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

Amanda Momenzadeh

Cedars-Sinai Medical Center

ORCID: 0000-0002-8614-0690

Also affiliated with Cedars-Sinai Smidt Heart Institute

ChemistryBiochemistry, Genetics and Molecular Biology

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 5%percentile
0.521Author DataRank

Indexed papers

3in 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 3 indexed papers 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.

Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures

Clinical Proteomics(2024)10.1186/s12014-024-09487-4
Top 57%
0.275DataRank
Top 57%4 citations

Simion Kreimer, Dongchuan Guo, Matthew Ayres, Daniel S. Berman, Kuang‐Yuh Chyu +6 more

Papers

Driven by 11 papers — median percentile 30. Top paper: “Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures”.

Differentiation between descending thoracic aortic diseases using machine learning and plasma proteomic signatures

Clinical Proteomics(2024)10.1186/s12014-024-09487-4
Top 57%
0.275DataRank
Top 57%4 citations

Simion Kreimer, Dongchuan Guo, Matthew Ayres, Daniel S. Berman, Kuang‐Yuh Chyu +6 more

Differentiation between Descending Thoracic Aortic Diseases using Machine Learning and Plasma Proteomic Signatures

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.04.26.538468
Top 70%
0.142DataRank
Top 70%1 citations

Simion Kreimer, Dongchuan Guo, Matthew Ayres, Daniel S. Berman, Kuang‐Yuh Chyu +6 more

Data-driven discovery of medication effects on blood glucose from electronic health records

Patterns(2025)10.1016/j.patter.2025.101312
Top 78%
0.104DataRank
Top 78%1 citations

Caleb Cranney, So Yung Choi, Catherine Bresee, Mourad Tighiouart, Roma Gianchandani +4 more

A Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics

Journal of the American Society for Mass Spectrometry(2023)10.1021/jasms.3c00072
N/A
0DataRank · unranked
24 citations

Yuming Jiang, Simion Kreimer, Laura E. Teigen, Carlos S. Zepeda, Ali Haghani +8 more

Single-Injection Multi-Omics Analysis by Direct Infusion Mass Spectrometry

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.06.26.546628
N/A
0DataRank · unranked
10 citations

Ivan Alexander Salladay-Perez, Amanda Momenzadeh, Jesús Muñoz-Estrada, Uktarsh Tripathi, Anthony J. Covarrubias +2 more

Parallelization with Dual-Trap Single-Column Configuration Maximizes Throughput of Proteomic Analysis

Analytical Chemistry(2022)10.1021/acs.analchem.2c02609
N/A
0DataRank · unranked
39 citations

Ali Haghani, Aleksandra Binek, Alisse Hauspurg, Saeed Seyedmohammad, Alejandro Rivas +5 more

Complete Workflow for High Throughput Human Single Skeletal Muscle Fiber Proteomics

bioRxiv (Cold Spring Harbor Laboratory)(2023)10.1101/2023.02.23.529600
N/A
0DataRank · unranked
3 citations

Yuming Jiang, Simion Kreimer, Laura E. Teigen, Carlos S. Zepeda, Ali Haghani +8 more

Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

ACS Measurement Science Au(2024)10.1021/acsmeasuresciau.3c00068
N/A
0DataRank · unranked
170 citations

Devasahayam Arokia Balaya Rex, Dina Schuster, Benjamin A. Neely, Germán L. Rosano, Norbert Volkmar +15 more

Comprehensive Overview of Bottom-up Proteomics using Mass Spectrometry

PubMed(2023)10.48550/arxiv.2311.07791
N/A
0DataRank · unranked
8 citations

Rex, Devasahayam Arokia Balaya, Dina Schuster, Benjamin A. Neely, Germán L. Rosano, Norbert Volkmar +14 more

Bias or biology? Importance of model interpretation in machine learning studies from electronic health records

JAMIA Open(2022)10.1093/jamiaopen/ooac063
N/A
0DataRank · unranked
17 citations

Ali Shamsa, Jesse G. Meyer, Amanda Momenzadeh

Clinical interpretation of machine learning models for prediction of diabetic complications using electronic health records

medRxiv(2022)10.1101/2022.03.11.22272039
N/A
0DataRank · unranked
3 citations

Ali Shamsa, Jesse G. Meyer, Amanda Momenzadeh