scholarly journals Mining SAGE data allows large-scale, sensitive screening of antisense transcript expression

2004 ◽  
Vol 32 (20) ◽  
pp. e163-e163 ◽  
Author(s):  
R. Quere
Keyword(s):  
Large Scale ◽  
Antisense Transcript ◽  
Transcript Expression ◽  
Sage Data

Understanding platelets

2005 ◽  
Vol 94 (11) ◽  
pp. 916-925 ◽  
Author(s):  
Marcus Dittrich ◽  
Ingvild Birschmann ◽  
Christiane Stuhlfelder ◽  
Albert Sickmann ◽  
Sabine Herterich ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Large Scale ◽  
Building Blocks ◽  
Clinical Implications ◽  
Scale Analysis ◽  
New Techniques ◽  
Analysis Techniques ◽  
Large Scale Analysis ◽  
Sage Data ◽  
New Framework

SummaryNew large-scale analysis techniques such as bioinformatics, mass spectrometry and SAGE data analysis will allow a new framework for understanding platelets. This review analyses some important options and tasks for these tools and examines an outline of the new, refined picture of the platelet outlined by these new techniques. Looking at the platelet-specific building blocks of genome, (active) transcriptome and proteome (notably secretome and phospho-proteome), we summarize current bioinformatical and biochemical approaches, tasks as well as their limitations. Understanding the surprisingly complex platelet regarding compartmentalization, key cascades, and pathways including clinical implications will remain an exciting and hopefully fruitful challenge for the future.

scholarly journals Magnaporthe grisea Infection Triggers RNA Variation and Antisense Transcript Expression in Rice

2007 ◽  
Vol 144 (1) ◽  
pp. 524-533 ◽  
Author(s):  
Malali Gowda ◽  
R.-C. Venu ◽  
Huameng Li ◽  
Chatchawan Jantasuriyarat ◽  
Songbiao Chen ◽  
...  
Keyword(s):  
Magnaporthe Grisea ◽  
Antisense Transcript ◽  
Transcript Expression

IGF2 antisense transcript expression in porcine postnatal muscle is affected by a quantitative trait nucleotide in intron 3

Genomics ◽  
2004 ◽  
Vol 84 (6) ◽  
pp. 1021-1029 ◽  
Author(s):  
Martin H. Braunschweig ◽  
Anne-Sophie Van Laere ◽  
Nadine Buys ◽  
Leif Andersson ◽  
Göran Andersson
Keyword(s):  
Quantitative Trait ◽  
Antisense Transcript ◽  
Transcript Expression ◽  
Quantitative Trait Nucleotide

scholarly journals P2-175: Tau gene-specific natural antisense transcript expression and splicing in sporadic tauopathies

2008 ◽  
Vol 4 ◽  
pp. T421-T422
Author(s):  
Jana Vandrovcova ◽  
Laura Dunn ◽  
Elke Malzer ◽  
John Hardy ◽  
Rohan de Silva
Keyword(s):  
Antisense Transcript ◽  
Transcript Expression ◽  
Natural Antisense Transcript

scholarly journals Evolution of gene expression levels in the male reproductive organs of Anopheles mosquitoes

2019 ◽  
Vol 2 (1) ◽  
pp. e201800191 ◽  
Author(s):  
Abril Izquierdo ◽  
Martin Fahrenberger ◽  
Tania Persampieri ◽  
Mark Q Benedict ◽  
Tom Giles ◽  
...  
Keyword(s):  
Gene Expression ◽  
Related Species ◽  
Regulatory Networks ◽  
Large Scale ◽  
Evolutionary Rate ◽  
Interaction Analysis ◽  
Expression Patterns ◽  
Transcript Expression ◽  
Closely Related Species ◽  
Expression Levels

Modifications in gene expression determine many of the phenotypic differentiations between closely related species. This is particularly evident in reproductive tissues, where evolution of genes is more rapid, facilitating the appearance of distinct reproductive characteristics which may lead to species isolation and phenotypic variation. Large-scale, comparative analyses of transcript expression levels have been limited until recently by lack of inter-species data mining solutions. Here, by combining expression normalisation across lineages, multivariate statistical analysis, evolutionary rate, and protein–protein interaction analysis, we investigate ortholog transcripts in the male accessory glands and testes across five closely related species in the Anopheles gambiae complex. We first demonstrate that the differentiation by transcript expression is consistent with the known Anopheles phylogeny. Then, through clustering, we discover groups of transcripts with tissue-dependent expression patterns conserved across lineages, or lineage-dependent patterns conserved across tissues. The strongest associations with reproductive function, transcriptional regulatory networks, protein–protein subnetworks, and evolutionary rate are found for the groups of transcripts featuring large expression differences in lineage or tissue-conserved patterns.

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