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Transcriptome analysis

Section edited by Adam Olshen

This section incorporates all aspects of transcriptomic analysis including but not limited to: methods and applications for the analysis of microarray and RNA-seq data.

Page 1 of 10

  1. Content type: Software

    High-throughput gene expression technologies provide complex datasets reflecting mechanisms perturbed in an experiment, typically in a treatment versus control design. Analysis of these information-rich data c...

    Authors: Florian Martin, Sylvain Gubian, Marja Talikka, Julia Hoeng and Manuel C. Peitsch

    Citation: BMC Bioinformatics 2019 20:451

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  2. Content type: Research article

    The epidermal growth factor receptor (EGFR) is a major regulator of proliferation in tumor cells. Elevated expression levels of EGFR are associated with prognosis and clinical outcomes of patients in a variety...

    Authors: Claus Weinholdt, Henri Wichmann, Johanna Kotrba, David H. Ardell, Matthias Kappler, Alexander W. Eckert, Dirk Vordermark and Ivo Grosse

    Citation: BMC Bioinformatics 2019 20:434

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  3. Content type: Methodology article

    Ultra-fast pseudo-alignment approaches are the tool of choice in transcript-level RNA sequencing (RNA-seq) analyses. Unfortunately, these methods couple the tasks of pseudo-alignment and transcript quantificat...

    Authors: Mohamed K Gunady, Stephen M Mount and Héctor Corrada Bravo

    Citation: BMC Bioinformatics 2019 20:421

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  4. Content type: Software

    Standard RNAseq methods using bulk RNA and recent single-cell RNAseq methods use DNA barcodes to identify samples and cells, and the barcoded cDNAs are pooled into a library pool before high throughput sequenc...

    Authors: Shintaro Katayama, Tiina Skoog, Cilla Söderhäll, Elisabet Einarsdottir, Kaarel Krjutškov and Juha Kere

    Citation: BMC Bioinformatics 2019 20:418

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  5. Content type: Methodology article

    High-dimensional data of discrete and skewed nature is commonly encountered in high-throughput sequencing studies. Analyzing the network itself or the interplay between genes in this type of data continues to ...

    Authors: Anjali Silva, Steven J. Rothstein, Paul D. McNicholas and Sanjeena Subedi

    Citation: BMC Bioinformatics 2019 20:394

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  6. Content type: Research article

    MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In ...

    Authors: Emmy Borgmästars, Hendrik Arnold de Weerd, Zelmina Lubovac-Pilav and Malin Sund

    Citation: BMC Bioinformatics 2019 20:393

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  7. Content type: Methodology article

    The QuantiGene® Plex 2.0 platform (ThermoFisher Scientific) combines bDNA with the Luminex/xMAP magnetic bead capturing technology to assess differential gene expression in a compound exposure setting. This te...

    Authors: Bie Verbist, Eva Adriaensen, Vikki Keersmaekers, Dea Putri, Marjolein Crabbe, Maarten Derks, Rytis Bagdziunas, Griet Laenen and Hans De Wolf

    Citation: BMC Bioinformatics 2019 20:378

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  8. Content type: Methodology article

    Single cell RNA sequencing (scRNA-seq) brings unprecedented opportunities for mapping the heterogeneity of complex cellular environments such as bone marrow, and provides insight into many cellular processes. ...

    Authors: Sergii Domanskyi, Anthony Szedlak, Nathaniel T Hawkins, Jiayin Wang, Giovanni Paternostro and Carlo Piermarocchi

    Citation: BMC Bioinformatics 2019 20:369

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  9. Content type: Software

    A microRNA (miRNA) sponge is an RNA molecule with multiple tandem miRNA response elements that can sequester miRNAs from their target mRNAs. Despite growing appreciation of the importance of miRNA sponges, our...

    Authors: Junpeng Zhang, Lin Liu, Taosheng Xu, Yong Xie, Chunwen Zhao, Jiuyong Li and Thuc Duy Le

    Citation: BMC Bioinformatics 2019 20:235

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  10. Content type: Methodology article

    The rapid increase in High-throughput sequencing of RNA (RNA-seq) has led to tremendous improvements in the detection and reconstruction of both expressed coding and non-coding RNA transcripts. Yet, the comple...

    Authors: Thomas Gatter and Peter F Stadler

    Citation: BMC Bioinformatics 2019 20:190

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  11. Content type: Methodology article

    For many practical hypothesis testing (H-T) applications, the data are correlated and/or with heterogeneous variance structure. The regression t-test for weighted linear mixed-effects regression (LMER) is a legit...

    Authors: Yun Zhang, Gautam Bandyopadhyay, David J. Topham, Ann R. Falsey and Xing Qiu

    Citation: BMC Bioinformatics 2019 20:185

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  12. Content type: Methodology article

    The design of an experiment influences both what a researcher can measure, as well as how much confidence can be placed in the results. As such, it is vitally important that experimental design decisions do no...

