Reconstructing and comparing signal transduction networks from single-cell protein quantification data.

{"sci_version": "1.0", "schema": "https://corpus.bntrg.co.uk/sci/1.0/sci.schema.json", "id": "pmid:41437636", "kind": "science-record", "revision": 2, "content_hash": "sha256:d50f3c9aafd442390b8f246b80819d1140d86d9e38f07d61668c457e1af317c8", "created_at": "2026-11-01T20:31:25Z", "updated_at": "2026-11-01T21:36:13Z", "generator": {"name": "corpus-assay-engine", "run_id": "reading-sci-2026-11-01"}, "paper": {"state": "complete", "title": "Reconstructing and comparing signal transduction networks from single-cell protein quantification data.", "doi": "10.1093/bioinformatics/btaf675", "pmid": "41437636", "authors": ["Tim Stohn", "Roderick A P M van Eijl", "Klaas W Mulder", "Lodewyk F A Wessels", "Evert Bosdriesz"], "journal": "Bioinformatics (Oxford, England)", "year": 2026, "abstract": "MOTIVATION: Signal transduction networks regulate many essential biological processes and are frequently aberrated in diseases such as cancer. A mechanistic understanding of such networks, and how they differ between cell populations, is essential to design effective treatment strategies. Typically, such networks are computationally reconstructed based on systematic perturbation experiments, followed by quantification of signaling protein activity. Recent technological advances now allow for the quantification of the activity of many (signaling) proteins simultaneously in single cells. This makes it feasible to reconstruct or quantify signaling networks without performing systematic perturbations.\nRESULTS: Here, we introduce single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR) to derive signal transduction networks by exploiting the heterogeneity of single-cell (phospho-)protein measurements. The methods treat stochastic variation in total protein abundances as natural perturbation experiments, whose effects propagate through the network and hence facilitate the reconstruction and quantification of the underlying signaling network. scCNR reconstructs cell population-specific networks, where cells from different populations have the same underlying topology, but the interaction strengths can differ between populations. We extensively validated scMRA and scCNR on simulated data, and applied it to unpublished data of (phospho-)protein measurements of EGFR-inhibitor-treated keratinocytes to recover signaling differences downstream of EGFR. scCNR will help to unravel the mechanistic signaling differences between cell populations, and will subsequently guide the development of well-informed treatment strategies.\nAVAILABILITY AND IMPLEMENTATION: The code used for scCNR in this study has been deposited on Zenodo https://doi.org/10.5281/zenodo.17600937 and is also available as a Python module at https://github.com/ibivu/scmra. Additionally, data and code to reproduce all figures is available at https://github.com/tstohn/scmra_analysis.", "claims": [{"id": "claim-method", "statement": "scMRA and scCNR both solve a Mixed Integer Quadratic Programming (MIQP) optimization problem that aims to find the values of rijξ, siξ and pimξ that minimize the squared error, ϵi,a, representing the deviations between measured active protein abundance per cell (Ri,a) and the prediction of the model as described by the right-hand side of equation (1).", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41437636", "locator": "sections[3] \"2.1 Formulation of scMRA and scCNR\" paragraph 6", "quote": "scMRA and scCNR both solve a Mixed Integer Quadratic Programming (MIQP) optimization problem that aims to find the values of rijξ, siξ and pimξ that minimize the squared error, ϵi,a, representing the deviations between measured active protein abundance per cell (Ri,a) and the prediction of the model as described by the right-hand side of equation (1)."}], "state": "complete"}, {"id": "claim-data-access", "statement": "Supplementary data is available at Bioinformatics online.", "kind": "methodological", "target": null, "evidence": [{"asset": "source:pmid:41437636", "locator": "sections[18] \"Supplementary data\" paragraph 2", "quote": "Supplementary data is available at Bioinformatics online."