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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.

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  1. Content type: Methodology Article

    In order to better understand complex diseases, it is important to understand how genetic variation in the regulatory regions affects gene expression. Genetic variants found in these regulatory regions have be...

    Authors: Chaitanya R. Acharya, Janice M. McCarthy, Kouros Owzar and Andrew S. Allen

    Citation: BMC Bioinformatics 2016 17:257

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  2. Content type: Methodology article

    The inference of gene regulatory networks (GRNs) from transcriptional expression profiles is challenging, predominantly due to its underdetermined nature. One important consequence of underdetermination is the...

    Authors: S.M. Minhaz Ud-Dean, Sandra Heise, Steffen Klamt and Rudiyanto Gunawan

    Citation: BMC Bioinformatics 2016 17:252

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  3. Content type: Methodology article

    Integrative analysis of multi-omics data is becoming increasingly important to unravel functional mechanisms of complex diseases. However, the currently available multi-omics datasets inevitably suffer from mi...

    Authors: Dongdong Lin, Jigang Zhang, Jingyao Li, Chao Xu, Hong-Wen Deng and Yu-Ping Wang

    Citation: BMC Bioinformatics 2016 17:247

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  4. Content type: Research Article

    An exponential growth of high-throughput biological information and data has occurred in the past decade, supported by technologies, such as microarrays and RNA-Seq. Most data generated using such methods are ...

    Authors: Arnav Kapur, Kshitij Marwah and Gil Alterovitz

    Citation: BMC Bioinformatics 2016 17:243

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  5. Content type: Methodology Article

    Single-cell technologies make it possible to quantify the comprehensive states of individual cells, and have the power to shed light on cellular differentiation in particular. Although several methods have bee...

    Authors: Hirotaka Matsumoto and Hisanori Kiryu

    Citation: BMC Bioinformatics 2016 17:232

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  6. Content type: Research Article

    Discovery of microRNAs (miRNAs) relies on predictive models for characteristic features from miRNA precursors (pre-miRNAs). The short length of miRNA genes and the lack of pronounced sequence features complica...

    Authors: Ivani de O. N. Lopes, Alexander Schliep and André P. de L. F. de Carvalho

    Citation: BMC Bioinformatics 2016 17:224

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  7. Content type: Methodology Article

    Gene expression connectivity mapping has gained much popularity recently with a number of successful applications in biomedical research testifying its utility and promise. Previously methodological research i...

    Authors: Qing Wen, Chang-Sik Kim, Peter W. Hamilton and Shu-Dong Zhang

    Citation: BMC Bioinformatics 2016 17:211

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  8. Content type: Software

    Gene expression connectivity mapping has proven to be a powerful and flexible tool for research. Its application has been shown in a broad range of research topics, most commonly as a means of identifying pote...

    Authors: Paul G. O’Reilly, Qing Wen, Peter Bankhead, Philip D. Dunne, Darragh G. McArt, Suzanne McPherson, Peter W. Hamilton, Ken I. Mills and Shu-Dong Zhang

    Citation: BMC Bioinformatics 2016 17:198

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  9. Content type: Methodology Article

    RNA-Sequencing (RNA-seq) experiments have been popularly applied to transcriptome studies in recent years. Such experiments are still relatively costly. As a result, RNA-seq experiments often employ a small nu...

    Authors: Ran Bi and Peng Liu

    Citation: BMC Bioinformatics 2016 17:146

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  10. Content type: Research Article

    Several techniques have been tailored to the quantification of microRNA expression, including hybridization arrays, quantitative PCR (qPCR), and high-throughput sequencing. Each of these has certain strengths ...

    Authors: Matthew N. McCall, Alexander S. Baras, Alexander Crits-Christoph, Roxann Ingersoll, Melissa A. McAlexander, Kenneth W. Witwer and Marc K. Halushka

    Citation: BMC Bioinformatics 2016 17:138

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  11. Content type: Methodology Article

    Confounding due to cellular heterogeneity represents one of the foremost challenges currently facing Epigenome-Wide Association Studies (EWAS). Statistical methods leveraging the tissue-specificity of DNA meth...

