Skip to main content

Advertisement

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 9 of 10

  1. Patterns of genome-wide methylation vary between tissue types. For example, cancer tissue shows markedly different patterns from those of normal tissue. In this paper we propose a beta-mixture model to describ...

    Authors: Kirsti Laurila, Bodil Oster, Claus L Andersen, Philippe Lamy, Torben Orntoft, Olli Yli-Harja and Carsten Wiuf

    Citation: BMC Bioinformatics 2011 12:215

    Content type: Research article

    Published on:

  2. Studies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relati...

    Authors: Roger S Day, Kevin K McDade, Uma R Chandran, Alex Lisovich, Thomas P Conrads, Brian L Hood, VS Kumar Kolli, David Kirchner, Traci Litzi and G Larry Maxwell

    Citation: BMC Bioinformatics 2011 12:213

    Content type: Methodology article

    Published on:

  3. A key objective in many microarray association studies is the identification of individual genes associated with clinical outcome. It is often of additional interest to identify sets of genes, known a priori t...

    Authors: Insuk Sohn, Kouros Owzar, Johan Lim, Stephen L George, Stephanie Mackey Cushman and Sin-Ho Jung

    Citation: BMC Bioinformatics 2011 12:209

    Content type: Methodology article

    Published on:

  4. The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which...

    Authors: Alfredo A Kalaitzis and Neil D Lawrence

    Citation: BMC Bioinformatics 2011 12:180

    Content type: Research article

    Published on:

  5. A major challenge in genomic research is identifying significant biological processes and generating new hypotheses from large gene sets. Gene sets often consist of multiple separate biological pathways, contr...

    Authors: Mitja I Kurki, Jussi Paananen, Markus Storvik, Seppo Ylä-Herttuala, Juha E Jääskeläinen, Mikael von und zu Fraunberg, Garry Wong and Petri Pehkonen

    Citation: BMC Bioinformatics 2011 12:171

    Content type: Methodology article

    Published on:

  6. Gene expression is regulated at both the DNA sequence level and through modification of chromatin. However, the effect of chromatin on tissue/cell-type specific gene regulation (TCSR) is largely unknown. In th...

    Authors: Zhihua Zhang and Michael Q Zhang

    Citation: BMC Bioinformatics 2011 12:155

    Content type: Research article

    Published on:

  7. Chromatin immunoprecipitation (ChIP), coupled with massively parallel short-read sequencing (seq) is used to probe chromatin dynamics. Although there are many algorithms to call peaks from ChIP-seq datasets, m...

    Authors: Xin Feng, Robert Grossman and Lincoln Stein

    Citation: BMC Bioinformatics 2011 12:139

    Content type: Software

    Published on:

  8. Classification and variable selection play an important role in knowledge discovery in high-dimensional data. Although Support Vector Machine (SVM) algorithms are among the most powerful classification and pre...

    Authors: Natalia Becker, Grischa Toedt, Peter Lichter and Axel Benner

    Citation: BMC Bioinformatics 2011 12:138

    Content type: Methodology article

    Published on:

  9. Microarray technology has become a widely used tool in the biological sciences. Over the past decade, the number of users has grown exponentially, and with the number of applications and secondary data analyse...

    Authors: Matthew N McCall, Peter N Murakami, Margus Lukk, Wolfgang Huber and Rafael A Irizarry

    Citation: BMC Bioinformatics 2011 12:137

    Content type: Methodology article

    Published on:

  10. Probes on a microarray represent a frozen view of a genome and are quickly outdated when new sequencing studies extend our knowledge, resulting in significant measurement error when analyzing any microarray ex...

    Authors: Christopher C Overall, D Andrew Carr, Ehsan S Tabari, Kevin J Thompson and Jennifer W Weller

    Citation: BMC Bioinformatics 2011 12:136

    Content type: Software

    Published on:

  11. Processing cDNA microarray images is a crucial step in gene expression analysis, since any errors in early stages affect subsequent steps, leading to possibly erroneous biological conclusions. When processing ...

    Authors: Luis Rueda and Iman Rezaeian

    Citation: BMC Bioinformatics 2011 12:113

    Content type: Research article

    Published on:

  12. OmniLog™ phenotype microarrays (PMs) have the capability to measure and compare the growth responses of biological samples upon exposure to hundreds of growth conditions such as different metabolites and antib...

    Authors: Wenling E Chang, Keri Sarver, Brandon W Higgs, Timothy D Read, Nichole ME Nolan, Carol E Chapman, Kimberly A Bishop-Lilly and Shanmuga Sozhamannan

    Citation: BMC Bioinformatics 2011 12:109

    Content type: Database

    Published on:

  13. In the last decades, microarray technology has spread, leading to a dramatic increase of publicly available datasets. The first statistical tools developed were focused on the identification of significant dif...

