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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. Large-scale accumulation of omics data poses a pressing challenge of integrative analysis of multiple data sets in bioinformatics. An open question of such integrative analysis is how to pinpoint consistent bu...

    Authors: Xin-Ping Xie, Yu-Feng Xie and Hong-Qiang Wang

    Citation: BMC Bioinformatics 2017 18:375

    Content type: Research Article

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  2. MicroRNAs carry out post-transcriptional gene regulation in animals by binding to the 3' untranslated regions of mRNAs, causing their degradation or translational repression. MicroRNAs influence many biologica...

    Authors: Daniel Amsel, Andreas Vilcinskas and André Billion

    Citation: BMC Bioinformatics 2017 18:359

    Content type: Research Article

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  3. Personalizing treatment regimes based on gene expression profiles of individual tumors will facilitate management of cancer. Although many methods have been developed to identify pathways perturbed in tumors, ...

    Authors: Michael I. Klein, David F. Stern and Hongyu Zhao

    Citation: BMC Bioinformatics 2017 18:317

    Content type: Research Article

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  4. Given the development of high-throughput experimental techniques, an increasing number of whole genome transcription profiling time series data sets, with good temporal resolution, are becoming available to re...

    Authors: Giorgos Minas, Hiroshi Momiji, Dafyd J. Jenkins, Maria J. Costa, David A. Rand and Bärbel Finkenstädt

    Citation: BMC Bioinformatics 2017 18:316

    Content type: Software

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  5. Distance based unsupervised clustering of gene expression data is commonly used to identify heterogeneity in biologic samples. However, high noise levels in gene expression data and relatively high correlation...

    Authors: Xiting Yan, Anqi Liang, Jose Gomez, Lauren Cohn, Hongyu Zhao and Geoffrey L. Chupp

    Citation: BMC Bioinformatics 2017 18:309

    Content type: Methodology Article

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  6. The availability of fast alignment-free algorithms has greatly reduced the computational burden of RNA-seq processing, especially for relatively poorly assembled genomes. Using these approaches, previous RNA-s...

    Authors: Stephen J. Bush, Mary E. B. McCulloch, Kim M. Summers, David A. Hume and Emily L. Clark

    Citation: BMC Bioinformatics 2017 18:301

    Content type: Methodology Article

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  7. Despite advances in the gene-set enrichment analysis methods; inadequate definitions of gene-sets cause a major limitation in the discovery of novel biological processes from the transcriptomic datasets. Typic...

    Authors: Atif Khan, Dejan Katanic and Juilee Thakar

    Citation: BMC Bioinformatics 2017 18:295

    Content type: Research Article

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  8. Quantitative molecular biology remains a challenge for researchers due to inconsistent approaches for control of errors in the final results. Due to several factors that can influence the final result, quantit...

    Authors: Špela Baebler, Miha Svalina, Marko Petek, Katja Stare, Ana Rotter, Maruša Pompe-Novak and Kristina Gruden

    Citation: BMC Bioinformatics 2017 18:276

    Content type: Software

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  9. Alternative gene splicing is a common phenomenon in which a single gene gives rise to multiple transcript isoforms. The process is strictly guided and involves a multitude of proteins and regulatory complexes....

    Authors: Marijke Van Moerbeke, Adetayo Kasim, Willem Talloen, Joke Reumers, Hinrick W. H. Göhlmann and Ziv Shkedy

    Citation: BMC Bioinformatics 2017 18:273

    Content type: Methodology Article

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  10. Exponentially increasing numbers of NGS-based epigenomic datasets in public repositories like GEO constitute an enormous source of information that is invaluable for integrative and comparative studies of gene...

    Authors: Mohamed-Ashick M. Saleem, Marco-Antonio Mendoza-Parra, Pierre-Etienne Cholley, Matthias Blum and Hinrich Gronemeyer

    Citation: BMC Bioinformatics 2017 18:259

    Content type: Methodology Article

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  11. There exist many methods for describing the complex relation between changes of gene expression in molecular pathways or gene ontologies under different experimental conditions. Among them, Gene Set Enrichment...

    Authors: Joanna Zyla, Michal Marczyk, January Weiner and Joanna Polanska

    Citation: BMC Bioinformatics 2017 18:256

    Content type: Research Article

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  12. A major challenge of high throughput transcriptome studies is presenting the data to researchers in an interpretable format. In many cases, the outputs of such studies are gene lists which are then examined fo...

    Authors: Liang Sun, Yongnan Zhu, A. S. M. Ashique Mahmood, Catalina O. Tudor, Jia Ren, K. Vijay-Shanker, Jian Chen and Carl J. Schmidt

    Citation: BMC Bioinformatics 2017 18:237

    Content type: Software

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  13. Sample size calculation and power estimation are essential components of experimental designs in biomedical research. It is very challenging to estimate power for RNA-Seq differential expression under complex ...

