14795
2016
eng
baw146
2016
article
1
2017-05-05
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TBro: visualization and management of de novo transcriptomes
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.
Database
10.1093/database/baw146
urn:nbn:de:bvb:20-opus-147954
Database, 2016, 1–7 doi: 10.1093/database/baw146
Markus J. Ankenbrand
Lorenz Weber
Dirk Becker
Frank Förster
Felix Bemm
eng
uncontrolled
database
Datenverarbeitung; Informatik
open_access
Theodor-Boveri-Institut für Biowissenschaften
Förderzeitraum 2016
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/14795/Ankenbrand_baw146.pdf
14736
2016
eng
baw041
2016
article
1
2017-04-20
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The drug-minded protein interaction database (DrumPID) for efficient target analysis and drug development
The drug-minded protein interaction database (DrumPID) has been designed to provide fast, tailored information on drugs and their protein networks including indications, protein targets and side-targets. Starting queries include compound, target and protein interactions and organism-specific protein families. Furthermore, drug name, chemical structures and their SMILES notation, affected proteins (potential drug targets), organisms as well as diseases can be queried including various combinations and refinement of searches. Drugs and protein interactions are analyzed in detail with reference to protein structures and catalytic domains, related compound structures as well as potential targets in other organisms. DrumPID considers drug functionality, compound similarity, target structure, interactome analysis and organismic range for a compound, useful for drug development, predicting drug side-effects and structure–activity relationships.
Database
10.1093/database/baw041
urn:nbn:de:bvb:20-opus-147369
Database (2016) Vol. 2016: article ID baw041; doi:10.1093/database/baw041
Meik Kunz
Chunguang Liang
Santosh Nilla
Alexander Cecil
Thomas Dandekar
eng
uncontrolled
drug-minded protein
eng
uncontrolled
database
Datenverarbeitung; Informatik
Biowissenschaften; Biologie
open_access
Theodor-Boveri-Institut für Biowissenschaften
Förderzeitraum 2016
Universität Würzburg
https://opus.bibliothek.uni-wuerzburg.de/files/14736/097_Dandekar_baw041.pdf