    Authors: Devin C. Koestler, Meaghan J. Jones, Joseph Usset, Brock C. Christensen, Rondi A. Butler, Michael S. Kobor, John K. Wiencke and Karl T. Kelsey

    Citation: BMC Bioinformatics 2016 17:120

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  12. Content type: Research Article

    To facilitate advances in personalized medicine, it is important to detect predictive, stable and interpretable biomarkers related with different clinical characteristics. These clinical characteristics may be...

    Authors: Meng-Yun Wu, Xiao-Fei Zhang, Dao-Qing Dai, Le Ou-Yang, Yuan Zhu and Hong Yan

    Citation: BMC Bioinformatics 2016 17:108

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  13. Content type: Research article

    High-throughput RNA-Sequencing (RNA-Seq) has become the preferred technique for studying gene expression differences between biological samples and for discovering novel isoforms, though the techniques to anal...

    Authors: Claire R. Williams, Alyssa Baccarella, Jay Z. Parrish and Charles C. Kim

    Citation: BMC Bioinformatics 2016 17:103

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  14. Content type: Research Article

    Often researchers are interested in comparing multiple experimental groups (e.g. tumor size) with a reference group (e.g. normal tissue) on the basis of thousands of features (e.g. genes) and determine if a di...

    Authors: Anjana Grandhi, Wenge Guo and Shyamal D. Peddada

    Citation: BMC Bioinformatics 2016 17:104

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  15. Content type: Methodology article

    Accurate detection of homologous relationships of biological sequences (DNA or amino acid) amongst organisms is an important and often difficult task that is essential to various evolutionary studies, ranging ...

    Authors: M. Stanley Fujimoto, Anton Suvorov, Nicholas O. Jensen, Mark J. Clement and Seth M. Bybee

    Citation: BMC Bioinformatics 2016 17:101

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  16. Content type: Software

    The regulation of gene expression in eukaryotic cells is a complex process that involves epigenetic modifications and the interaction of DNA with multiple transcription factors. This process can be studied wit...

    Authors: Marcin Piechota, Michal Korostynski, Joanna Ficek, Andrzej Tomski and Ryszard Przewlocki

    Citation: BMC Bioinformatics 2016 17:85

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  17. Content type: Methodology Article

    It has been shown that a random-effects framework can be used to test the association between a gene’s expression level and the number of DNA copies of a set of genes. This gene-set modelling framework was lat...

    Authors: Renée X. Menezes, Leila Mohammadi, Jelle J. Goeman and Judith M. Boer

    Citation: BMC Bioinformatics 2016 17:77

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  18. Content type: Methodology article

    Repositioning approved drug and small molecules in novel therapeutic areas is of key interest to the pharmaceutical industry. A number of promising computational techniques have been developed to aid in reposi...

    Authors: Adam S. Brown, Sek Won Kong, Isaac S. Kohane and Chirag J. Patel

    Citation: BMC Bioinformatics 2016 17:78

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  19. Content type: Software

    Many tools exist in the analysis of bacterial RNA sequencing (RNA-seq) transcriptional profiling experiments to identify differentially expressed genes between experimental conditions. Generally, the workflow ...

    Authors: Benjamin K. Johnson, Matthew B. Scholz, Tracy K. Teal and Robert B. Abramovitch

    Citation: BMC Bioinformatics 2016 17:66

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  20. Content type: Methodology article

    Stored biological samples with pathology information and medical records are invaluable resources for translational medical research. However, RNAs extracted from the archived clinical tissues are often substa...

