Demo Data from EDBT 2026 / reviewers in the wild / expert
Jan Mollenhauer
dblp:147/9474
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Bioinformatics and computational biology · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
proteomics |
0.2 | 1 | 2014 | Microarray R-based analysis of complex lysate experiments with MIRACLE · Bioinform. 2014 |
Bioinformatics and computational biology › proteomics
reverse-phase protein array analysis |
0.2 | 1 | 2014 | Microarray R-based analysis of complex lysate experiments with MIRACLE · Bioinform. 2014 |
Methods — techniques the papers use, named apart from their topics
statistical evaluation · 0.2response curve estimation · 0.2normalization · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Microarray R-based analysis of complex lysate experiments with MIRACLEabstractMOTIVATION: Reverse-phase protein arrays (RPPAs) allow sensitive quantification of relative protein abundance in thousands of samples in parallel. Typical challenges involved in this technology are antibody selection, sample preparation and optimization of staining conditions. The issue of combining effective sample management and data analysis, however, has been widely neglected. RESULTS: This motivated us to develop MIRACLE, a comprehensive and user-friendly web application bridging the gap between spotting and array analysis by conveniently keeping track of sample information. Data processing includes correction of staining bias, estimation of protein concentration from response curves, normalization for total protein amount per sample and statistical evaluation. Established analysis methods have been integrated with MIRACLE, offering experimental scientists an end-to-end solution for sample management and for carrying out data analysis. In addition, experienced users have the possibility to export data to R for more complex analyses. MIRACLE thus has the potential to further spread utilization of RPPAs as an emerging technology for high-throughput protein analysis. AVAILABILITY: Project URL: http://www.nanocan.org/miracle/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Markus List, Ines Block, Marlene Lemvig Pedersen, Helle Christiansen, Steffen Schmidt, Mads Thomassen, Qihua Tan, Jan Baumbach, Jan Mollenhauer |
Bioinform. | 9 |