004 Datenverarbeitung; Informatik
Refine
Has Fulltext
- yes (10)
Is part of the Bibliography
- yes (10)
Year of publication
- 2016 (10) (remove)
Document Type
- Journal article (6)
- Jahresbericht (2)
- Doctoral Thesis (2)
Keywords
- Computer Center University of Wuerzburg (2)
- Jahresbericht (2)
- annual report (2)
- database (2)
- Fehlertoleranz (1)
- Graphenzeichnen (1)
- Julius-Maximilians-Universität Würzburg. Rechenzentrum (1)
- Kleinsatellit (1)
- Kreuzung (1)
- Miniaturisierung (1)
- Modularität (1)
- Picosatellite (1)
- RZUW (1)
- Rechenzentrum Universität Würzburg (1)
- Satellit (1)
- Winkel (1)
- adaptation models (1)
- aerodynamics (1)
- angular schematization (1)
- boundary labeling (1)
- contact representation (1)
- distributed control (1)
- drug-minded protein (1)
- educational tool (1)
- formation flight (1)
- graph drawing (1)
- immersive classroom (1)
- immersive classroom management (1)
- independent crossing (1)
- intelligent vehicles (1)
- invasive vascular interventions (1)
- mathematical model (1)
- model following (1)
- monotone drawing (1)
- quadcopter (1)
- right angle crossing (1)
- robustness (1)
- rotors (1)
- scalable quadcopter (1)
- simulation system (1)
- simultaneous embedding (1)
- smooth orthogonal drawing (1)
- student simulation (1)
- unmanned aerial vehicle (1)
- v (1)
- vehicle dynamics (1)
- virtual agent interaction (1)
- virtual reality training (1)
- word clouds (1)
Institute
RNA sequencing (RNA-seq) has become a powerful tool to understand molecular mechanisms and/or developmental programs. It provides a fast, reliable and cost-effective method to access sets of expressed elements in a qualitative and quantitative manner. Especially for non-model organisms and in absence of a reference genome, RNA-seq data is used to reconstruct and quantify transcriptomes at the same time. Even SNPs, InDels, and alternative splicing events are predicted directly from the data without having a reference genome at hand. A key challenge, especially for non-computational personnal, is the management of the resulting datasets, consisting of different data types and formats. Here, we present TBro, a flexible de novo transcriptome browser, tackling this challenge. TBro aggregates sequences, their annotation, expression levels as well as differential testing results. It provides an easy-to-use interface to mine the aggregated data and generate publication-ready visualizations. Additionally, it supports users with an intuitive cart system, that helps collecting and analysing biological meaningful sets of transcripts. TBro’s modular architecture allows easy extension of its functionalities in the future. Especially, the integration of new data types such as proteomic quantifications or array-based gene expression data is straightforward. Thus, TBro is a fully featured yet flexible transcriptome browser that supports approaching complex biological questions and enhances collaboration of numerous researchers.