Search Results - "RNA-Seq data" :: K.UTB vyhledávací portál

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Detecting differential usage of exons from RNA-seq data

by Anders, Simon, Reyes, Alejandro, Huber, Wolfgang
Published in Genome research (01.10.2012)

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Benchmarking methods for detecting differential states between conditions from multi-subject single-cell RNA-seq data

by Junttila, Sini, Smolander, Johannes, Elo, Laura L
Published in Briefings in bioinformatics (20.09.2022)

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eSVD-DE: cohort-wide differential expression in single-cell RNA-seq data using exponential-family embeddings

by Lin, Kevin Z., Qiu, Yixuan, Roeder, Kathryn
Published in BMC bioinformatics (15.03.2024)

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CathaCyc, a Metabolic Pathway Database Built from Catharanthus roseus RNA-Seq Data

by Van Moerkercke, Alex, Fabris, Michele, Pollier, Jacob, Baart, Gino J.E., Rombauts, Stephane, Hasnain, Ghulam, Rischer, Heiko, Memelink, Johan, Oksman-Caldentey, Kirsi-Marja, Goossens, Alain
Published in Plant and cell physiology (01.05.2013)

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Using RNA-seq data to select reference genes for normalizing gene expression in apple roots

by Zhou, Zhe, Cong, Peihua, Tian, Yi, Zhu, Yanmin
Published in PloS one (21.09.2017)

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Prioritizing Autism Risk Genes Using Personalized Graphical Models Estimated From Single-Cell RNA-seq Data

by Liu, Jianyu, Wang, Haodong, Sun, Wei, Liu, Yufeng
Published in Journal of the American Statistical Association (02.01.2022)

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V-SVA: an R Shiny application for detecting and annotating hidden sources of variation in single-cell RNA-seq data

by Lawlor, Nathan, Marquez, Eladio J, Lee, Donghyung, Ucar, Duygu
Published in Bioinformatics (01.06.2020)

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scReClassify: post hoc cell type classification of single-cell rNA-seq data

by Kim, Taiyun, Lo, Kitty, Geddes, Thomas A., Kim, Hani Jieun, Yang, Jean Yee Hwa, Yang, Pengyi
Published in BMC genomics (24.12.2019)

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Cell type-aware analysis of RNA-seq data

by Jin, Chong, Chen, Mengjie, Lin, Danyu, Sun, Wei
Published in Nature Computational Science (01.04.2021)

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A novel method for predicting cell abundance based on single-cell RNA-seq data

by Peng, Jiajie, Han, Lu, Shang, Xuequn
Published in BMC bioinformatics (25.08.2021)

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An augmented GSNMF model for complete deconvolution of bulk RNA-seq data

by Li, Shaoyu, Xu, Su, Wang, Xue, Ertekin-Taner, Nilüfer, Chen, Duan
Published in Mathematical biosciences and engineering : MBE (14.03.2025)

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Reference gene selection for real-time qPCR in European flounder (Platichthys flesus) using organ-specific RNA-seq data

by Pomianowski, Konrad, Burzyński, Artur
Published in Molecular biology reports (01.12.2025)

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Penalised regression improves imputation of cell-type specific expression using RNA-seq data from mixed cell populations compared to domain-specific methods

by Lin, Wei-Yu, Kartawinata, Melissa, Jebson, Bethany R., Restuadi, Restuadi, Peckham, Hannah, Radziszewska, Anna, Deakin, Claire T., Ciurtin, Coziana, Wedderburn, Lucy R., Wallace, Chris
Published in PLoS computational biology (07.03.2025)

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Estimating the strength of expression conservation from high throughput RNA-seq data

by Gu, Xun, Ruan, Hang, Yang, Jingwen
Published in Bioinformatics (01.12.2019)

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Machine learning model for predicting Major Depressive Disorder using RNA-Seq data: optimization of classification approach

by Verma, Pragya, Shakya, Madhvi
Published in Cognitive neurodynamics (01.04.2022)

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SeqGSEA: a Bioconductor package for gene set enrichment analysis of RNA-Seq data integrating differential expression and splicing

by Wang, Xi, Cairns, Murray J.
Published in Bioinformatics (Oxford, England) (15.06.2014)

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Inflammation-based lung adenocarcinoma molecular subtype identification and construction of an inflammation-related signature with bulk and single-cell RNA-seq data

by Gu, Yan, Bian, Chengyu, Wang, Hongchang, Fu, Chenghao, Xue, Wentao, Zhang, Wenhao, Mu, Guang, Xia, Yang, Wei, Ke, Wang, Jun
Published in Aging (Albany, NY.) (20.05.2024)

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Poisson–Tweedie mixed-effects model: A flexible approach for the analysis of longitudinal RNA-seq data

by Signorelli, Mirko, Spitali, Pietro, Tsonaka, Roula
Published in Statistical modelling (01.12.2021)

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scID Uses Discriminant Analysis to Identify Transcriptionally Equivalent Cell Types across Single-Cell RNA-Seq Data with Batch Effect

by Boufea, Katerina, Seth, Sohan, Batada, Nizar N.
Published in iScience (27.03.2020)

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sNucConv: A bulk RNA-seq deconvolution method trained on single-nucleus RNA-seq data to estimate cell-type composition of human adipose tissues

by Sorek, Gil, Haim, Yulia, Chalifa-Caspi, Vered, Lazarescu, Or, Ziv-Agam, Maya, Hagemann, Tobias, Nono Nankam, Pamela Arielle, Blüher, Matthias, Liberty, Idit F., Dukhno, Oleg, Kukeev, Ivan, Yeger-Lotem, Esti, Rudich, Assaf, Levin, Liron
Published in iScience (19.07.2024)

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