ArticlePloS one2012
Automated analysis and reannotation of subcellular locations in confocal images from the Human Protein Atlas.
Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed.
- Drug response in the era of precision medicine: A methodological review.Computational and structural biotechnology journal · 2025Review
- AutoUnmix: an autoencoder-based spectral unmixing method for multi-color fluorescence microscopy imaging.Biomedical optics express · 2023Article
- PScL-DDCFPred: an ensemble deep learning-based approach for characterizing multiclass subcellular localization of human proteins from bioimage data.Bioinformatics (Oxford, England) · 2022Article
- Self-supervised learning of cell type specificity from immunohistochemical images.Bioinformatics (Oxford, England) · 2022Article
- PScL-HDeep: image-based prediction of protein subcellular location in human tissue using ensemble learning of handcrafted and deep learned features with two-layer feature selection.Briefings in bioinformatics · 2021Article
- Article
- Subcellular proteomics.Nature reviews. Methods primers · 2021Article
- Learning complex subcellular distribution patterns of proteins via analysis of immunohistochemistry images.Bioinformatics (Oxford, England) · 2020Article
- MIC_Locator: a novel image-based protein subcellular location multi-label prediction model based on multi-scale monogenic signal representation and intensity encoding strategy.BMC bioinformatics · 2019Article
- Learning unsupervised feature representations for single cell microscopy images with paired cell inpainting.PLoS computational biology · 2019Article
- Spatial proteomics: a powerful discovery tool for cell biology.Nature reviews. Molecular cell biology · 2019Review
- Deep learning is combined with massive-scale citizen science to improve large-scale image classification.Nature biotechnology · 2018Article
- Paired Expression Analysis of Tumor Cell Surface Antigens.Frontiers in oncology · 2017Article
- Subcellular protein expression models for microsatellite instability in colorectal adenocarcinoma tissue images.BMC bioinformatics · 2016Article
- Automated Learning of Subcellular Variation among Punctate Protein Patterns and a Generative Model of Their Relation to Microtubules.PLoS computational biology · 2015Article
- HPASubC: A suite of tools for user subclassification of human protein atlas tissue images.Journal of pathology informatics · 2015Article
- COMPARTMENTS: unification and visualization of protein subcellular localization evidence.Database : the journal of biological databases and curation · 2014Article
- Determining the subcellular location of new proteins from microscope images using local features.Bioinformatics (Oxford, England) · 2013Article
- An image-based multi-label human protein subcellular localization predictor (iLocator) reveals protein mislocalizations in cancer tissues.Bioinformatics (Oxford, England) · 2013Article
- Immunofluorescence and fluorescent-protein tagging show high correlation for protein localization in mammalian cells.Nature methods · 2013Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
The Human Protein Atlas contains immunofluorescence images showing subcellular locations for thousands of proteins. These are currently annotated by visual inspection. In this paper, we describe automated approaches to analyze the images and their use to improve annotation. We began by training classifiers to recognize the annotated patterns. By ranking proteins according to the confidence of the classifier, we generated a list of proteins that were strong candidates for reexamination. In parallel, we applied hierarchical clustering to group proteins and identified proteins whose annotations were inconsistent with the remainder of the proteins in their cluster. These proteins were reexamined by the original annotators, and a significant fraction had their annotations changed. The results demonstrate that automated approaches can provide an important complement to visual annotation.
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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.