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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 9

  1. 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. Content type: Software

    In-depth study of the intron retention levels of transcripts provide insights on the mechanisms regulating pre-mRNA splicing efficiency. Additionally, detailed analysis of retained introns can link these intro...

    Authors: Ali Oghabian, Dario Greco and Mikko J. Frilander

    Citation: BMC Bioinformatics 2018 19:130

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  12. Content type: Software

    The analysis of modular gene co-expression networks is a well-established method commonly used for discovering the systems-level functionality of genes. In addition, these studies provide a basis for the disco...

    Authors: Pedro S. T. Russo, Gustavo R. Ferreira, Lucas E. Cardozo, Matheus C. Bürger, Raul Arias-Carrasco, Sandra R. Maruyama, Thiago D. C. Hirata, Diógenes S. Lima, Fernando M. Passos, Kiyoshi F. Fukutani, Melissa Lever, João S. Silva, Vinicius Maracaja-Coutinho and Helder I. Nakaya

    Citation: BMC Bioinformatics 2018 19:56

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  13. Content type: Software

    Many R packages have been developed for transcriptome analysis but their use often requires familiarity with R and integrating results of different packages requires scripts to wrangle the datatypes. Furthermo...

    Authors: Qin Zhu, Stephen A. Fisher, Hannah Dueck, Sarah Middleton, Mugdha Khaladkar and Junhyong Kim

    Citation: BMC Bioinformatics 2018 19:6

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  14. Content type: Research Article

    Gene expression connectivity mapping has gained much popularity in recent years with a number of successful applications in biomedical research testifying its utility and promise. A major application of connec...

    Authors: Gayathri Thillaiyampalam, Fabio Liberante, Liam Murray, Chris Cardwell, Ken Mills and Shu-Dong Zhang

    Citation: BMC Bioinformatics 2017 18:581

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  15. Content type: Methodology Article

    DNA methylation is an important tissue-specific epigenetic event that influences transcriptional regulation of gene expression. Differentially methylated CpG sites may act as mediators between genetic variatio...

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

    Citation: BMC Bioinformatics 2017 18:455

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  16. Content type: Research Article

    Predicting disease-associated genes is helpful for understanding the molecular mechanisms during the disease progression. Since the pathological mechanisms of neurodegenerative diseases are very complex, tradi...

    Authors: Xue Jiang, Han Zhang, Feng Duan and Xiongwen Quan

    Citation: BMC Bioinformatics 2017 18:447

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  17. Content type: Software

    Although ultrahigh-throughput RNA-Sequencing has become the dominant technology for genome-wide transcriptional profiling, the vast majority of RNA-Seq studies typically profile only tens of samples, and most ...

    Authors: Joseph N. Paulson, Cho-Yi Chen, Camila M. Lopes-Ramos, Marieke L. Kuijjer, John Platig, Abhijeet R. Sonawane, Maud Fagny, Kimberly Glass and John Quackenbush

    Citation: BMC Bioinformatics 2017 18:437

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  18. Content type: Software

    The evolution of next-generation sequencing (NGS) technologies has led to increased focus on RNA-Seq. Many bioinformatic tools have been developed for RNA-Seq analysis, each with unique performance characteris...

    Authors: Jérôme Audoux, Mikaël Salson, Christophe F. Grosset, Sacha Beaumeunier, Jean-Marc Holder, Thérèse Commes and Nicolas Philippe

    Citation: BMC Bioinformatics 2017 18:428

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  19. Content type: Software

    RNA-Seq is currently used routinely, and it provides accurate information on gene transcription. However, the method cannot accurately estimate duplicated genes expression. Several strategies have been previou...

    Authors: Matthias Zytnicki

    Citation: BMC Bioinformatics 2017 18:411

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  20. Content type: Software

    A group of miRNAs can regulate a biological process by targeting genes involved in the process. The unbiased miRNA functional enrichment analysis is the most precise in silico approach to predict the biological p...

    Authors: Konstantinos Zagganas, Thanasis Vergoulis, Maria D. Paraskevopoulou, Ioannis S. Vlachos, Spiros Skiadopoulos and Theodore Dalamagas

    Citation: BMC Bioinformatics 2017 18:399

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  21. Content type: Methodology Article

    As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to...

    Authors: Lian Liu, Shao-Wu Zhang, Yufei Huang and Jia Meng

    Citation: BMC Bioinformatics 2017 18:387

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  22. Content type: Research Article

    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

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  23. Content type: Research Article

    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

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  24. Content type: Software

    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

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  25. Content type: Research Article

    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

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  26. Content type: Methodology Article

    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

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  27. Content type: Methodology Article

    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

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  28. Content type: Research Article

    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

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  29. Content type: Methodology Article

    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

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  30. Content type: Software

    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

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  31. Content type: Research Article

    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

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  32. Content type: Methodology Article

    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

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  33. Content type: Software

    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

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  34. Content type: Methodology Article

    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

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  35. Content type: Methodology Article

    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

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  36. Content type: Research Article

    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

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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)

    Usage 
    4,129,368 downloads

    Social Media Impact
    4446 mentions

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