocyanin b
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Meunier, Léa. "Analyse de signatures transcriptomiques et épigénétiques des carcinomes hépatocellulaires." Thesis, Université de Paris (2019-....), 2020. http://www.theses.fr/2020UNIP7082.

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Élucider les processus transcriptionnels et épigénétiques dérégulés dans les cancers est fondamental pour mieux comprendre les voies biologiques impliquées et proposer une thérapie adaptée au phénotype moléculaire de chaque tumeur. Les approches classiques de classification non supervisée définissent des groupes moléculaires principaux pour chaque type tumoral. Cependant, ces méthodes, appliquées à des tumeurs complexes comme le carcinome hépatocellulaire (CHC), le 3ème cancer le plus mortel au monde, définissent des groupes qui restent relativement hétérogènes et ne reflètent qu’imparfaitemen
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Books on the topic "RNAseq analysis"

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1925-, Cherayil J. D., ed. Transfer RNAs and other soluble RNAs. CRC Press, 1990.

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Cao, Haiming, ed. Functional Analysis of Long Non-Coding RNAs. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1158-6.

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Rederstorff, Mathieu. Small non-coding RNAs: Methods and protocols. Humana Press, 2015.

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R Bioinformatics Cookbook: Use R and Bioconductor to Perform RNAseq, Genomics, Data Visualization, and Bioinformatic Analysis. Packt Publishing, Limited, 2019.

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Nellen, Wolfgang, and Christian Hammann. Small RNAs : : Analysis and Regulatory Functions. Springer London, Limited, 2007.

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Cao, Haiming. Functional Analysis of Long Non-Coding RNAs: Methods and Protocols. Springer, 2020.

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Cao, Haiming. Functional Analysis of Long Non-Coding RNAs: Methods and Protocols. Springer, 2021.

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(Editor), Wolfgang Nellen, and Christian Hammann (Editor), eds. Small RNAs:: Analysis and Regulatory Functions (Nucleic Acids and Molecular Biology). Springer, 2007.

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(Editor), Wolfgang Nellen, and Christian Hammann (Editor), eds. Small RNAs:: Analysis and Regulatory Functions (Nucleic Acids and Molecular Biology). Springer, 2005.

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Rederstorff, Mathieu. Small Non-Coding RNAs: Methods and Protocols. Springer, 2022.

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Book chapters on the topic "RNAseq analysis"

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Cagnin, Stefano, Enrico Alessio, Raphael Severino Bonadio, and Gabriele Sales. "Single-Cell RNAseq Analysis of lncRNAs." In Long Non-Coding RNAs in Cancer. Springer US, 2021. http://dx.doi.org/10.1007/978-1-0716-1581-2_5.

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Sharma, Preeti, B. Sharan Sharma, and Ramtej J. Verma. "A Guide to RNAseq Data Analysis Using Bioinformatics Approaches." In Advances in Bioinformatics. Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-33-6191-1_12.

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Majerczyk, Charlotte D. "Global Expression Analysis of Quorum Sensing-Controlled Genes by RNAseq." In Methods in Molecular Biology. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-7309-5_14.

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Croce, Olivier, and Eric Röttinger. "Creating a User-Friendly and Open-Access Gene Expression Database for Comparing Embryonic Development and Regeneration in Nematostella vectensis." In Methods in Molecular Biology. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2172-1_35.

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AbstractThe sea anemone Nematostella vectensis has emerged as a powerful research model to understand at the gene regulatory network level, to what extend regeneration recapitulates embryonic development. Such comparison involves massive transcriptomic analysis, a routine approach for identifying differential gene expression. Here we present a workflow to build a user-friendly, mineable, and open-access database providing access to the scientific community to various RNAseq datasets.
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Grassmann, Felix. "Conduct and Quality Control of Differential Gene Expression Analysis Using High-Throughput Transcriptome Sequencing (RNASeq)." In Methods in Molecular Biology. Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-8669-9_2.