    Authors: Paolo Martini, Davide Risso, Gabriele Sales, Chiara Romualdi, Gerolamo Lanfranchi and Stefano Cagnin

    Citation: BMC Bioinformatics 2011 12:92

    Content type: Methodology article

    Published on:

  14. Advances in biotechnology offer a fast growing variety of high-throughput data for screening molecular activities of genomic, transcriptional, post-transcriptional and translational observations. However, to d...

    Authors: Raffaele Fronza, Michele Tramonti, William R Atchley and Christine Nardini

    Citation: BMC Bioinformatics 2011 12:86

    Content type: Research article

    Published on:

  15. Many different microarray experiments are publicly available today. It is natural to ask whether different experiments for the same phenotypic conditions can be combined using meta-analysis, in order to increa...

    Authors: Fan Shi, Gad Abraham, Christopher Leckie, Izhak Haviv and Adam Kowalczyk

    Citation: BMC Bioinformatics 2011 12:84

    Content type: Methodology article

    Published on:

  16. Gene set enrichment testing has helped bridge the gap from an individual gene to a systems biology interpretation of microarray data. Although gene sets are defined a priori based on biological knowledge, curr...

    Authors: Jun Ma, Maureen A Sartor and HV Jagadish

    Citation: BMC Bioinformatics 2011 12:81

    Content type: Research article

    Published on:

  17. Cross-platform analysis of gene express data requires multiple, intricate processes at different layers with various platforms. However, existing tools handle only a single platform and are not flexible enough...

    Authors: Jihoon Kim, Kiltesh Patel, Hyunchul Jung, Winston P Kuo and Lucila Ohno-Machado

    Citation: BMC Bioinformatics 2011 12:75

    Content type: Software

    Published on:

  18. With the growing availability of entire genome sequences, an increasing number of scientists can exploit oligonucleotide microarrays for genome-scale expression studies. While probe-design is a major research ...

    Authors: Peter Sykacek, David P Kreil, Lisa A Meadows, Richard P Auburn, Bettina Fischer, Steven Russell and Gos Micklem

    Citation: BMC Bioinformatics 2011 12:73

    Content type: Methodology article

    Published on:

  19. Genome-wide expression signatures are emerging as potential marker for overall survival and disease recurrence risk as evidenced by recent commercialization of gene expression based biomarkers in breast cancer...

    Authors: Samir B Amin, Parantu K Shah, Aimin Yan, Sophia Adamia, Stéphane Minvielle, Hervé Avet-Loiseau, Nikhil C Munshi and Cheng Li

    Citation: BMC Bioinformatics 2011 12:72

    Content type: Software

    Published on:

  20. The creation of a complete genome-wide map of transcription factor binding sites is essential for understanding gene regulatory networks in vivo. However, current prediction methods generally rely on statistical ...

    Authors: Jonathon T Hill, Keith R Anderson, Teresa L Mastracci, Klaus H Kaestner and Lori Sussel

    Citation: BMC Bioinformatics 2011 12:62

    Content type: Research article

    Published on:

  21. Multiclass classification of microarray data samples with a reduced number of genes is a rich and challenging problem in Bioinformatics research. The problem gets harder as the number of classes is increased. ...

    Authors: Elizabeth Tapia, Leonardo Ornella, Pilar Bulacio and Laura Angelone

    Citation: BMC Bioinformatics 2011 12:59

    Content type: Methodology article

    Published on:

  22. Alternative splicing (AS) is a process which generates several distinct mRNA isoforms from the same gene by splicing different portions out of the precursor transcript. Due to the (patho-)physiological importa...

    Authors: Johannes Eichner, Georg Zeller, Sascha Laubinger and Gunnar Rätsch

    Citation: BMC Bioinformatics 2011 12:55

    Content type: Research article

    Published on:

  23. DNA methylation has been shown to play an important role in the silencing of tumor suppressor genes in various tumor types. In order to have a system-wide understanding of the methylation changes that occur in...

    Authors: Shuying Sun, Zhengyi Chen, Pearlly S Yan, Yi-Wen Huang, Tim HM Huang and Shili Lin

    Citation: BMC Bioinformatics 2011 12:54

    Content type: Research article

    Published on:

  24. Tumor cells are considered to have an aberrant cell state, and some evidence indicates different development states appearing in the tumorigenesis. Embryonic development and stem cell differentiation are order...

