Demo Data from SIGIR 2026 / reviewers in the wild / expert
Nils B. Leimkühler
dblp:339/7614
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2021
—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 › single-cell analysis › single-cell RNA sequencing
single-cell RNA-seq analysis |
0.5 | 1 | 2021 | CrossTalkeR: analysis and visualization of ligand-receptorne tworks · Bioinform. 2021 |
Bioinformatics and computational biology
cell-cell communication |
0.1 | 1 | 2021 | CrossTalkeR: analysis and visualization of ligand-receptorne tworks · Bioinform. 2021 |
Methods — techniques the papers use, named apart from their topics
visualization · 0.5network analysis · 0.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2021 | CrossTalkeR: analysis and visualization of ligand-receptorne tworksabstractMOTIVATION: Ligand-receptor (LR) network analysis allows the characterization of cellular crosstalk based on single cell RNA-seq data. However, current methods typically provide a list of inferred LR interactions and do not allow the researcher to focus on specific cell types, ligands or receptors. In addition, most of these methods cannot quantify changes in crosstalk between two biological phenotypes. RESULTS: CrossTalkeR is a framework for network analysis and visualization of LR interactions. CrossTalkeR identifies relevant ligands, receptors and cell types contributing to changes in cell communication when contrasting two biological phenotypes, i.e. disease versus homeostasis. A case study on scRNA-seq of human myeloproliferative neoplasms reinforces the strengths of CrossTalkeR for characterization of changes in cellular crosstalk in disease. AVAILABILITY AND IMPLEMENTATION: CrosstalkeR is an R package available at: Github: https://github.com/CostaLab/CrossTalkeR. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. James Shiniti Nagai, Nils B. Leimkühler, Michael T. Schaub, Rebekka K. Schneider, Ivan G. Costa |
Bioinform. | 2 |