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Ocaña, Kary, Lucas Cruz, Micaella Coelho, et al. "ParslRNA-Seq: An Efficient and Scalable RNAseq Analysis Workflow for Studies of Differentiated Gene Expression." In Communications in Computer and Information Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23821-5_13.

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Kopajtich, Robert, Johannes A. Mayr, and Holger Prokisch. "Analysis of Mitochondrial RNA-Processing Defects in Patient-Derived Tissues by qRT-PCR and RNAseq." In Methods in Molecular Biology. Springer New York, 2017. http://dx.doi.org/10.1007/978-1-4939-6824-4_23.

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Ender, Anna, Peter F. Stadler, Mario Mörl, and Sven Findeiß. "RNA Design Principles for Riboswitches that Regulate RNase P-Mediated tRNA Processing." In Riboregulator Design and Analysis. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2421-0_11.

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Ender, Anna, Peter F. Stadler, Mario Mörl, and Sven Findeiß. "RNA Design Principles for Riboswitches that Regulate RNase P-Mediated tRNA Processing." In Riboregulator Design and Analysis. Springer US, 2022. http://dx.doi.org/10.1007/978-1-0716-2421-0_11.

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Hallier, Marc, Svetlana Chabelskaya, and Brice Felden. "Experimental Analyses of RNA-Based Regulations in Bacteria." In Regulatory RNAs. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-662-45801-3_14.

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Conference papers on the topic "RNAseq analysis"

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Oba-Shinjo, Sueli M., Lais C. Cardoso, Roseli da Silva, Antonio M. Lerario, Miyuki Uno, and Suely S. K. Marie. "Abstract 66: CD99 functional analysis in glioblastoma by RNAseq." In Proceedings: AACR 106th Annual Meeting 2015; April 18-22, 2015; Philadelphia, PA. American Association for Cancer Research, 2015. http://dx.doi.org/10.1158/1538-7445.am2015-66.

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Legeai, Fabrice, Susete Alves-Carvalho, Kévin Gazengel, Anthony Bretaudeau, Stéphanie Robin, and Stéphanie Daval. "AskoR, A R Package for Easy RNASeq Data Analysis." In The 1st International Electronic Conference on Entomology. MDPI, 2021. http://dx.doi.org/10.3390/iece-10646.

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Bhuvaneshwar, Krithika, Coleman I. Smith, Alexander H. Kroemer, Aiwu Ruth He, and Yuriy Gusev. "Abstract 548: RNAseq analysis of infiltrating immune cells in liver cancer." 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.am2017-548.

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Lunev, E. A., E. A. Volovikov, S. V. Popov, T. V. Egorova, and M. V. Bardina. "INVERTED TERMINAL REPEATS OF THE ADENO-ASSOCIATED VIRUS DEMONSTRATE PROMOTER ACTIVITY IN GABAERGIC NEURONS IN VITRO." In XI МЕЖДУНАРОДНАЯ КОНФЕРЕНЦИЯ МОЛОДЫХ УЧЕНЫХ: БИОИНФОРМАТИКОВ, БИОТЕХНОЛОГОВ, БИОФИЗИКОВ, ВИРУСОЛОГОВ, МОЛЕКУЛЯРНЫХ БИОЛОГОВ И СПЕЦИАЛИСТОВ ФУНДАМЕНТАЛЬНОЙ МЕДИЦИНЫ. IPC NSU, 2024. https://doi.org/10.25205/978-5-4437-1691-6-86.

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Khademioureh, Sara, Irina Dinu, and Sergio Peignier. "GSHAPA: Gene Set Analysis for Single-Cell RNAseq Using Random Forest and SHAP Values." In SAC '25: 40th ACM/SIGAPP Symposium on Applied Computing. ACM, 2025. https://doi.org/10.1145/3672608.3707901.

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Ryan, Michael C., and John N. Weinstein. "Abstract 1796: Analysis of TCGA RNASeq data using SpliceSeq provides a survey of alternative splicing in cancer." 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.am2013-1796.

