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Qianming Xiang

dblp:425/8933 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2025
0000-0002-0372-2792ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
epigenomics
0.912025
scNucMap: mapping the nucleosome landscapes at single-cell resolution · Bioinform. 2025
Bioinformatics and computational biology › epigenomics › chromatin analysis
nucleosome positioning
0.912025
scNucMap: mapping the nucleosome landscapes at single-cell resolution · Bioinform. 2025
Bioinformatics and computational biology
single-cell analysis
0.912025
scNucMap: mapping the nucleosome landscapes at single-cell resolution · Bioinform. 2025
Bioinformatics and computational biology › single-cell analysis › single-cell epigenomics
single-cell chromatin accessibility
0.912025
scNucMap: mapping the nucleosome landscapes at single-cell resolution · Bioinform. 2025

Methods — techniques the papers use, named apart from their topics

transcription factor association analysis · 0.9cell clustering · 0.9
YearPublicationVenuePosition
2025 scNucMap: mapping the nucleosome landscapes at single-cell resolution
abstract
MOTIVATION: Nucleosome depletion around cis-regulatory elements (CREs) is associated with CRE activity and implies the underlying gene regulatory network. Single-cell micrococcal nuclease sequencing (scMNase-seq) enables the simultaneous measurement of nucleosome positioning and chromatin accessibility at single-cell resolution, thereby capturing cellular heterogeneity in epigenetic regulation. However, there is currently no computational tool specifically designed to decode scMNase-seq data, impeding the generation of more precise and context-dependent insights into chromatin dynamics and gene regulation. RESULTS: Here, we present scNucMap, a tool designed to leverage the unique characteristics of scMNase-seq data to map the landscapes of candidate nucleosome-free regions (NFRs). scNucMap demonstrated superior performance and robustness in cell clustering on scMNase-seq data compared to Signac and chromVAR across diverse sample compositions and data complexities, achieving higher overall accuracy and Kappa coefficients. Additionally, scNucMap identified significant TFs associated with nucleosome depletion at CREs at both single-cell and cell-cluster levels, thereby facilitating cell-type annotation and regulatory network inference. When applied to scATAC-seq data, scNucMap enriched standard analyses with complementary insights into nucleosome architecture, underscoring its cross‑modality versatility. Overall, scNucMap exhibits both high reliability and adaptability, making it an effective tool for analyzing scMNase-seq data and supporting multimodal studies, thereby illuminating the intricate relationship between regulatory networks and nucleosome positioning at single-cell resolution. AVAILABILITY AND IMPLEMENTATION: scNucMap is available at https://github.com/qianming-bioinfo/scNucMap.
Qianming Xiang, Binbin Lai
Bioinform.1