Demo Data from EDBT 2026 / reviewers in the wild / expert
Ram Ajore
dblp:59/6557
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—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 3 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology
genomics |
0.4 | 1 | 2019 | MPRAscore: robust and non-parametric analysis of massively parallel reporter assays · Bioinform. 2019 |
Bioinformatics and computational biology
massively parallel reporter assay |
0.4 | 1 | 2019 | MPRAscore: robust and non-parametric analysis of massively parallel reporter assays · Bioinform. 2019 |
Bioinformatics and computational biology › gene regulation
regulatory variant analysis |
0.4 | 1 | 2019 | MPRAscore: robust and non-parametric analysis of massively parallel reporter assays · Bioinform. 2019 |
Methods — techniques the papers use, named apart from their topics
variance regularization · 0.4permutation testing · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | MPRAscore: robust and non-parametric analysis of massively parallel reporter assaysabstractMOTIVATION: Massively parallel reporter assays (MPRA) enable systematic screening of DNA sequence variants for effects on transcriptional activity. However, convenient analysis tools are still needed. RESULTS: We introduce MPRAscore, a novel tool to infer allele-specific effects on transcription from MPRA data. MPRAscore uses a weighted, variance-regularized method to calculate variant effect sizes robustly, and a permutation approach to test for significance without assuming normality or independence. AVAILABILITY AND IMPLEMENTATION: Source code (C++), precompiled binaries and data used in the paper at https://github.com/abhisheknrl/MPRAscore and https://www.ncbi.nlm.nih.gov/bioproject/PRJNA554195. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Abhishek Niroula, Ram Ajore, Björn Nilsson |
Bioinform. | 2 |