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Scope
The Protein Bioinformatics section publishes high-quality papers in protein bioinformatics, defined as any bioinformatic method primarily aimed at increasing our understanding of the function of proteins.
Scope
• Protein evolution
• Protein structure prediction
• Methods to search databases to identify related protein sequences and structures
• Machine learning and statistical methods utilizing protein sequence information
• Machine learning and statistical methods utilizing protein structural information
• Protein-protein interaction methods
• Statistical methods for understanding protein sequence, structure, function and evolution
• Methods to predict protein function
• Novel benchmark sets providing insights into the performance of widely used search methods
• Databases that can be expected to provide novel insights about proteins
• Software that can be expected to provide novel insights about proteins
Purely computational chemistry methods, such as molecular dynamics simulations, virtual drug-design, ligand docking, applied to a single system are only considered if they provide significantly improved tools or insights that can be generalized for a large number of proteins/protein families.
Methods that primarily apply to the development of machine learning methods are preferably submitted to our sister journal section 'Machine learning and Artificial Intelligence'.
Indexed in: CLOCKSS, CrossRef, DOAJ, Google Scholar, OpenAIRE, Semantic Scholar
PMCID: NA
Protein Bioinformatics welcomes submissions of the following article types: Brief Research Report, Case Report, Correction, Data Report, Editorial, General Commentary, Hypothesis and Theory, Methods, Mini Review, Opinion, Original Research, Perspective, Review, Systematic Review and Technology and Code.
All manuscripts must be submitted directly to the section Protein Bioinformatics, where they are peer-reviewed by the Associate and Review Editors of the specialty section.
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