    Authors: Liguo Wang, Jinfu Nie, Hugues Sicotte, Ying Li, Jeanette E. Eckel-Passow, Surendra Dasari, Peter T. Vedell, Poulami Barman, Liewei Wang, Richard Weinshiboum, Jin Jen, Haojie Huang, Manish Kohli and Jean-Pierre A. Kocher

    Citation: BMC Bioinformatics 2016 17:58

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  21. Content type: Methodology Article

    Consider the problem of designing a panel of complex biomarkers to predict a patient’s health or disease state when one can pair his or her current test sample, called a target sample, with the patient’s previ...

    Authors: Tzu-Yu Liu, Thomas Burke, Lawrence P. Park, Christopher W. Woods, Aimee K. Zaas, Geoffrey S. Ginsburg and Alfred O. Hero

    Citation: BMC Bioinformatics 2016 17:47

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  22. Content type: Database

    One of our goals for the echinoderm tree of life project (http://​echinotol.​org) is to identify orthologs suitable for phylogenetic analysis from next-g...

    Authors: Daniel A. Janies, Zach Witter, Gregorio V. Linchangco, David W. Foltz, Allison K. Miller, Alexander M. Kerr, Jeremy Jay, Robert W. Reid and Gregory A. Wray

    Citation: BMC Bioinformatics 2016 17:48

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  23. Content type: Software

    Enrichment analysis of gene expression data is essential to find functional groups of genes whose interplay can explain experimental observations. Numerous methods have been published that either ignore (set-b...

    Authors: Ludwig Geistlinger, Gergely Csaba and Ralf Zimmer

    Citation: BMC Bioinformatics 2016 17:45

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  24. Content type: Software

    Technical advances in Next Generation Sequencing (NGS) provide a means to acquire deeper insights into cellular functions. The lack of standardized and automated methodologies poses a challenge for the analysi...

    Authors: Markus Wolfien, Christian Rimmbach, Ulf Schmitz, Julia Jeannine Jung, Stefan Krebs, Gustav Steinhoff, Robert David and Olaf Wolkenhauer

    Citation: BMC Bioinformatics 2016 17:21

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  25. Content type: Database

    The Pacific oyster, Crassostrea gigas, is one of the most important aquaculture shellfish resources worldwide. Important efforts have been undertaken towards a better knowledge of its genome and transcriptome, wh...

    Authors: Guillaume Riviere, Christophe Klopp, Nabihoudine Ibouniyamine, Arnaud Huvet, Pierre Boudry and Pascal Favrel

    Citation: BMC Bioinformatics 2015 16:401

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  26. Content type: Research article

    Genomic data production is at its highest level and continues to increase, making available novel primary data and existing public data to researchers for exploration. Here we explore the consequences of “batc...

    Authors: Andrew E. Jaffe, Thomas Hyde, Joel Kleinman, Daniel R. Weinbergern, Joshua G. Chenoweth, Ronald D. McKay, Jeffrey T. Leek and Carlo Colantuoni

    Citation: BMC Bioinformatics 2015 16:372

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    The Erratum to this article has been published in BMC Bioinformatics 2016 17:302

  27. Content type: Methodology Article

    The high-throughput sequencing technology, RNA-Seq, has been widely used to quantify gene and isoform expression in the study of transcriptome in recent years. Accurate expression measurement from the millions...

    Authors: Xuejun Liu, Xinxin Shi, Chunlin Chen and Li Zhang

    Citation: BMC Bioinformatics 2015 16:332

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  28. Content type: Research Article

    In the past decade, the identification of gene co-expression has become a routine part of the analysis of high-dimensional microarray data. Gene co-expression, which is mostly detected via the Pearson correlat...

    Authors: Saskia Freytag, Johann Gagnon-Bartsch, Terence P. Speed and Melanie Bahlo

    Citation: BMC Bioinformatics 2015 16:309

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  29. Content type: Methodology article

    This study addresses a recurrent biological problem, that is to define a formal clustering structure for a set of tissues on the basis of the relative abundance of multiple alternatively spliced isoforms mRNAs...