}], "state": "complete"}, {"id": "claim-target-result", "statement": "The paper introduces single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR) to derive signal transduction networks by exploiting the heterogeneity of single-cell (phospho-)protein measurements.", "kind": "qualitative", "target": null, "evidence": [{"asset": "source:pmid:41437636", "locator": "sections[0] \"Abstract\" paragraph 2", "quote": "Here, we introduce single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR) to derive signal transduction networks by exploiting the heterogeneity of single-cell (phospho-)protein measurements."}], "state": "complete"}], "gaps": []}, "experiment": {"state": "partial", "objective": "The paper introduces single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR) to derive signal transduction networks by exploiting the heterogeneity of single-cell (phospho-)protein measurements.", "steps": [{"id": "read_published_estimate", "order": 1, "name": "Read the published estimate from the source", "kind": "other", "state": "complete", "blocked_on": null, "description": "The claim, method and evidence span published with the source article.", "duration_hours": null, "parameters": {}, "inputs": ["source:pmid:41437636"], "outputs": ["the published estimate and its evidence"], "instruments": [], "reagents": []}, {"id": "obtain_source_data", "order": 2, "name": "Obtain the source data from the named repository", "kind": "data-preparation", "state": "blocked", "blocked_on": "data:accession_absent", "description": "The GEO series accession resolves and its sample accessions are listed. This lane did not download the dataset or read its licence.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the source data with its repository provenance"], "instruments": [], "reagents": []}, {"id": "run_analysis", "order": 3, "name": "Run the published analysis", "kind": "analysis", "state": "complete", "blocked_on": null, "description": "Apply the paper's statistical method to the resolved series and compare the result with the published target.", "duration_hours": null, "parameters": {}, "inputs": [], "outputs": ["the replicated result and its comparison"], "instruments": [], "reagents": []}], "materials": [], "instruments": [], "reagents": [], "conditions": {}, "gaps": ["step:obtain_source_data blocked on data:accession_absent"]}, "data": {"state": "partial", "assets": [{"id": "source:pmid:41437636", "role": "manuscript", "format": "xml", "media_type": "application/xml", "uri": "https://doi.org/10.1093/bioinformatics/btaf675", "sha256": "sha256:3ff08ae8ed6d12531afc1455108438b0e15040d51fbe1cb32d4d2e6ca2833b19", "bytes": 59193, "access": "open", "state": "resolved", "reader": null, "reader_status": "reader_required", "identifier": "10.1093/bioinformatics/btaf675", "version": null, "note": "Full article fetched from PMC; the checksum covers the rendered section body, not the original XML bytes.", "structure": {"pmcid": "PMC12797212", "source": "europe_pmc_fulltext", "coverage": "whole_body_without_references", "text_hash_scope": "rendered_section_body"}}], "gaps": []}, "analysis": {"state": "partial", "methods": [{"id": "method-1", "family": null, "specific": null, "label": "Single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR), formulated as a Mixed Integer Quadratic Programming (MIQP) optimization problem", "dsl_operations": [], "missing_operations": [], "expressible": null, "parameters": {}, "data_shapes": [], "evidence": {"score": 1.0, "band": "verbatim", "quote": "scMRA and scCNR both solve a Mixed Integer Quadratic Programming (MIQP) optimization problem that aims to find the values of rijξ, siξ and pimξ that minimize the squared error, ϵi,a, representing the deviations between measured active protein abundance per cell (Ri,a) and the prediction of the model as described by the right-hand side of equation (1)."