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Toccacieli, Ali, and Manuela Petti. "Identification of Cancer Biomarkers for Multi-class Diagnostics through Network Analysis of RNAseq Data of Tumor-Educated Platelets." In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM). IEEE, 2022. http://dx.doi.org/10.1109/bibm55620.2022.9995086.

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Mavrommatis, Konstantinos, Lauren Intagliata, Garth McGrath, Daniel Civello, and Maureen Cronin. "Abstract 3626: Establishing a robust NGS laboratory workflow and analysis pipeline for FFPE specimen RNAseq to support biopharmaceutical translational research." In Proceedings: AACR 107th Annual Meeting 2016; April 16-20, 2016; New Orleans, LA. American Association for Cancer Research, 2016. http://dx.doi.org/10.1158/1538-7445.am2016-3626.

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Wu, Xue, Yue Zhao, Xiaoyu Xie, et al. "Abstract 549: Genome-wide CRISPR-Cas9 screen and RNAseq analysis identify new candidate synthetic lethality partners to PARP inhibitor in triple-negative breast cancer." In Proceedings: AACR Annual Meeting 2020; April 27-28, 2020 and June 22-24, 2020; Philadelphia, PA. American Association for Cancer Research, 2020. http://dx.doi.org/10.1158/1538-7445.am2020-549.

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Pineda, R. H., N. Mitash, K. Kohler, et al. "Differential RNAseq Analysis of an Ex-Vivo Human Fibrotic Tissue Slice Model Reveals Dysregulated Genes of Cellular Senescence and YAP/TAZ Signaling in Fibrosis." In American Thoracic Society 2022 International Conference, May 13-18, 2022 - San Francisco, CA. American Thoracic Society, 2022. http://dx.doi.org/10.1164/ajrccm-conference.2022.205.1_meetingabstracts.a5229.

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Reports on the topic "RNAseq analysis"

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Lers, Amnon, E. Lomaniec, S. Burd, A. Khalchitski, L. Canetti, and Pamela J. Green. Analysis of Senescence Inducible Ribonuclease in Tomato: Gene Regulation and Function. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7570563.bard.

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Natural leaf senescence has a negative influence on yield. Postharvest induced senescence contributes to the losses of quality in flowers, foliage, and vegetables. Strategies designed to control the senescence process in crop plants could therefore have great applied significance. Senescence is regulated by differential gene expression yet, functional characterization of the genes specifically induced and study of their expression control, is still in its infancy. Study of senescence-specific genes is required to allow identification of regulatory elements participating in senescence-induced e
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Glazer, Itamar, Alice Churchill, Galina Gindin, and Michael Samish. Genomic and Organismal Studies to Elucidate the Mechanisms of Infectivity of Entomopathogenic Fungi to Ticks. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7593382.bard.

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The overall goal of this research was to elucidate the factors affecting early development of Metarhizium spp. (previously named M. anisopliae) on ticks or tick cuticle extracts and the molecular basis of these early infection processes. The original objectives were: 1. Characterize the pre-penetration events (adhesion, germination and appressorium formation) of spores of M. anisopliae strains with high or low virulence during tick infection. 2. Create GFP-expressing strains of M. anisopliae tick pathogens having high and low virulence to compare their progress of infection by microscopy. 3. U
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Schuster, Gadi, and David Stern. Integrated Studies of Chloroplast Ribonucleases. United States Department of Agriculture, 2011. http://dx.doi.org/10.32747/2011.7697125.bard.

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Gene regulation at the RNA level encompasses multiple mechanisms in prokaryotes and eukaryotes, including splicing, editing, endo- and exonucleolytic cleavage, and various phenomena related to small or interfering RNAs. Ribonucleases are key players in nearly all of these post-transcriptional mechanisms, as the catalytic agents. This proposal continued BARD-funded research into ribonuclease activities in the chloroplast, where RNase mutation or deficiency can cause metabolic defects and is often associated with plant chlorosis, embryo or seedling lethality, and/or failure to tolerate nutrient
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Ori, Naomi, and Mark Estelle. Specific mediators of auxin activity during tomato leaf and fruit development. United States Department of Agriculture, 2012. http://dx.doi.org/10.32747/2012.7597921.bard.