    Authors: Lianbo Yu, Soledad Fernandez and Guy Brock

    Citation: BMC Bioinformatics 2017 18:234

    Content type: Methodology Article

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  14. Reconstructing transcript models from RNA-sequencing (RNA-seq) data and establishing these as independent transcriptional units can be a challenging task. Current state-of-the-art tools for long non-coding RNA...

    Authors: Francisco Avila Cobos, Jasper Anckaert, Pieter-Jan Volders, Celine Everaert, Dries Rombaut, Jo Vandesompele, Katleen De Preter and Pieter Mestdagh

    Citation: BMC Bioinformatics 2017 18:231

    Content type: Methodology Article

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  15. MicroRNAs always function cooperatively in their regulation of gene expression. Dysfunctions of these co-functional microRNAs can play significant roles in disease development. We are interested in those multi...

    Authors: Hui Peng, Chaowang Lan, Yi Zheng, Gyorgy Hutvagner, Dacheng Tao and Jinyan Li

    Citation: BMC Bioinformatics 2017 18:193

    Content type: Research Article

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  16. The unveiling of long non-coding RNAs as important gene regulators in many biological contexts has increased the demand for efficient and robust computational methods to identify novel long non-coding RNAs fro...

    Authors: Giovanna M. M. Ventola, Teresa M. R. Noviello, Salvatore D’Aniello, Antonietta Spagnuolo, Michele Ceccarelli and Luigi Cerulo

    Citation: BMC Bioinformatics 2017 18:187

    Content type: Research Article

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  17. Genome-wide miRNA expression data can be used to study miRNA dysregulation comprehensively. Although many open-source tools for microRNA (miRNA)-seq data analyses are available, challenges remain in accurate m...

    Authors: Shanrong Zhao, William Gordon, Sarah Du, Chi Zhang, Wen He, Li Xi, Sachin Mathur, Michael Agostino, Theresa Paradis, David von Schack, Michael Vincent and Baohong Zhang

    Citation: BMC Bioinformatics 2017 18:180

    Content type: Software

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  18. Phenotypic studies in Triticeae have shown that low temperature-induced protective mechanisms are developmentally regulated and involve dynamic acclimation processes. Understanding these mechanisms is importan...

    Authors: Alain B. Tchagang, François Fauteux, Dan Tulpan and Youlian Pan

    Citation: BMC Bioinformatics 2017 18:174

    Content type: Research article

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  19. The purpose of gene set enrichment analysis (GSEA) is to find general trends in the huge lists of genes or proteins generated by many functional genomics techniques and bioinformatics analyses.

    Authors: Cedric Simillion, Robin Liechti, Heidi E.L. Lischer, Vassilios Ioannidis and Rémy Bruggmann

    Citation: BMC Bioinformatics 2017 18:151

    Content type: Methodology article

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  20. A family of parsimonious Gaussian mixture models for the biclustering of gene expression data is introduced. Biclustering is accommodated by adopting a mixture of factor analyzers model with a binary, row-stoc...

    Authors: Monica H. T. Wong, David M. Mutch and Paul D. McNicholas

    Citation: BMC Bioinformatics 2017 18:150

    Content type: Methodology Article

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  21. Recent studies illuminated a novel role of microRNA (miRNA) in the competing endogenous RNA (ceRNA) interaction: two genes (ceRNAs) can achieve coexpression by competing for a pool of common targeting miRNAs. ...

    Authors: Yu-Chiao Chiu, Li-Ju Wang, Tzu-Pin Lu, Tzu-Hung Hsiao, Eric Y. Chuang and Yidong Chen

    Citation: BMC Bioinformatics 2017 18:132

    Content type: Research article

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  22. Molecular signatures identified from high-throughput transcriptomic studies often have poor reliability and fail to reproduce across studies. One solution is to combine independent studies into a single integr...

    Authors: Florian Rohart, Aida Eslami, Nicholas Matigian, Stéphanie Bougeard and Kim-Anh Lê Cao

    Citation: BMC Bioinformatics 2017 18:128

    Content type: Methodology Article

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  23. Alternative splicing is an important cellular mechanism that can be analyzed by RNA sequencing. However, identification of splicing events in an automated fashion is error-prone. Thus, further validation is re...

    Authors: Matthias Barann, Ralf Zimmer and Fabian Birzele

    Citation: BMC Bioinformatics 2017 18:120

    Content type: Software

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  24. Orthology characterizes genes of different organisms that arose from a single ancestral gene via speciation, in contrast to paralogy, which is assigned to genes that arose via gene duplication. An accurate ort...

    Authors: Malte Petersen, Karen Meusemann, Alexander Donath, Daniel Dowling, Shanlin Liu, Ralph S. Peters, Lars Podsiadlowski, Alexandros Vasilikopoulos, Xin Zhou, Bernhard Misof and Oliver Niehuis

    Citation: BMC Bioinformatics 2017 18:111

    Content type: Software

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  25. Next-generation sequencing technologies have greatly increased our ability to identify gene expression levels, including at specific developmental stages and in specific tissues. Gene expression data can help ...