    Authors: Bo Zhang, Beibei Chen, Tao Wu, Zhenyu Xuan, Xiaopeng Zhu and Runsheng Chen

    Citation: BMC Bioinformatics 2011 12:53

    Content type: Methodology article

    Published on:

  25. The Gene Ontology (GO) Consortium organizes genes into hierarchical categories based on biological process, molecular function and subcellular localization. Tools such as GoMiner can leverage GO to perform ont...

    Authors: Barry R Zeeberg, Hongfang Liu, Ari B Kahn, Martin Ehler, Vinodh N Rajapakse, Robert F Bonner, Jacob D Brown, Brian P Brooks, Vladimir L Larionov, William Reinhold, John N Weinstein and Yves G Pommier

    Citation: BMC Bioinformatics 2011 12:52

    Content type: Software

    Published on:

  26. DNA microarrays have become a nearly ubiquitous tool for the study of human disease, and nowhere is this more true than in cancer. With hundreds of studies and thousands of expression profiles representing the...

    Authors: Fenglong Liu, Joseph A White, Corina Antonescu, Daniel Gusenleitner and John Quackenbush

    Citation: BMC Bioinformatics 2011 12:46

    Content type: Database

    Published on:

  27. The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA g...

    Authors: Alexander Herbig and Kay Nieselt

    Citation: BMC Bioinformatics 2011 12:40

    Content type: Research article

    Published on:

  28. Microarray technology allows the analysis of genomic aberrations at an ever increasing resolution, making functional interpretation of these vast amounts of data the main bottleneck in routine implementation o...

    Authors: Geert Vandeweyer, Edwin Reyniers, Wim Wuyts, Liesbeth Rooms and R Frank Kooy

    Citation: BMC Bioinformatics 2011 12:4

    Content type: Software

    Published on:

  29. High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical s...

    Authors: Xiaoliang Sun, Yong Zou, Victoria Nikiforova, Jürgen Kurths and Dirk Walther

    Citation: BMC Bioinformatics 2010 11:607

    Content type: Research article

    Published on:

  30. With the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these re...

    Authors: Jesse M Engreitz, Alexander A Morgan, Joel T Dudley, Rong Chen, Rahul Thathoo, Russ B Altman and Atul J Butte

    Citation: BMC Bioinformatics 2010 11:603

    Content type: Research article

    Published on:

  31. Expression levels for 47294 transcripts in lymphoblastoid cell lines from all 270 HapMap phase II individuals, and genotypes (both HapMap phase II and III) of 3.96 million single nucleotide polymorphisms (SNPs...

    Authors: Kristian Holm, Espen Melum, Andre Franke and Tom H Karlsen

    Citation: BMC Bioinformatics 2010 11:600

    Content type: Software

    Published on:

  32. High-throughput profiling of DNA methylation status of CpG islands is crucial to understand the epigenetic regulation of genes. The microarray-based Infinium methylation assay by Illumina is one platform for l...

    Authors: Pan Du, Xiao Zhang, Chiang-Ching Huang, Nadereh Jafari, Warren A Kibbe, Lifang Hou and Simon M Lin

    Citation: BMC Bioinformatics 2010 11:587

    Content type: Research article

    Published on:

  33. External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes...

    Authors: Andreas Kowarsch, Florian Blöchl, Sebastian Bohl, Maria Saile, Norbert Gretz, Ursula Klingmüller and Fabian J Theis

    Citation: BMC Bioinformatics 2010 11:585

    Content type: Research article

    Published on:

  34. Exon arrays provide a way to measure the expression of different isoforms of genes in an organism. Most of the procedures to deal with these arrays are focused on gene expression or on exon expression. Althoug...

    Authors: Miguel A Anton, Ander Aramburu and Angel Rubio

    Citation: BMC Bioinformatics 2010 11:578

    Content type: Research article

    Published on:

  35. The data from DNA microarrays are increasingly being used in order to understand effects of different conditions, exposures or diseases on the modulation of the expression of various genes in a biological syst...

    Authors: Reuben Thomas, Luis de la Torre, Xiaoqing Chang and Sanjay Mehrotra

    Citation: BMC Bioinformatics 2010 11:576

    Content type: Research article

    Published on:

  36. Recent technological advancements have made high throughput sequencing an increasingly popular approach for transcriptome analysis. Advantages of sequencing-based transcriptional profiling over microarrays hav...

    Authors: Zhijin Wu, Bethany D Jenkins, Tatiana A Rynearson, Sonya T Dyhrman, Mak A Saito, Melissa Mercier and LeAnn P Whitney

    Citation: BMC Bioinformatics 2010 11:564

    Content type: Research article

    Published on:

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)

    Usage 
    4,129,368 downloads

    Social Media Impact
    4446 mentions

Advertisement