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BMC Bioinformatics

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: 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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  2. 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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  3. 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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  4. 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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  5. 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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  6. 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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  7. 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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  8. 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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  9. 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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  10. 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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  11. 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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  12. 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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2016 Journal Metrics

  • Citation Impact
    2.448 - 2-year Impact Factor
    3.450 - 5-year Impact Factor
    0.946 - Source Normalized Impact per Paper (SNIP)
    1.467 - SCImago Journal Rank (SJR)

    1405 Usage Factor

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