Demo Data from VLDB 2026 / reviewers in the wild / expert
Neda Ghohabi Esfahani
dblp:434/2105
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2026
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021
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 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Bioinformatics and computational biology › sequence analysis
nanopore sequencing |
1.0 | 1 | 2026 | CurrentView: a tool for visualization and comparison of nanopore ionic current signals · Bioinform. 2026 |
Bioinformatics and computational biology
sequence analysis |
1.0 | 1 | 2026 | CurrentView: a tool for visualization and comparison of nanopore ionic current signals · Bioinform. 2026 |
Methods — techniques the papers use, named apart from their topics
kernel density estimation · 1.0gaussian mixture model · 1.0UMAP dimensionality reduction · 1.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2026 | CurrentView: a tool for visualization and comparison of nanopore ionic current signalsabstractSUMMARY: Nanopore sequencing measures ionic current as native DNA or RNA molecules move through a biological pore. The resulting ionic current changes are inferred into sequence by Oxford Nanopore Technologies' Dorado basecaller. These data permit direct analysis of nucleotide sequences and modifications. The Dorado basecaller also outputs a move-table that contains approximate mappings between ionic current signal and basecalled sequence. This ionic current information can be visualized at specific positions given the alignment between a read sequence and a reference sequence. We present CurrentView, a fast and user-friendly toolkit for reference-guided visualization of nanopore ionic current signals. CurrentView uses conventional sequence alignment and move-table information from BAM files and signal information from ONT POD5 files to extract and visualize ionic current traces at specific positions. The toolkit supports simultaneous comparison across multiple experimental conditions, computes summary statistics through kernel density estimation and histograms, and enables visual analysis of signal patterns associated with modifications or sequence context. Notably, CurrentView can visualize and analyze more than two conditions at once. It supports UMAP dimensionality reduction and Gaussian Mixture Model (GMM) clustering, enabling the identification of distinct signal populations across experimental groups. CurrentView is available as both a Python API and an exploratory interactive web application, allowing researchers to rapidly inspect ionic current patterns and compare conditions. AVAILABILITY AND IMPLEMENTATION: CurrentView is fully open-source and available on GitHub https://github.com/genometechlab/currentview. The repository includes full documentation, an installation guide, usage instructions, and an example Jupyter notebook showing typical use cases similar to the one presented in the manuscript. Pooria Daneshvar Kakhaki, Neda Ghohabi Esfahani, Stuart Akeson, Miten Jain |
Bioinform. | 2 |