ReviewThe Journal of cell biology2017
Machine learning and computer vision approaches for phenotypic profiling.
Review in The Journal of cell biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 73 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
73 citing papers in PubMed.
- Exploring clusters based on ultrasound-detected inflammation in patients with psoriatic arthritis: a post-hoc analysis from the ULTIMATE trial.BMC musculoskeletal disorders · 2026Trial
- Trial
- Novel Approaches for Investigating Host Responses to HIV Infection in Ex Vivo Human Genital Tissues.American journal of reproductive immunology (New York, N.Y. : 1989) · 2026Review
- Foundation model cascades enable zero-shot microscopy image analysis for cell therapy manufacturing.Cytotherapy · 2026Article
- MaizeField3D: A curated 3D point cloud and procedural model dataset of field-grown maize from a diversity panel.Plant phenomics (Washington, D.C.) · 2026Article
- Instance Segmentation as a Foundation for Quantitative Image Analysis in Leptospira Research.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Advances in machine learning-enhanced microfluidic cell sorting.Science advances · 2025Review
- Single-cell imaging of protein dynamics of paralogs reveals sources of gene retention.iScience · 2025Article
- Representation of high-dimensional cell morphology and morphodynamics in 2D latent space.Physical biology · 2025Article
- Decoding Drug Discovery: Exploring A-to-Z In Silico Methods for Beginners.Applied biochemistry and biotechnology · 2025Review
- Drug Repurposing: Insights into Current Advances and Future Applications.Current medicinal chemistry · 2025Review
- PIFiA: self-supervised approach for protein functional annotation from single-cell imaging data.Molecular systems biology · 2024Article
- Article
- AI-organoid integrated systems for biomedical studies and applications.Bioengineering & translational medicine · 2024Review
- Leveraging Artificial Intelligence for Synergies in Drug Discovery: From Computers to Clinics.Current pharmaceutical design · 2024Review
- Real-time semantic segmentation and anomaly detection of functional images for cell therapy manufacturing.Cytotherapy · 2023Article
- Strategic Approach to Heterogeneity Analysis of Cutaneous Adnexal Carcinomas Using Computational Pathology and Genomics.JID innovations : skin science from molecules to population health · 2023Article
- Machine learning and feature analysis of the cortical microtubule organization of Arabidopsis cotyledon pavement cells.Protoplasma · 2023Article
- Interpretable machine learning approach for neuron-centric analysis of human cortical cytoarchitecture.Scientific reports · 2023Article
- Computer vision meets microfluidics: a label-free method for high-throughput cell analysis.Microsystems & nanoengineering · 2023Review
13 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
With recent advances in high-throughput, automated microscopy, there has been an increased demand for effective computational strategies to analyze large-scale, image-based data. To this end, computer vision approaches have been applied to cell segmentation and feature extraction, whereas machine-learning approaches have been developed to aid in phenotypic classification and clustering of data acquired from biological images. Here, we provide an overview of the commonly used computer vision and machine-learning methods for generating and categorizing phenotypic profiles, highlighting the general biological utility of each approach.
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Identifiers
What Socratic 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 Socratic graph.