ResearcherChinese Academy of Medical Sciences & Peking Union Medical CollegeActive in the last 2 years

Xing Wang

ORCID-verified (high confidence, 0.95), identity_conf@1As of 7 November 2026

Matched on ORCID iD 0000-0002-0804-2956; OpenAlex author ID A5101441943. Sources: OpenAlex.

Their work

Papers: 1
Trials: 0
Grants: 0
Labs led: 0
Collaborators: 6

Papers, trials and grants by year

2024: 1 paper

Papers 1

Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. Co-author DOI 10.1016/j.gendis.2023.101143 ↗

Closest collaborators

The 6 strongest of 6 by collab_strength@1: shared papers, trials and grants, recent and small-team work weighing most.

Bo Ren · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗
Gang Yang · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗
Jinshou Yang · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗
Jie Ren · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗
Yupei Zhao · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗
Lei You · 1 shared paper, 2024 · strength 0.21
- Paper Comprehensive multi-omics profiling identifies novel molecular subtypes of pancreatic ductal adenocarcinoma. DOI 10.1016/j.gendis.2023.101143 ↗

How to reach this person

A chain of introductions through people who have published, run trials or held grants together (warm_path@1: fewest links first, then the strongest). Built from public records only; no contact details are kept.