    Authors: Daphne Ezer and Joseph Keir

    Citation: BMC Bioinformatics 2019 20:166

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  13. Content type: Software

    RNA-Seq technology is routinely used to characterize the transcriptome, and to detect gene expression differences among cell types, genotypes and conditions. Advances in short-read sequencing instruments such ...

    Authors: Refael Kohen, Jonathan Barlev, Gil Hornung, Gil Stelzer, Ester Feldmesser, Kiril Kogan, Marilyn Safran and Dena Leshkowitz

    Citation: BMC Bioinformatics 2019 20:154

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  14. Content type: Methodology article

    Gene duplications are a major source of raw material for evolution and a likely contributor to the diversity of life on earth. Duplicate genes (i.e., homeologs, in the case of a whole genome duplication) may r...

    Authors: Ronald D. Smith, Taliesin J. Kinser, Gregory D. Conradi Smith and Joshua R. Puzey

    Citation: BMC Bioinformatics 2019 20:149

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  15. Content type: Methodology article

    Gene Set Enrichment Analysis (GSEA) is a powerful tool to identify enriched functional categories of informative biomarkers. Canonical GSEA takes one-dimensional feature scores derived from the data of one pla...

    Authors: Khong-Loon Tiong and Chen-Hsiang Yeang

    Citation: BMC Bioinformatics 2019 20:145

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  16. Content type: Methodology article

    Using meta-analysis, high-dimensional transcriptome expression data from public repositories can be merged to make group comparisons that have not been considered in the original studies. Merging of high-dimen...

    Authors: Christine Winter, Robin Kosch, Martin Ludlow, Albert D. M. E. Osterhaus and Klaus Jung

    Citation: BMC Bioinformatics 2019 20:144

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  17. Content type: Research article

    microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and they play an important role in various biological processes in the human body. Therefore, identifying their regulation mechanis...

    Authors: Vu VH Pham, Junpeng Zhang, Lin Liu, Buu Truong, Taosheng Xu, Trung T. Nguyen, Jiuyong Li and Thuc D. Le

    Citation: BMC Bioinformatics 2019 20:143

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  18. Content type: Software

    A large fraction of human and mouse autosomal genes are subject to random monoallelic expression (MAE), an epigenetic mechanism characterized by allele-specific gene expression that varies between clonal cell ...

    Authors: Svetlana Vinogradova, Sachit D. Saksena, Henry N. Ward, Sébastien Vigneau and Alexander A. Gimelbrant

    Citation: BMC Bioinformatics 2019 20:106

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  19. Content type: Software

    Prioritisation of gene ontology terms from differential gene expression analyses in a two-dimensional format remains a challenge with exponentially growing data volumes. Typically, gene ontology terms are repr...

    Authors: Irina Kuznetsova, Artur Lugmayr, Stefan J. Siira, Oliver Rackham and Aleksandra Filipovska

    Citation: BMC Bioinformatics 2019 20:84

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  20. Content type: Software

    Life science research is moving quickly towards large-scale experimental designs that are comprised of multiple tissues, time points, and samples. Omic time-series experiments offer answers to three big questi...

    Authors: Joshua R. Williams, Ruoting Yang, John L. Clifford, Daniel Watson, Ross Campbell, Derese Getnet, Raina Kumar, Rasha Hammamieh and Marti Jett

    Citation: BMC Bioinformatics 2019 20:81

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  21. Content type: Research article

    Non-coding RNAs (ncRNAs) are emerging as key regulators and play critical roles in a wide range of tumorigenesis. Recent studies have suggested that long non-coding RNAs (lncRNAs) could interact with microRNAs...

    Authors: Qiu Xiao, Jiawei Luo, Cheng Liang, Jie Cai, Guanghui Li and Buwen Cao

    Citation: BMC Bioinformatics 2019 20:67

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  22. Content type: Research article

    Harmonization techniques make different gene expression profiles and their sets compatible and ready for comparisons. Here we present a new bioinformatic tool termed Shambhala for harmonization of multiple hum...

    Authors: Nicolas Borisov, Irina Shabalina, Victor Tkachev, Maxim Sorokin, Andrew Garazha, Andrey Pulin, Ilya I. Eremin and Anton Buzdin

    Citation: BMC Bioinformatics 2019 20:66

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  23. Content type: Software

    Exploring cellular responses to stimuli using extensive gene expression profiles has become a routine procedure performed on a daily basis. Raw and processed data from these studies are available on public dat...

    Authors: Marco Moretto, Paolo Sonego, Ana B. Villaseñor-Altamirano and Kristof Engelen

    Citation: BMC Bioinformatics 2019 20:54

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  24. Content type: Software

    Non-co-linear (NCL) transcripts consist of exonic sequences that are topologically inconsistent with the reference genome in an intragenic fashion (circular or intragenic trans-spliced RNAs) or in an intergenic f...

    Authors: Chia-Ying Chen and Trees-Juen Chuang

    Citation: BMC Bioinformatics 2019 20:3

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  25. Content type: Research article

    Selection for feed efficiency is crucial for overall profitability and sustainability in dairy cattle production. Key regulator genes and genetic markers derived from co-expression networks underlying feed eff...

