EDBT 2026 Demo / reviewers in the wild / expert
Peter Schierack
dblp:167/1781
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2015
—ORCID · unresolved
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 1 heaviest of 1, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
nucleic acid quantification |
0.2 | 1 | 2015 | chipPCR: an R package to pre-process raw data of amplification curves · Bioinform. 2015 |
Methods — techniques the papers use, named apart from their topics
statistical testing · 0.2derivative interpolation · 0.2curve smoothing · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2015 | chipPCR: an R package to pre-process raw data of amplification curvesabstractMOTIVATION: Both the quantitative real-time polymerase chain reaction (qPCR) and quantitative isothermal amplification (qIA) are standard methods for nucleic acid quantification. Numerous real-time read-out technologies have been developed. Despite the continuous interest in amplification-based techniques, there are only few tools for pre-processing of amplification data. However, a transparent tool for precise control of raw data is indispensable in several scenarios, for example, during the development of new instruments. RESULTS: chipPCR is an R: package for the pre-processing and quality analysis of raw data of amplification curves. The package takes advantage of R: 's S4 object model and offers an extensible environment. chipPCR contains tools for raw data exploration: normalization, baselining, imputation of missing values, a powerful wrapper for amplification curve smoothing and a function to detect the start and end of an amplification curve. The capabilities of the software are enhanced by the implementation of algorithms unavailable in R: , such as a 5-point stencil for derivative interpolation. Simulation tools, statistical tests, plots for data quality management, amplification efficiency/quantification cycle calculation, and datasets from qPCR and qIA experiments are part of the package. Core functionalities are integrated in GUIs (web-based and standalone shiny applications), thus streamlining analysis and report generation. AVAILABILITY AND IMPLEMENTATION: http://cran.r-project.org/web/packages/chipPCR. Source code: https://github.com/michbur/chipPCR. CONTACT: [email protected] SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Stefan Rödiger, Michal Burdukiewicz, Peter Schierack |
Bioinform. | 3 |