Computational Science & Discovery

IOP Publishing

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About the journal

Computational Science & Discovery is a journal published by IOP Publishing in United Kingdom. It is listed in PUBMED according to the sources read. Facts are reproduced as recorded at their sources with their capture dates; PublishLens indicators are available after sign-in.

Basic facts

Publisher
IOP Publishing
ISSN
1749-4680 · 1749-4699
Country
United Kingdom
Access
Not open access / not declared

Index listings

  • PUBMED · 2012-03-20
Indexing
PUBMED
APC
—
Declared review time (DOAJ)
—
Activity (OpenAlex)
Dormant — no works recorded since 2015
PublishLens list status
Shown after sign-in
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Methodology signals (dated facts from their sources)

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Journal profile

Descriptive metadata from public sources (DOAJ, OpenAlex, PubMed) as of the capture date shown — contains no assessment or judgment.

Works in OpenAlex

99

Last recorded publication year

2015

Reported by OpenAlex in 1 of 3 sources (CC0 flags, not verified indexing)DOAJSciELOOpenAlex Core

h-index

26

i10-index

55

From OpenAlex open data (CC0).

Editorial & policy4
Observed digital preservation (Keepers registry)— snapshot 2026-10-05
CLOCKSSPortico
Norwegian register (HK-dir)— 2026
Level 1 — approved scholarly channel
Open references deposited at Crossref
0%
ORCID iDs in current deposits
0%
Identity & continuity2
Alternate titles
Computational science and discoveryCSD
Source type
journal
Classification(no data)

No data available to the platform for this group

No platform data for: Classification — absence is not a judgment about the journal.

Subject areas

  • Magnetic confinement fusion research
  • Magnetic confinement fusion research
  • Parallel Computing and Optimization Techniques
  • Parallel Computing and Optimization Techniques
  • Protein Structure and Dynamics
  • Protein Structure and Dynamics
  • Advanced Numerical Methods in Computational Mathematics
  • Computational Physics and Python Applications
Show all subjects (50)
  • Fluid Dynamics and Turbulent Flows
  • Numerical methods for differential equations
  • Computational Physics and Python Applications
  • Advanced Numerical Methods in Computational Mathematics
  • Fluid Dynamics and Turbulent Flows
  • Numerical methods for differential equations
  • Scientific Computing and Data Management
  • Ionosphere and magnetosphere dynamics
  • Scientific Computing and Data Management
  • Distributed and Parallel Computing Systems
  • Ionosphere and magnetosphere dynamics
  • Distributed and Parallel Computing Systems
  • Gas Dynamics and Kinetic Theory
  • Advanced Chemical Physics Studies
  • Combustion and flame dynamics
  • Advanced Data Storage Technologies
  • Computational Fluid Dynamics and Aerodynamics
  • Advanced Data Storage Technologies
  • Solar and Space Plasma Dynamics
  • Solar and Space Plasma Dynamics
  • Computational Fluid Dynamics and Aerodynamics
  • Combustion and flame dynamics
  • Advanced Chemical Physics Studies
  • Gas Dynamics and Kinetic Theory
  • Model Reduction and Neural Networks
  • Laser-Plasma Interactions and Diagnostics
  • Quantum Chromodynamics and Particle Interactions
  • Laser-Plasma Interactions and Diagnostics
  • Model Reduction and Neural Networks
  • Advanced Thermodynamics and Statistical Mechanics
  • Quantum Computing Algorithms and Architecture
  • DNA and Nucleic Acid Chemistry
  • Computational Drug Discovery Methods
  • Quantum Computing Algorithms and Architecture
  • Computational Drug Discovery Methods
  • Quantum Chromodynamics and Particle Interactions
  • Particle accelerators and beam dynamics
  • Nanoparticles: synthesis and applications
  • DNA and Nucleic Acid Chemistry
  • Advanced Thermodynamics and Statistical Mechanics
  • Particle accelerators and beam dynamics
  • Nanoparticles: synthesis and applications

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The journal's record in other sources:Web of Science MJLDOAJ

Everything shown here is produced automatically from named sources (DOAJ, OpenAlex, Crossref, PubMed, the Norwegian register) as of its capture date, with no human editing. Facts appear as recorded at the source; derived scores (PCI, PTD, PublishLens score) follow a published methodology. Not a judgement on the journal, not an official accreditation, not advice.

Wrong items are corrected automatically by re-reading the source (24 h for daily sources, 7 days for weekly ones) with a dated change log, and each item links to its source record. PublishLens-derived assessments are contested through the appeals mechanism (15 working days). Appeals · Indicator guide

Norwegian register data: Kanalregisteret (HK-dir, Norway) — CC BY 4.0 / NLOD — adapted: level extracted per year · OASPA member list — CC BY

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