ArticlePLoS computational biology2005
Refining protein subcellular localization.
Article in PLoS computational biology, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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Who cites it
60 citing papers in PubMed.
- SPSignal: a web tool for structure-assisted prediction of nuclear localization and nuclear export signals in proteins.Nucleic acids research · 2026Article
- PTEN Subcellular Localization Dictates Function.bioRxiv : the preprint server for biology · 2026Article
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- Complete NUB1 depletion in ER - negative breast cancer progression in paired primary-metastatic cases: a case series.Journal of medical case reports · 2026Article
- Proteome Analysis of Spermathecal Fluid and Seminal Plasma Reveals the Mechanism of Sperm Storage inAnimals : an open access journal from MDPI · 2025Article
- Ion channel traffic jams: the significance of trafficking deficiency in long QT syndrome.Cell discovery · 2025Review
- Druggable proteins ofFrontiers in pharmacology · 2025Article
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- The small tumor antigen of Merkel cell polyomavirus accomplishes cellular transformation by uniquely localizing to the nucleus despite the absence of a known nuclear localization signal.Virology journal · 2024Article
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- An integrated in-silico approach for drug target identification in human pathogen Shigella dysenteriae.PloS one · 2024Article
- Comprehensive Analysis and Functional Verification of theInternational journal of molecular sciences · 2023Article
- Integrated Bioinformatics-Based Subtractive Genomics Approach to Decipher the Therapeutic Drug Target and Its Possible Intervention against Brucellosis.Bioengineering (Basel, Switzerland) · 2022Article
- TritiKBdb: A Functional Annotation Resource for Deciphering the Complete Interaction Networks in Wheat-Karnal Bunt Pathosystem.International journal of molecular sciences · 2022Article
- Neurotropic RNA Virus Modulation of Immune Responses within the Central Nervous System.International journal of molecular sciences · 2022Review
- Functional Analysis of Hypothetical Proteins ofBioinformatics and biology insights · 2022Article
- Genome-Wide Identification and Analysis of the Polycomb Group Family inInternational journal of molecular sciences · 2021Article
- Genome-Based Drug Target Identification in Human PathogenFrontiers in genetics · 2021Article
- Protein Subcellular Localization Prediction.Methods in molecular biology (Clifton, N.J.) · 2021Article
- HumDLoc: Human Protein Subcellular Localization Prediction Using Deep Neural Network.Current genomics · 2020Article
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The study of protein subcellular localization is important to elucidate protein function. Even in well-studied organisms such as yeast, experimental methods have not been able to provide a full coverage of localization. The development of bioinformatic predictors of localization can bridge this gap. We have created a Bayesian network predictor called PSLT2 that considers diverse protein characteristics, including the combinatorial presence of InterPro motifs and protein interaction data. We compared the localization predictions of PSLT2 to high-throughput experimental localization datasets. Disagreements between these methods generally involve proteins that transit through or reside in the secretory pathway. We used our multi-compartmental predictions to refine the localization annotations of yeast proteins primarily by distinguishing between soluble lumenal proteins and soluble proteins peripherally associated with organelles. To our knowledge, this is the first tool to provide this functionality. We used these sub-compartmental predictions to characterize cellular processes on an organellar scale. The integration of diverse protein characteristics and protein interaction data in an appropriate setting can lead to high-quality detailed localization annotations for whole proteomes. This type of resource is instrumental in developing models of whole organelles that provide insight into the extent of interaction and communication between organelles and help define organellar functionality.
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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.