ReviewSeminars in cell & developmental biology2015
Computational analysis of signaling patterns in single cells.
Review in Seminars in cell & developmental biology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
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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
12 citing papers in PubMed, 20 citations in OpenAlex.
- NF-kB in Signaling Patterns and Its Temporal Dynamics Encode/Decode Human Diseases.Life (Basel, Switzerland) · 2022Review
- microRNA-Mediated Encoding and Decoding of Time-Dependent Signals in Tumorigenesis.Biomolecules · 2022Review
- Isolation of Murine Retinal Endothelial Cells for Next-Generation Sequencing.Journal of visualized experiments : JoVE · 2021Article
- Inferring the structures of signaling motifs from paired dynamic traces of single cells.PLoS computational biology · 2021Article
- Isolation of Highly Purified and Viable Retinal Endothelial Cells.Journal of vascular research · 2021Article
- The Cell Cycle Browser: An Interactive Tool for Visualizing, Simulating, and Perturbing Cell-Cycle Progression.Cell systems · 2018Article
- Integrated Platform for Monitoring Single-cell MAPK Kinetics in Computer-controlled Temporal Stimulations.Scientific reports · 2018Article
- Accurate delineation of cell cycle phase transitions in living cells with PIP-FUCCI.Cell cycle (Georgetown, Tex.) · 2018Article
- A Critical and Comparative Review of Fluorescent Tools for Live-Cell Imaging.Annual review of physiology · 2017Review
- Processing Oscillatory Signals by Incoherent Feedforward Loops.PLoS computational biology · 2016Article
- Single-cell approaches for molecular classification of endocrine tumors.Current opinion in oncology · 2016Review
- Intracellular Information Processing through Encoding and Decoding of Dynamic Signaling Features.PLoS computational biology · 2015Article
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 at 1 institution in 1 country.
Funding
Abstract
Signaling proteins are flexible in both form and function. They can bind to multiple molecular partners and integrate diverse types of cellular information. When imaged by time-lapse microscopy, many signaling proteins show complex patterns of activity or localization that vary from cell to cell. This heterogeneity is so prevalent that it has spurred the development of new computational strategies to analyze single-cell signaling patterns. A collective observation from these analyses is that cells appear less heterogeneous when their responses are normalized to, or synchronized with, other single-cell measurements. In many cases, these transformed signaling patterns show distinct dynamical trends that correspond with predictable phenotypic outcomes. When signaling mechanisms are unclear, computational models can suggest putative molecular interactions that are experimentally testable. Thus, computational analysis of single-cell signaling has not only provided new ways to quantify the responses of individual cells, but has helped resolve longstanding questions surrounding many well-studied human signaling proteins including NF-κB, p53, ERK1/2, and CDK2. A number of specific challenges lie ahead for single-cell analysis such as quantifying the contribution of non-cell autonomous signaling as well as the characterization of protein signaling dynamics in vivo.
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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.