    Authors: Michele Pelosi, Marco Alfò, Francesca Martella, Elisa Pappalardo and Antonio Musarò

    Citation: BMC Bioinformatics 2015 16:289

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  30. Content type: Research article

    RNA-seq has been widely used for genome-wide expression profiling. RNA-seq data typically consists of tens of millions of short sequenced reads from different transcripts. However, due to sequence similarity a...

    Authors: Soohyun Lee, Chae Hwa Seo, Burak Han Alver, Sanghyuk Lee and Peter J. Park

    Citation: BMC Bioinformatics 2015 16:278

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  31. Content type: Methodology Article

    Gene set analysis (GSA) of gene expression data can be highly powerful when the biological signal is weak compared to other sources of variability in the data. However, many gene set analysis approaches utiliz...

    Authors: Jacob A. Turner, Christopher R. Bolen and Derek M. Blankenship

    Citation: BMC Bioinformatics 2015 16:272

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  32. Content type: Research Article

    Multiple high-throughput molecular profiling by omics technologies can be collected for the same individuals. Combining these data, rather than exploiting them separately, can significantly increase the power ...

    Authors: Angela Serra, Michele Fratello, Vittorio Fortino, Giancarlo Raiconi, Roberto Tagliaferri and Dario Greco

    Citation: BMC Bioinformatics 2015 16:261

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  33. Content type: Research Article

    Detecting and quantifying isoforms from RNA-seq data is an important but challenging task. The problem is often ill-posed, particularly at low coverage. One promising direction is to exploit several samples si...

    Authors: Elsa Bernard, Laurent Jacob, Julien Mairal, Eric Viara and Jean-Philippe Vert

    Citation: BMC Bioinformatics 2015 16:262

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  34. Content type: Methodology Article

    Tumorigenesis is an evolutionary process by which tumor cells acquire mutations through successive diversification and differentiation. There is much interest in reconstructing this process of evolution due to...

    Authors: Theodore Roman, Amir Nayyeri, Brittany Terese Fasy and Russell Schwartz

    Citation: BMC Bioinformatics 2015 16:254

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  35. Content type: Methodology Article

    Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluati...

    Authors: Fang Yu, Ming-Hui Chen, Lynn Kuo, Heather Talbott and John S. Davis

    Citation: BMC Bioinformatics 2015 16:245

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  36. Content type: Software

    Gene expression microarrays measure the levels of messenger ribonucleic acid (mRNA) in a sample using probe sequences that hybridize with transcribed regions. These probe sequences are designed using a referen...

    Authors: David Quigley

    Citation: BMC Bioinformatics 2015 16:238

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  37. Content type: Software

    Global run-on coupled with deep sequencing (GRO-seq) provides extensive information on the location and function of coding and non-coding transcripts, including primary microRNAs (miRNAs), long non-coding RNAs...

    Authors: Minho Chae, Charles G. Danko and W. Lee Kraus

    Citation: BMC Bioinformatics 2015 16:222

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  38. Content type: Methodology Article

    Clinical data, such as patient history, laboratory analysis, ultrasound parameters-which are the basis of day-to-day clinical decision support-are often used to guide the clinical management of cancer in the p...

    Authors: Minta Thomas, Kris De Brabanter, Johan AK Suykens and Bart De Moor

    Citation: BMC Bioinformatics 2014 15:411

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  39. Content type: Research article

    Transcriptional hotspots are defined as genomic regions bound by multiple factors. They have been identified recently as cell type specific enhancers regulating developmentally essential genes in many species ...

    Authors: Anagha Joshi

    Citation: BMC Bioinformatics 2014 15:412

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2017 Journal Metrics

  • Citation Impact
    2.213 - 2-year Impact Factor
    3.114 - 5-year Impact Factor
    0.878 - Source Normalized Impact per Paper (SNIP)
    1.479 - SCImago Journal Rank (SJR)


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