Protocol for single-cell optimization objective and trade-off inference.

Da-Wei Lin, Cara Teixeira, Carolina Chung, Sayan Saha Roy, Amit Ghosh, Sriram Chandrasekaran

Abstract read

In one paragraph

Article in STAR protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

–field-weighted citation impact

1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Da-Wei LinGilbert S. Omenn Department of Computational Medicine and Bioinformatics, Ann Arbor, MI 48109, USA; Department of Statistics, University of Michigan, Ann Arbor, MI, USA.

Cara TeixeiraGilbert S. Omenn Department of Computational Medicine and Bioinformatics, Ann Arbor, MI 48109, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA.

Carolina ChungDepartment of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA.

Sayan Saha RoySchool of Nano Science Technology, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India.

Amit GhoshSchool of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India.

Sriram ChandrasekaranGilbert S. Omenn Department of Computational Medicine and Bioinformatics, Ann Arbor, MI 48109, USA; Department of Biomedical Engineering, University of Michigan, Ann Arbor, MI, USA; Program in Chemical Biology, University of Michigan, Ann Arbor, MI, USA; Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, MI 48109, USA. Electronic address: csriram@umich.edu.

Funding

Linking metabolic activity with drug sensitivity using metabolic influence networksR35GM137795 · NIGMS · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Sriram Chandrasekaran · 2020 to 2026

$2.6M

NIGMS NIH HHS R35 GM137795

6 · The paper itself

Abstract

Single-cell optimization objective and trade-off inference (SCOOTI) is a computational framework that integrates bulk and single-cell omics data with genome-scale metabolic modeling to infer metabolic objectives and trade-offs in biological systems. Here, we present a protocol for installing and running SCOOTI, using transcriptomics, proteomics, and metabolomics data to constrain metabolic models. We describe steps to interpret metabolic priorities across different cell states or conditions through clustering, dimensionality reduction, and trade-off analysis.

Indexed as

Computational BiologySingle-Cell AnalysisAnimalsMetabolomicsModels, BiologicalMultiomicsProteomicsSoftwareSystems BiologyBioinformaticsMetabolismSystems biology

Identifiers

PMID41790544

DOI10.1016/j.xpro.2026.104373

PMCPMC12992945

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.