ArticleBioinformatics (Oxford, England)2017
SChloro: directing Viridiplantae proteins to six chloroplastic sub-compartments.
Article in Bioinformatics (Oxford, England), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 23 citations in OpenAlex.
- Comprehensive Prediction of Protein Localization and Signal Peptides Using MULocDeep.Methods in molecular biology (Clifton, N.J.) · 2025Article
- MULocDeep web service for protein localization prediction and visualization at subcellular and suborganellar levels.Nucleic acids research · 2023Article
- Prediction of protein subplastid localization and origin with PlastoGram.Scientific reports · 2023Article
- The genome of a nonphotosynthetic diatom provides insights into the metabolic shift to heterotrophy and constraints on the loss of photosynthesis.The New phytologist · 2021Article
- Improving Protein Subcellular Location Classification by Incorporating Three-Dimensional Structure Information.Biomolecules · 2021Article
- MULocDeep: A deep-learning framework for protein subcellular and suborganellar localization prediction with residue-level interpretation.Computational and structural biotechnology journal · 2021Article
- Computational methods for protein localization prediction.Computational and structural biotechnology journal · 2021Review
- Light attention predicts protein location from the language of life.Bioinformatics advances · 2021Article
- Use of Chou's 5-steps rule to predict the subcellular localization of gram-negative and gram-positive bacterial proteins by multi-label learning based on gene ontology annotation and profile alignment.Journal of integrative bioinformatics · 2020Article
- Tools for the Recognition of Sorting Signals and the Prediction of Subcellular Localization of Proteins From Their Amino Acid Sequences.Frontiers in genetics · 2020Review
- DeepMito: accurate prediction of protein sub-mitochondrial localization using convolutional neural networks.Bioinformatics (Oxford, England) · 2020Article
- Benchmarking subcellular localization and variant tolerance predictors on membrane proteins.BMC genomics · 2019Article
- BUSCA: an integrative web server to predict subcellular localization of proteins.Nucleic acids research · 2018Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Motivation: Chloroplasts are organelles found in plants and involved in several important cell processes. Similarly to other compartments in the cell, chloroplasts have an internal structure comprising several sub-compartments, where different proteins are targeted to perform their functions. Given the relation between protein function and localization, the availability of effective computational tools to predict protein sub-organelle localizations is crucial for large-scale functional studies. Results: In this paper we present SChloro, a novel machine-learning approach to predict protein sub-chloroplastic localization, based on targeting signal detection and membrane protein information. The proposed approach performs multi-label predictions discriminating six chloroplastic sub-compartments that include inner membrane, outer membrane, stroma, thylakoid lumen, plastoglobule and thylakoid membrane. In comparative benchmarks, the proposed method outperforms current state-of-the-art methods in both single- and multi-compartment predictions, with an overall multi-label accuracy of 74%. The results demonstrate the relevance of the approach that is eligible as a good candidate for integration into more general large-scale annotation pipelines of protein subcellular localization. Availability and Implementation: The method is available as web server at http://schloro.biocomp.unibo.it Contact: gigi@biocomp.unibo.it.
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