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The plant hormone auxin is involved in numerous developmental processes, including leaf and fruit development. The tomato (Solanumlycopersicum) gene ENTIRE (E) encodes an auxin-response inhibitor from the Aux/IAA family. While most loss-offunction mutations in Aux/IAA genes are similar to the wild type due to genetic redundancy, entire (e) mutants show specific effects on leaf and fruit development. e mutants have simple leaves, in contrast to the compound leaves of wild type tomatoes. In addition, e plants produce parthenocarpic fruits, in which fruit set occurs independently of fertilization
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Lers, Amnon, and Pamela J. Green. LX Senescence-Induced Ribonuclease in Tomato: Function and Regulation. United States Department of Agriculture, 2003. http://dx.doi.org/10.32747/2003.7586455.bard.

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Natural leaf senescence, which occurs even when growth conditions are near optimal, has a negative influence on yield. Postharvest induced senescence contributes to the losses of quality in flowers, foliage, and vegetables. Strategies designed to control the senescence process in crop plants could therefore have great applied significance. However, the successful design of such strategies requires a better insight into the senescence machinery and control in higher plants. A main feature of senescence is the hydrolysis of macromolecules by hydrolases of various types such as ribonucleases (RNa
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Eyal, Yoram, and Sheila McCormick. Molecular Mechanisms of Pollen-Pistil Interactions in Interspecific Crossing Barriers in the Tomato Family. United States Department of Agriculture, 2000. http://dx.doi.org/10.32747/2000.7573076.bard.

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During the evolutionary process of speciation in plants, naturally occurring barriers to reproduction have developed that affect the transfer of genes within and between related species. These barriers can occur at several different levels beginning with pollination-barriers and ending with hybrid-breakdown. The interaction between pollen and pistils presents one of the major barriers to intra- and inter-specific crosses and is the focus of this research project. Our long-term goal in this research proposal was defined to resolve questions on recognition and communication during pollen-pistil
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Lers, Amnon, and Pamela J. Green. Analysis of Small RNAs Associated with Plant Senescence. United States Department of Agriculture, 2013. http://dx.doi.org/10.32747/2013.7593393.bard.

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Senescence is an agriculturally significant process due to its negative impact to crop yield and postharvest quality. The genetic regulatory systems controlling senescence induction and progress respond to both developmental and environmental stress signals and involve numerous gene expression changes. Knowledge about the key molecular factors which control senescence is very limited. MicroRNAs (miRNAs) are a class of small RNAs which typically function by guiding cleavage of target messenger RNAs. They have been shown to play major roles in a variety of plant processes including development,
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Splitter, Gary A., Menachem Banai, and Jerome S. Harms. Brucella second messenger coordinates stages of infection. United States Department of Agriculture, 2011. http://dx.doi.org/10.32747/2011.7699864.bard.

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Aim 1: To determine levels of this second messenger in: a) B. melitensiscyclic-dimericguanosinemonophosphate-regulating mutants (BMEI1448, BMEI1453, and BMEI1520), and b) B. melitensis16M (wild type) and mutant infections of macrophages and immune competent mice. (US lab primary) Aim 2: To determine proteomic differences between Brucelladeletion mutants BMEI1453 (high cyclic-dimericguanosinemonophosphate, chronic persistent state) and BMEI1520 (low cyclicdimericguanosinemonophosphate, acute virulent state) compared to wild type B. melitensisto identify the role of this second messenger in esta
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Zhong, xiaoling. Diagnostic Significance of Noncoding RNAs in Kawasaki Disease: A Systematic Review and Meta-Analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2022. http://dx.doi.org/10.37766/inplasy2022.10.0035.

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Xu, Jianhao, Fang Cao, Yongwei Hu, and Zaichang Chen. Circulating long noncoding RNAs as potential biomarkers for stomach cancer: A systematic review and meta-analysis. INPLASY - International Platform of Registered Systematic Review and Meta-analysis Protocols, 2021. http://dx.doi.org/10.37766/inplasy2021.2.0079.

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