}}], "targets": [], "gaps": ["method.reader_named_unmapped"]}, "capability": {"state": "complete", "requirements": [{"capability_id": "capability:computational_analysis", "label": "Computational analysis platform", "assay_families": ["meta_analysis", "machine_learning", "survival_analysis", "statistical_regression", "pca", "molecular_docking", "network_analysis", "differential_expression", "gwas"], "availability_state": "owned", "tier_unlocked": "R1", "candidate": "Automated Assays Laravel application and simulated adapters"}], "gaps": []}, "readiness": {"state": "blocked", "tier": "R4", "blocking_axis": "data", "blocked_on": "data:accession_absent", "axes": {"method": {"tier": "R4", "expressible": false, "required_operations": [], "missing_operations": [], "basis": "The reader quoted the method the paper names (Single-cell modular response analysis (scMRA) and single-cell comparative network reconstruction (scCNR), formulated as a Mixed Integer Quadratic Programming (MIQP) optimization problem), but the corpus's method extractor could not map it onto a DSL operation, so the method is published but not expressible."}, "capability": {"tier": "R1", "capability_id": "capability:computational_analysis", "availability_state": "owned", "basis": "The computational analysis is owned. The physical bench the paper used is not, so a physical validation cannot be run here."}, "data": {"tier": "R4", "reachable": false, "accessions": [], "resolved_accessions": [], "statements": ["Supplementary data is available at Bioinformatics online."], "basis": "The paper names no accession to its source data, so the data has to come from the authors."}}, "can_run": {"dsl_operations": [], "assets": ["source:pmid:41437636"], "steps": ["run_analysis"]}, "must_build": {"dsl_operations": [], "converters": [], "readers": [], "capabilities": [], "data_gaps": ["data:geo:None"]}, "gaps": ["data:accession_absent"]}, "review": {"state": "partial", "machine_critique": {"kind": "extraction_review", "reader": {"model": "MiniMax-M3.1-Flash", "provider": "minimax", "provider_family": "minimax", "read_at": "2026-11-01T20:08:46Z", "independence": "single_reader"}, "evidence_check": {"method": "verbatim", "availability": "verbatim"}, "calls": 5, "usage": {"prompt_tokens": 13862, "completion_tokens": 1326, "cached_tokens": 256}}, "human_critique": null, "stages": [{"id": "extraction", "state": "complete", "reader": "MiniMax-M3.1-Flash", "provider": "minimax"}], "gaps": ["review.independent_reader", "review.machine_critique", "review.human_critique"]}, "execution": {"state": "absent", "status": "not_run", "mode": null, "runs": [], "gaps": ["execution.not_run"]}, "provenance": {"entities": [{"id": "pmid:41437636", "type": "paper", "label": "pmid:41437636"}, {"id": "source:pmid:41437636", "type": "manuscript", "label": "PMID 41437636 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "activities": [{"id": "activity-reading-sci-2026-11-01", "type": "classification", "used": [{"id": "pmid:41437636", "type": "paper", "label": "pmid:41437636"}, {"id": "source:pmid:41437636", "type": "manuscript", "label": "PMID 41437636 full text"}, {"id": "data:geo:None", "type": "dataset", "label": "GEO None"}], "agent": "agent:corpus-assay-engine"}, {"id": "activity-read-41437636", "type": "extraction", "used": ["source:pmid:41437636"], "agent": "agent:minimax-reader"}, {"id": "activity-resolve-None", "type": "accession_resolution", "used": ["data:geo:None"], "agent": "agent:corpus-assay-engine"}], "agents": [{"id": "agent:corpus-assay-engine", "type": "software", "label": "Corpus assay engine"}, {"id": "agent:minimax-reader", "type": "software", "label": "MiniMax literature reader"}], "source_run_id": "reading-sci-2026-11-01", "dsl_catalogue_fingerprint": "343fb30756ba6ec3", "capability_table_fingerprint": "2cb3e42f047d2ecf", "snapshot_id": "ba34b49490d9bfaf"}, "lineage": {"parent_id": "pmid:41437636", "parent_hash": "sha256:3ae5bf54f184e2d1e43d6109a84321f2a427c636f1de6fca0b4fb55d1648393c", "fork_of": null, "generation": 1}, "gaps": ["execution.not_run", "method.reader_named_unmapped", "review.human_critique", "review.independent_reader", "review.machine_critique", "step:obtain_source_data blocked on data:accession_absent"]}