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

Srinivas Niranj Chandrasekaran

Broad Institute

ORCID: 0000-0001-8874-9988
Biochemistry, Genetics and Molecular BiologyMaterials Science

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 2%percentile
4.5Author DataRank

Indexed papers

2in 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 2 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.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

Nature Methods(2024)10.1038/s41592-024-02241-6
Top 8%
2.7DataRank
Top 8%124 citations

Beth A. Cimini, Amy Goodale, Lisa Miller, Maria Kost‐Alimova, Nasim Jamali +18 more

Papers

Driven by 13 papers — median percentile 90. Top paper: “Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations”.

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

Nature Methods(2024)10.1038/s41592-024-02241-6
Top 8%
2.7DataRank
Top 8%124 citations

Beth A. Cimini, Amy Goodale, Lisa Miller, Maria Kost‐Alimova, Nasim Jamali +18 more

Three million images and morphological profiles of cells treated with matched chemical and genetic perturbations

bioRxiv (Cold Spring Harbor Laboratory)(2022)10.1101/2022.01.05.475090
Top 12%
1.8DataRank
Top 12%51 citations

Beth A. Cimini, Amy Goodale, Lisa Miller, Maria Kost‐Alimova, Nasim Jamali +18 more

Image-based profiling for drug discovery: due for a machine-learning upgrade?

Nature Reviews Drug Discovery(2020)10.1038/s41573-020-00117-w
N/A
0.909DataRank · unranked
427 citations

Hugo Ceulemans, Justin D. Boyd, Anne E. Carpenter, Srinivas Niranj Chandrasekaran

Optimizing the Cell Painting assay for image-based profiling

Nature Protocols(2023)10.1038/s41596-023-00840-9
N/A
0.763DataRank · unranked
161 citations

Srinivas Niranj Chandrasekaran, Maria Kost‐Alimova, Lisa Miller, Amy Goodale, Briana Fritchman +30 more

Morphology and gene expression profiling provide complementary information for mapping cell state

Cell Systems(2022)10.1016/j.cels.2022.10.001
N/A
0.737DataRank · unranked
135 citations

Ted Natoli, Adeniyi Adeboye, Lev Litichevskiy, Andrew X. Yang, Xiaodong Lü +15 more

Reproducible image-based profiling with Pycytominer

PubMed(2023)10.48550/arxiv.2311.13417
N/A
0.538DataRank · unranked
18 citations

Srinivas Niranj Chandrasekaran, Dave Bunten, Kenneth I. Brewer, Jenna Tomkinson, Roshan Kern +23 more

Morphology and gene expression profiling provide complementary information for mapping cell state

bioRxiv (Cold Spring Harbor Laboratory)(2021)10.1101/2021.10.21.465335
N/A
0.515DataRank · unranked
30 citations

Ted Natoli, Adeniyi Adeboye, Lev Litichevskiy, Andrew X. Yang, Xiaodong Lü +15 more

Morphological map of under- and overexpression of genes in human cells

Nature Methods(2025)10.1038/s41592-025-02753-9
N/A
0.385DataRank · unranked
12 citations

Eric Alix, John Arévalo, Adriana Borowa, Patrick J. Byrne, William G Charles +51 more

nELISA: a high-throughput, high-plex platform enables quantitative profiling of the inflammatory secretome

Nature Methods(2025)10.1038/s41592-025-02861-6
N/A
0DataRank · unranked
11 citations

Grant Ongo, Nathaniel Robichaud, Jinglin Kong, Woojong Rho, Ivan Teahulos +27 more

Statistical Evaluation of the Rodin–Ohno Hypothesis: Sense/Antisense Coding of Ancestral Class I and II Aminoacyl-tRNA Synthetases

UNC Libraries(2020)10.17615/wqqr-e324
N/A
0DataRank · unranked
0 citations

Charles W. Carter, Özgün Erdoğan, Jeffrey Roach, Srinivas Niranj Chandrasekaran, Galip Gürkan Yardımcı

Microcalorimetry reveals multi-state thermal denaturation of G. stearothermophilus tryptophanyl-tRNA synthetase

Structural Dynamics(2023)10.1063/4.0000181
N/A
0DataRank · unranked
2 citations

Jhuma Das, Nikolay V. Dokholyan, Charles W. Carter, Srinivas Niranj Chandrasekaran

Functional Class I and II Amino Acid-activating Enzymes Can Be Coded by Opposite Strands of the Same Gene

UNC Libraries(2020)10.17615/0che-gh49
N/A
0DataRank · unranked
0 citations

Luis Martínez‐Rodríguez, Srinivas Niranj Chandrasekaran, Brian Kuhlman, Mariel Jimenez-Rodriguez, Li Li +7 more

Enhanced Amino Acid Selection in Fully Evolved Tryptophanyl-tRNA Synthetase, Relative to Its Urzyme, Requires Domain Motion Sensed by the D1 Switch, a Remote Dynamic Packing Motif

UNC Libraries(2020)10.17615/pbcg-4323
N/A
0DataRank · unranked
0 citations

Charles W. Carter, Patrice Koehl, Violetta Weinreb, Li Li, Srinivas Niranj Chandrasekaran +1 more