ArticleBMC genomics2008
The FEATURE framework for protein function annotation: modeling new functions, improving performance, and extending to novel applications.
Article in BMC genomics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers.
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Who cites it
39 citing papers in PubMed.
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- Unsupervised learning reveals landscape of local structural motifs across protein classes.Bioinformatics (Oxford, England) · 2025Article
- FeatureDock for protein-ligand docking guided by physicochemical feature-based local environment learning using transformer.npj drug discovery · 2025Article
- RNA-protein interaction prediction without high-throughput data: An overview and benchmark ofComputational and structural biotechnology journal · 2024Article
- Enhancing Missense Variant Pathogenicity Prediction with MissenseNet: Integrating Structural Insights and ShuffleNet-Based Deep Learning Techniques.Biomolecules · 2024Article
- ProNet DB: a proteome-wise database for protein surface property representations and RNA-binding profiles.Database : the journal of biological databases and curation · 2024Article
- Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data.BMC bioinformatics · 2024Article
- Predicting the pathogenicity of missense variants using features derived from AlphaFold2.Bioinformatics (Oxford, England) · 2023Article
- BindWeb: A web server for ligand binding residue and pocket prediction from protein structures.Protein science : a publication of the Protein Society · 2022Article
- Defining A Global Map of Functional Group-based 3D Ligand-binding Motifs.Genomics, proteomics & bioinformatics · 2022Article
- Protein-RNA interaction prediction with deep learning: structure matters.Briefings in bioinformatics · 2022Article
- Quantifying structural relationships of metal-binding sites suggests origins of biological electron transfer.Science advances · 2022Article
- ResiRole: residue-level functional site predictions to gauge the accuracies of protein structure prediction techniques.Bioinformatics (Oxford, England) · 2021Article
- Huntingtin: A Protein with a Peculiar Solvent Accessible Surface.International journal of molecular sciences · 2021Article
- Review of Machine Learning Methods for the Prediction and Reconstruction of Metabolic Pathways.Frontiers in molecular biosciences · 2021Review
- Rhapsody: predicting the pathogenicity of human missense variants.Bioinformatics (Oxford, England) · 2020Article
- A deep learning framework to predict binding preference of RNA constituents on protein surface.Nature communications · 2019Article
- Prediction of Enzyme Function Based on Three Parallel Deep CNN and Amino Acid Mutation.International journal of molecular sciences · 2019Article
- Informatics and Computational Methods in Natural Product Drug Discovery: A Review and Perspectives.Frontiers in genetics · 2019Review
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Authors and funding
4 authors.
Funding
Abstract
Structural genomics efforts contribute new protein structures that often lack significant sequence and fold similarity to known proteins. Traditional sequence and structure-based methods may not be sufficient to annotate the molecular functions of these structures. Techniques that combine structural and functional modeling can be valuable for functional annotation. FEATURE is a flexible framework for modeling and recognition of functional sites in macromolecular structures. Here, we present an overview of the main components of the FEATURE framework, and describe the recent developments in its use. These include automating training sets selection to increase functional coverage, coupling FEATURE to structural diversity generating methods such as molecular dynamics simulations and loop modeling methods to improve performance, and using FEATURE in large-scale modeling and structure determination efforts.
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