🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Yuge Ji

Helmholtz Munich

ORCID: 0009-0005-8198-9205

Also affiliated with Technical University of Munich

Biochemistry, Genetics and Molecular BiologyMedicine

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 1%percentile
5.0Author DataRank

Indexed papers

1in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 1 indexed paper attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Top data-sharing exemplar

The highest-impact dataset this researcher has shared, ranked by DataRank — the single contribution doing the most to lift their data-sharing standing.

An integrated cell atlas of the lung in health and disease

Nature Medicine(2023)10.1038/s41591-023-02327-2
Top 4%
5.0DataRank
Top 4%781 citations

Ciro Ramírez-Suástegui, Tessa E. Gillett, Luke Zappia, Elo Madissoon, Nikolay S. Markov +87 more

Papers

Driven by 8 papers — median percentile 96. Top paper: “An integrated cell atlas of the lung in health and disease”.

An integrated cell atlas of the lung in health and disease

Nature Medicine(2023)10.1038/s41591-023-02327-2
Top 4%
5.0DataRank
Top 4%781 citations

Ciro Ramírez-Suástegui, Tessa E. Gillett, Luke Zappia, Elo Madissoon, Nikolay S. Markov +87 more

Machine learning for perturbational single-cell omics

Cell Systems(2021)10.1016/j.cels.2021.05.016
N/A
3.6DataRank · unranked
136 citations

Mohammad Lotfollahi, Francesca Finotello, Fabian Joachim Theis, Florian Wolf, Yuge Ji

Learning interpretable cellular responses to complex perturbations in high-throughput screens

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.04.14.439903
N/A
1.9DataRank · unranked
52 citations

Anna Klimovskaia Susmelj, Carlo De Donno, Yuge Ji, Ignacio Ibarra Del Río, Francesca Finotello +5 more

Defining and benchmarking open problems in single-cell analysis

Nature Biotechnology(2025)10.1038/s41587-025-02694-w
N/A
0.937DataRank · unranked
29 citations

Scott Gigante, Daniel B. Burkhardt, Robrecht Cannoodt, Nikolay S. Markov, Luke Zappia +48 more

Optimal distance metrics for single-cell RNA-seq populations

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.12.26.572833
N/A
0.908DataRank · unranked
19 citations

Tessa D. Green, Stefan Peidli, Mojtaba Bahrami, Meiqi Liu, Luke Zappia +4 more

Predicting cellular responses to complex perturbations in high‐throughput screens

Molecular Systems Biology(2023)10.15252/msb.202211517
N/A
0.832DataRank · unranked
256 citations

Anna Klimovskaia Susmelj, Carlo De Donno, Leon Hetzel, Yuge Ji, Ignacio Ibarra Del Río +16 more

Defining and benchmarking open problems in single-cell analysis

Research Square(2024)10.21203/rs.3.rs-4181617/v1
N/A
0.603DataRank · unranked
17 citations

Scott Gigante, Daniel B. Burkhardt, Robrecht Cannoodt, Daniel Strobl, Nikolay S. Markov +45 more

Scalable and universal prediction of cellular phenotypes enables in silico experiments

bioRxiv (Cold Spring Harbor Laboratory)(2024)10.1101/2024.08.12.607533
N/A
0.527DataRank · unranked
12 citations

Alejandro Tejada-Lapuerta, Niklas A. Schmacke, Zihe Zheng, Xinyue Zhang, Simrah Khan +6 more