Computational methods to deconvolve low-re解 spatial transcriptomic data using single-cell RNA sequencing data

Authors

Xiting Yan (ORCID: https://orcid.org/0000-0001-8688-9004)
Huanhuan Wei (ORCID: https://orcid.org/0000-0002-6481-5407)

Publication Details

Journal: Scientia Sinica Mathematica
Published: 2025-04-15
DOI: https://doi.org/10.1360/ssm-2024-0318
Primary Topic: Single-cell and spatial transcriptomics
Type: article
Field-Weighted Citation Impact: 0.00

Controls

|||

ALL TIME

JAN

FEB

MAR

APR

MAY

JUN

JUL

AUG

SEP

OCT

article

Computational methods to deconvolve low-re解 spatial transcriptomic data using single-cell RNA sequencing data

Xiting Yan, Huanhuan Wei

Apr 15, 2025

Scientia Sinica Mathematica

Single-cell and spatial transcriptomics

article

Computational methods to deconvolve low-re解 spatial transcriptomic data using single-cell RNA sequencing data

Xiting Yan, Huanhuan Wei

April 15, 2025article en

Abstract

No abstract available for this paper.

Scientia Sinica MathematicaVol. 55(7)

Openalex Percentile: Top 93%

Single-cell and spatial transcriptomics

DOI Open Access PDF OpenAlex

AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Computational methods to deconvolve low-re解 spatial transcriptomic data using single-cell RNA sequencing data — Xiting Yan, Huanhuan Wei · Scientia Sinica Mathematica (2025) | TGRS Research Map | TGRS