Everything about Protein function prediction
Use of bioinformatic methods to correlate proteins with biofunctions
Protein function prediction methods are techniques that bioinformatics researchers use to assign biological or biochemical roles to proteins. These proteins are usually ones that are poorly studied or predicted based on genomic sequence data. These predictions are often driven by data-intensive computational procedures. Information may come from nucleic acid sequence homology, gene expression profiles, protein domain structures, text mining of publications, phylogenetic profiles, phenotypic profiles, and protein-protein interaction. Protein function is a broad term: the roles of proteins range from catalysis of biochemical reactions to transport to signal transduction, and a single protein may play a role in multiple processes or cellular pathways. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Protein function predictionA 5-minute orientation
- Skim a recent paper: Protein function prediction as approximate semantic entailmentInfluential work since 2022
- Pick up a classic book: Bioinformatics Research and ApplicationsThe most-reprinted book on the subject
- Read the landmark paper: Network‐based prediction of protein functionCited 882 times
- Go sideways: Gene predictionA closely related topic
- Go sideways: BioinformaticsA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🏆 Landmark papers (most cited)
Network‐based prediction of protein function
Protein function prediction via graph kernels
Global protein function prediction from protein-protein interaction networks
DeepGOPlus: improved protein function prediction from sequence
Prediction of protein function from protein sequence and structure
Automated protein function prediction--the genomic challenge
Prediction of Protein Function Using Protein–Protein Interaction Data
Automatic prediction of protein function
🆕 Influential since 2022
Protein function prediction as approximate semantic entailment
Hierarchical graph transformer with contrastive learning for protein function prediction
Enhancing Protein Function Prediction Performance by Utilizing AlphaFold-Predicted Protein Structures
Deep learning methods for protein function prediction
PANDA2: protein function prediction using graph neural networks
📚 Books worth reading
Bioinformatics Research and ApplicationsZhipeng Cai · 2013
Campbell biologyLisa A. Urry, Michael L. Cain · 2015
Essential bioinformaticsJin Xiong · 2006
Computational intelligence and pattern analysis in biology informaticsUjjwal Maulik · 2010
Gene discovery for disease modelsWeikuan Gu · 2011
Algorithms in computational molecular biologyMourad Elloumi · 2010
Protein Function Prediction for Omics EraDaisuke Kihara · 2011
Protein structure predictionDaisuke Kihara · 2014
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
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