ArticleNucleic acids research2011
Update of PROFEAT: a web server for computing structural and physicochemical features of proteins and peptides from amino acid sequence.
Article in Nucleic acids research, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.
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Who cites it
54 citing papers in PubMed, 1 synthesis or guideline pooled it.
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- LocPro: A deep learning-based prediction of protein subcellular localization for promoting multi-directional pharmaceutical research.Journal of pharmaceutical analysis · 2025Article
- Multimodal deep learning for allergenic proteins prediction.BMC biology · 2025Article
- BloodProST: prediction of blood-secretory proteins through self-training.Briefings in bioinformatics · 2025Article
- APBIO: bioactive profiling of air pollutants through inferred bioactivity signatures and prediction of novel target interactions.Journal of cheminformatics · 2025Article
- The genome of the polyextremophilic yeast, Naganishia friedmannii, reveals adaptations involved in stress response pathways, carbohydrate metabolism expansion, and a limited DNA repair repertoire.FEMS yeast research · 2025Article
- PLMC: Language Model of Protein Sequences Enhances Protein Crystallization Prediction.Interdisciplinary sciences, computational life sciences · 2024Article
- iNP_ESM: Neuropeptide Identification Based on Evolutionary Scale Modeling and Unified Representation Embedding Features.International journal of molecular sciences · 2024Article
- AnnoPRO: a strategy for protein function annotation based on multi-scale protein representation and a hybrid deep learning of dual-path encoding.Genome biology · 2024Article
- A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder.Nucleic acids research · 2023Article
- Prediction of Cholecystokinin-Secretory Peptides Using Bidirectional Long Short-term Memory Model Based on Transfer Learning and Hierarchical Attention Network Mechanism.Biomolecules · 2023Article
- RNAincoder: a deep learning-based encoder for RNA and RNA-associated interaction.Nucleic acids research · 2023Article
- Prediction of Proteins in Cerebrospinal Fluid and Application to Glioma Biomarker Identification.Molecules (Basel, Switzerland) · 2023Article
- The applications of deep learning algorithms on in silico druggable proteins identification.Journal of advanced research · 2022Article
- iFeatureOmega: an integrative platform for engineering, visualization and analysis of features from molecular sequences, structural and ligand data sets.Nucleic acids research · 2022Article
- Response to Cold: A Comparative Transcriptomic Analysis in Eight Cold-Adapted Yeasts.Frontiers in microbiology · 2022Article
- A genomic approach to analyze the cold adaptation of yeasts isolated from Italian Alps.Frontiers in microbiology · 2022Article
- Phage_UniR_LGBM: Phage Virion Proteins Classification with UniRep Features and LightGBM Model.Computational and mathematical methods in medicine · 2022Article
Corrections and comments
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5 authors.
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Abstract
Sequence-derived structural and physicochemical features have been extensively used for analyzing and predicting structural, functional, expression and interaction profiles of proteins and peptides. PROFEAT has been developed as a web server for computing commonly used features of proteins and peptides from amino acid sequence. To facilitate more extensive studies of protein and peptides, numerous improvements and updates have been made to PROFEAT. We added new functions for computing descriptors of protein-protein and protein-small molecule interactions, segment descriptors for local properties of protein sequences, topological descriptors for peptide sequences and small molecule structures. We also added new feature groups for proteins and peptides (pseudo-amino acid composition, amphiphilic pseudo-amino acid composition, total amino acid properties and atomic-level topological descriptors) as well as for small molecules (atomic-level topological descriptors). Overall, PROFEAT computes 11 feature groups of descriptors for proteins and peptides, and a feature group of more than 400 descriptors for small molecules plus the derived features for protein-protein and protein-small molecule interactions. Our computational algorithms have been extensively tested and used in a number of published works for predicting proteins of specific structural or functional classes, protein-protein interactions, peptides of specific functions and quantitative structure activity relationships of small molecules. PROFEAT is accessible free of charge at http://bidd.cz3.nus.edu.sg/cgi-bin/prof/protein/profnew.cgi.
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