    Authors: S. M. Salleh, G. Mazzoni, P. Løvendahl and H. N. Kadarmideen

    Citation: BMC Bioinformatics 2018 19:513

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  26. Content type: Methodology article

    Unsupervised clustering represents one of the most widely applied methods in analysis of high-throughput ‘omics data. A variety of unsupervised model-based or parametric clustering methods and non-parametric c...

    Authors: Qian Li, Janelle R. Noel-MacDonnell, Devin C. Koestler, Ellen L. Goode and Brooke L. Fridley

    Citation: BMC Bioinformatics 2018 19:474

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  27. Content type: Software

    The knowledge of miRNAs regulating the expression of sets of mRNAs has led to novel insights into numerous and diverse cellular mechanisms. While a single miRNA may regulate many genes, one gene can be regulat...

    Authors: Luqman Hakim Abdul Hadi, Quy Xiao Xuan Lin, Tri Tran Minh, Marie Loh, Hong Kiat Ng, Agus Salim, Richie Soong and Touati Benoukraf

    Citation: BMC Bioinformatics 2018 19:299

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  28. Content type: Research article

    Count data generated by next-generation sequencing assays do not measure absolute transcript abundances. Instead, the data are constrained to an arbitrary “library size” by the sequencing depth of the assay, a...

    Authors: Thomas P. Quinn, Tamsyn M. Crowley and Mark F. Richardson

    Citation: BMC Bioinformatics 2018 19:274

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  29. Content type: Methodology article

    Combining genomic data sets from multiple studies is advantageous to increase statistical power in studies where logistical considerations restrict sample size or require the sequential generation of data. How...

    Authors: Yuqing Zhang, David F. Jenkins, Solaiappan Manimaran and W. Evan Johnson

    Citation: BMC Bioinformatics 2018 19:262

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  30. Content type: Methodology article

    The single cell RNA sequencing (scRNA-seq) technique begin a new era by allowing the observation of gene expression at the single cell level. However, there is also a large amount of technical and biological n...

    Authors: Wuming Gong, Il-Youp Kwak, Pruthvi Pota, Naoko Koyano-Nakagawa and Daniel J. Garry

    Citation: BMC Bioinformatics 2018 19:220

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  31. Content type: Research article

    The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-speci...

    Authors: Ankit Jambusaria, Jeff Klomp, Zhigang Hong, Shahin Rafii, Yang Dai, Asrar B. Malik and Jalees Rehman

    Citation: BMC Bioinformatics 2018 19:217

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  32. Content type: Methodology article

    To ensure cancer patients are stratified towards treatments that are optimally beneficial, it is a priority to define robust molecular subtypes using clustering methods applied to high-dimensional biological d...

    Authors: Katherine Eason, Gift Nyamundanda and Anguraj Sadanandam

    Citation: BMC Bioinformatics 2018 19:182

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  33. Content type: Software

    Complex microbial communities are an area of growing interest in biology. Metatranscriptomics allows researchers to quantify microbial gene expression in an environmental sample via high-throughput sequencing....

    Authors: Samuel T. Westreich, Michelle L. Treiber, David A. Mills, Ian Korf and Danielle G. Lemay

    Citation: BMC Bioinformatics 2018 19:175

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  34. Content type: Research article

    Learning accurate models from ‘omics data is bringing many challenges due to their inherent high-dimensionality, e.g. the number of gene expression variables, and comparatively lower sample sizes, which leads ...

    Authors: Marta B. Lopes, André Veríssimo, Eunice Carrasquinha, Sandra Casimiro, Niko Beerenwinkel and Susana Vinga

    Citation: BMC Bioinformatics 2018 19:168

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  35. Content type: Software

    Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic t...

    Authors: Alexander S. Kirpich, Miguel Ibarra, Oleksandr Moskalenko, Justin M. Fear, Joseph Gerken, Xinlei Mi, Ali Ashrafi, Alison M. Morse and Lauren M. McIntyre

    Citation: BMC Bioinformatics 2018 19:151

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  36. Content type: Software

    RNA sequencing has become a ubiquitous technology used throughout life sciences as an effective method of measuring RNA abundance quantitatively in tissues and cells. The increase in use of RNA-seq technology ...

    Authors: MacIntosh Cornwell, Mahesh Vangala, Len Taing, Zachary Herbert, Johannes Köster, Bo Li, Hanfei Sun, Taiwen Li, Jian Zhang, Xintao Qiu, Matthew Pun, Rinath Jeselsohn, Myles Brown, X. Shirley Liu and Henry W. Long

    Citation: BMC Bioinformatics 2018 19:135

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2018 Journal Metrics

  • Citation Impact
    2.511 - 2-year Impact Factor
    2.970 - 5-year Impact Factor
    0.855 - Source Normalized Impact per Paper (SNIP)
    1.374 - SCImago Journal Rank (SJR)


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