Computational and Mathematical Biophysics

Aims & Scope

Computational and Mathematical Biophysics publishes original articles, letters, and reviews that concern the application of computational and mathematical approaches to important problems in molecular bioscience and biophysics, such as biomolecular structure and function, solvation, electrostatics, biomolecular dynamics and transport, ion channels, membrane transporters, protein interactions with ligands, proteins, and nucleic acids, signaling, genomic biophysics, cryo-electron microscopy, molecular motors, and rational drug design. Theoretical, computational, and mathematical studies, that can improve the understanding of experimental results or simulate systems for which experiments are intractable, are particularly welcomed. Studies of molecular bioscience and biophysics from all areas of computational and mathematical sciences are appropriate, including differential equations, functional analysis, harmonic analysis, Lie group, Lie algebra, geometry, graph theory, topology, multiscale modeling, inverse problem, optimization, stochastic analysis, uncertainty quantification, statistical inference, nonparametric regression, imaging, visualization, linear programming, combinatorics, fuzzy logic, Monte Carlo, molecular dynamics, machine learning, manifold learning, data mining, big data analysis, high-performance computing, software and database development.

A twelfth criterion — whether APC fees are clearly disclosed — is not scored here; it is left out of the total rather than counted as a failure. Publication charges appear in the metrics card above.

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Subject Classification