ReviewMolecular & cellular proteomics : MCP2020
Profiling Cell Signaling Networks at Single-cell Resolution.
Review in Molecular & cellular proteomics : MCP, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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.
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.
Who cites it
24 citing papers in PubMed.
- Amplification bias in sequencing-based spatial transcriptomics: sources, mechanisms, impacts, and mitigation strategies.Briefings in bioinformatics · 2026Review
- [Misdirected intercellular communication in aging and chronic inflammation].Zeitschrift fur Gerontologie und Geriatrie · 2026Review
- Mathematical Modeling and Inference of Epidermal Growth Factor-Induced Mitogen-Activated Protein Kinase Cell Signaling Pathways.International journal of molecular sciences · 2024Review
- PUFFFIN: an ultra-bright, customisable, single-plasmid system for labelling cell neighbourhoods.The EMBO journal · 2024Article
- Community assessment of methods to deconvolve cellular composition from bulk gene expression.Nature communications · 2024Article
- Deciphering the aging process through single-cell cytometric technologies.Cytometry. Part A : the journal of the International Society for Analytical Cytology · 2024Review
- Genetic Tools for Cell Lineage Tracing and Profiling Developmental Trajectories in the Skin.The Journal of investigative dermatology · 2024Review
- EZH2-mediated epigenetic silencing of tumor-suppressive let-7c/miR-99a cluster by hepatitis B virus X antigen enhances hepatocellular carcinoma progression and metastasis.Cancer cell international · 2023Article
- Deep Learning in Phosphoproteomics: Methods and Application in Cancer Drug Discovery.Proteomes · 2023Review
- To metabolomics and beyond: a technological portfolio to investigate cancer metabolism.Signal transduction and targeted therapy · 2023Review
- Pan-Cancer landscape of protein activities identifies drivers of signalling dysregulation and patient survival.Molecular systems biology · 2023Article
- Network-based approaches for modeling disease regulation and progression.Computational and structural biotechnology journal · 2023Review
- Multiplexed Detection of Molecular Interactions with DNA Origami Engineered Cells in 3D Collagen Matrices.ACS applied materials & interfaces · 2022Article
- Article
- Breast cancer heterogeneity through the lens of single-cell analysis and spatial pathologies.Seminars in cancer biology · 2022Review
- Advances and Utility of the Human Plasma Proteome.Journal of proteome research · 2021Review
- Computational quantification of global effects induced by mutations and drugs in signaling networks of colorectal cancer cells.Scientific reports · 2021Article
- Integration of FRET and sequencing to engineer kinase biosensors from mammalian cell libraries.Nature communications · 2021Article
- Analyzing signaling activity and function in hematopoietic cells.The Journal of experimental medicine · 2021Review
- Combining Mass Spectrometry-Based Phosphoproteomics with a Network-Based Approach to Reveal FLT3-Dependent Mechanisms of Chemoresistance.Proteomes · 2021Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
Abstract
Signaling networks process intra- and extracellular information to modulate the functions of a cell. Deregulation of signaling networks results in abnormal cellular physiological states and often drives diseases. Network responses to a stimulus or a drug treatment can be highly heterogeneous across cells in a tissue because of many sources of cellular genetic and non-genetic variance. Signaling network heterogeneity is the key to many biological processes, such as cell differentiation and drug resistance. Only recently, the emergence of multiplexed single-cell measurement technologies has made it possible to evaluate this heterogeneity. In this review, we categorize currently established single-cell signaling network profiling approaches by their methodology, coverage, and application, and we discuss the advantages and limitations of each type of technology. We also describe the available computational tools for network characterization using single-cell data and discuss potential confounding factors that need to be considered in single-cell signaling network analyses.
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What OpenQuestion holds
Registered trials
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.