ReviewProteomics2017
Single cell proteomics in biomedicine: High-dimensional data acquisition, visualization, and analysis.
Review in Proteomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 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
41 citing papers in PubMed.
- Navigating the Landscape of Cytometry-Based Single-Cell Proteomics: Quantification, Annotation, and Resources.International journal of molecular sciences · 2026Review
- Classification of biomedical lung cancer images using optimized binary bat technique by constructing oblique decision trees.Scientific reports · 2025Article
- Review
- Proteomics and Metabolomics in Biomedicine.International journal of molecular sciences · 2023Article
- ANPELA: Significantly Enhanced Quantification Tool for Cytometry-Based Single-Cell Proteomics.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2023Article
- Pterostilbene-Mediated Inhibition of Cell Proliferation and Cell Death Induction in Amelanotic and Melanotic Melanoma.International journal of molecular sciences · 2023Article
- Advances in neuroproteomics for neurotrauma: unraveling insights for personalized medicine and future prospects.Frontiers in neurology · 2023Review
- Next-Generation Personalized Medicine: Implementation of Variability Patterns for Overcoming Drug Resistance in Chronic Diseases.Journal of personalized medicine · 2022Review
- Article
- Constraint-Based Reconstruction and Analyses of Metabolic Models: Open-Source Python Tools and Applications to Cancer.Frontiers in oncology · 2022Review
- Identification and Engineering of Aptamers for Theranostic Application in Human Health and Disorders.International journal of molecular sciences · 2021Review
- Computational strategies for single-cell multi-omics integration.Computational and structural biotechnology journal · 2021Review
- Emerging Roles of Single-Cell Multi-Omics in Studying Developmental Temporal Patterning.International journal of molecular sciences · 2020Review
- On-chip protein separation with single-molecule resolution.Scientific reports · 2020Article
- Advances of Single-Cell Protein Analysis.Cells · 2020Review
- Multi-omic single-cell snapshots reveal multiple independent trajectories to drug tolerance in a melanoma cell line.Nature communications · 2020Article
- Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis.International journal of molecular sciences · 2020Review
- Predicting cell lineages using autoencoders and optimal transport.PLoS computational biology · 2020Article
- Circulating tumor cells in hepatocellular carcinoma: single-cell based analysis, preclinical models, and clinical applications.Theranostics · 2020Review
- Neurogenetic and Neuroepigenetic Mechanisms in Cognitive Health and Disease.Frontiers in molecular neuroscience · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
New insights on cellular heterogeneity in the last decade provoke the development of a variety of single cell omics tools at a lightning pace. The resultant high-dimensional single cell data generated by these tools require new theoretical approaches and analytical algorithms for effective visualization and interpretation. In this review, we briefly survey the state-of-the-art single cell proteomic tools with a particular focus on data acquisition and quantification, followed by an elaboration of a number of statistical and computational approaches developed to date for dissecting the high-dimensional single cell data. The underlying assumptions, unique features, and limitations of the analytical methods with the designated biological questions they seek to answer will be discussed. Particular attention will be given to those information theoretical approaches that are anchored in a set of first principles of physics and can yield detailed (and often surprising) predictions.
Indexed as
Identifiers
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.