    Authors: Yanhui Hu, Aram Comjean, Norbert Perrimon and Stephanie E. Mohr

    Citation: BMC Bioinformatics 2017 18:98

    Content type: Research article

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  26. Next generation sequencing provides a count of RNA molecules in the form of short reads, yielding discrete, often highly non-normally distributed gene expression measurements. Although Negative Binomial (NB) r...

    Authors: Seung Hoan Choi, Adam T. Labadorf, Richard H. Myers, Kathryn L. Lunetta, Josée Dupuis and Anita L. DeStefano

    Citation: BMC Bioinformatics 2017 18:91

    Content type: Methodology article

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  27. Biclustering has been largely applied for the unsupervised analysis of biological data, being recognised today as a key technique to discover putative modules in both expression data (subsets of genes correlat...

    Authors: Rui Henriques, Francisco L. Ferreira and Sara C. Madeira

    Citation: BMC Bioinformatics 2017 18:82

    Content type: Software

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    The Erratum to this article has been published in BMC Bioinformatics 2017 18:162

  28. The Friedman rank sum test is a widely-used nonparametric method in computational biology. In addition to examining the overall null hypothesis of no significant difference among any of the rank sums, it is ty...

    Authors: Rob Eisinga, Tom Heskes, Ben Pelzer and Manfred Te Grotenhuis

    Citation: BMC Bioinformatics 2017 18:68

    Content type: Methodology article

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  29. RNA-Seq has supplanted microarrays as the preferred method of transcriptome-wide identification of differentially expressed genes. However, RNA-Seq analysis is still rapidly evolving, with a large number of to...

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

    Citation: BMC Bioinformatics 2017 18:38

    Content type: Research article

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  30. The analysis of microarray time series promises a deeper insight into the dynamics of the cellular response following stimulation. A common observation in this type of data is that some genes respond with quic...

    Authors: Marco Albrecht, Damian Stichel, Benedikt Müller, Ruth Merkle, Carsten Sticht, Norbert Gretz, Ursula Klingmüller, Kai Breuhahn and Franziska Matthäus

    Citation: BMC Bioinformatics 2017 18:33

    Content type: Methodology Article

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  31. Performing statistical tests is an important step in analyzing genome-wide datasets for detecting genomic features differentially expressed between conditions. Each type of statistical test has its own advanta...

    Authors: Yuanzhe Bei and Pengyu Hong

    Citation: BMC Bioinformatics 2016 17:541

    Content type: Methodology article

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  32. Competitive gene set analysis is a standard exploratory tool for gene expression data. Permutation-based competitive gene set analysis methods are preferable to parametric ones because the latter make strong s...

    Authors: Pashupati P. Mishra, Alan Medlar, Liisa Holm and Petri Törönen

    Citation: BMC Bioinformatics 2016 17:526

    Content type: Research Article

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  33. Next-generation sequencing (NGS) technologies are arguably the most revolutionary technical development to join the list of tools available to molecular biologists since PCR. For researchers working with nonco...

    Authors: Nicolas Cerveau and Daniel J. Jackson

    Citation: BMC Bioinformatics 2016 17:525

    Content type: Methodology article

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  34. Increased emphasis on reproducibility of published research in the last few years has led to the large-scale archiving of sequencing data. While this data can, in theory, be used to reproduce results in papers...

    Authors: Harold Pimentel, Pascal Sturmfels, Nicolas Bray, Páll Melsted and Lior Pachter

    Citation: BMC Bioinformatics 2016 17:490

    Content type: Database

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  35. Active protein translation can be assessed and measured using ribosome profiling sequencing strategies. Prevailing analytical approaches applied to this technology make use of sequence fragment length profilin...

    Authors: Sang Y. Chun, Caitlin M. Rodriguez, Peter K. Todd and Ryan E. Mills

    Citation: BMC Bioinformatics 2016 17:482

    Content type: Software

    Published on:

  36. Genome-wide gene expression profiling of mammalian cells is becoming a staple of many published biomedical and biological research studies. Such data is deposited into data repositories such as the Gene Expres...

    Authors: Gregory W. Gundersen, Kathleen M. Jagodnik, Holly Woodland, Nicholas F. Fernandez, Kevin Sani, Anders B. Dohlman, Peter Man-Un Ung, Caroline D. Monteiro, Avner Schlessinger and Avi Ma’ayan

    Citation: BMC Bioinformatics 2016 17:461

    Content type: Software

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  37. Binding of transcription factors to transcription factor binding sites (TFBSs) is key to the mediation of transcriptional regulation. Information on experimentally validated functional TFBSs is limited and con...

    Authors: Narayan Jayaram, Daniel Usvyat and Andrew C. R. Martin

    Citation: BMC Bioinformatics 2016 17:547

    Content type: Research Article

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2019 Journal Metrics

  • Citation Impact
    3.242 - 2-year Impact Factor
    3.213 - 5-year Impact Factor
    1.156 - Source Normalized Impact per Paper (SNIP)
    1.626 - SCImago Journal Rank (SJR)

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