Journal Guide

Computational Statistics (CompStat) is an international journal that fosters the publication of applications and methodological research in the field of computational statistics. The journal provides a forum for computer scientists, mathematicians, and statisticians working in a variety of areas in statistics, including biometrics, econometrics, data analysis, graphics, simulation, algorithms, knowledge-based systems, and Bayesian computing. CompStat papers emphasize the contribution to and influence of computing on statistics and vice versa. The journal also publishes hardware, software, and package reports as well as book reviews.Officially cited as: Comput Stat

Computational Statistics & Data Analysis (CSDA), the official journal of the International Association of Statistical Computing (IASC), is an international journal dedicated to the dissemination of methodological research and applications in the areas of computational statistics and data analysis. The journal consists of three refereed sections, and a fourth section dedicated to news on statistical computing. The refereed sections are divided into the following subject areas:I) Computational Statistics - Manuscripts dealing with: 1) the explicit impact of computers on statistical methodology (e.g., Bayesian computing, bioinformatics, computational econometrics, computer graphics, computer intensive inferential methods, data exploration, data mining, expert systems, heuristics, knowledge based systems, machine learning, neural networks, numerical and optimization methods, parallel computing, statistical databases, statistical systems), and 2) the development, evaluation and validation of statistical software and algorithms. Software and algorithms can be submitted with manuscripts and will be stored together with the online article.II) Statistical Methodology for Data Analysis - Manuscripts dealing with novel and original data analytical strategies and methodologies applied in biostatistics (design and analytic methods for clinical trials, epidemiological studies, statistical genetics, or genetic/environmental interactions), chemometrics, classification, data exploration, density estimation, design of experiments, econometrics, environmetrics, education, image analysis, marketing, model free data exploration, pattern recognition, psychometrics, statistical physics, image processing, robust procedures.Statistical methodology includes, but not limited to: bootstrapping, classification techniques, clinical trials, data exploration, density estimation, design of experiments, pattern recognition/image analysis, parametric and nonparametric methods, statistical genetics, Bayesian modeling, outlier detection, robust procedures, cross-validation, functional data, fuzzy statistical analysis, mixture models, model selection and assessment, nonlinear models, partial least squares, latent variable models, structural equation models, supervised learning, signal extraction and filtering, time-series modelling, longitudinal analysis, multilevel analysis and quality control.III) Special Applications - Manuscripts at the interface of statistics and computing (e.g., comparison of statistical methodologies, computer-assisted instruction for statistics, simulation experiments). Advanced statistical analysis with real applications (economics, social sciences, marketing, psychometrics, chemometrics, signal processing, finance, medical statistics, environmentrics, statistical physics).

Computational & Applied Mathematics began to be published in 1981. This journal was conceived as the main scientific publication of SBMAC (Brazilian Society of Computational and Applied Mathematics).   The objective of the journal is the publication of original research in Applied and Computational Mathematics, with interfaces in Physics, Engineering, Chemistry, Biology, Operations Research, Statistics, Social Sciences and Economy. The journal has the usual quality standards of scientific international journals and we aim high level of contributions in terms of originality, depth and relevance. CAM is currently reviewed in Mathematical Reviews and Institute of Scientific Information (Webofscience).  

Computational & Mathematical Organization Theory has been accepted for Social Sciences Citation Index, Science Citation Index Expanded, and Current Contents/Social & Behavioral Sciences, and will first appear with an Impact Factor in the Journal Citation Reports 2010, published in 2011. Computational & Mathematical Organization Theory provides an international forum for interdisciplinary research that combines computation, organizations and society. The goal is to advance the state of science in formal reasoning, analysis, and system building drawing on and encouraging advances in areas at the confluence of social networks, artificial intelligence, complexity, machine learning, sociology, business, political science, economics, and operations research. The papers in this journal will lead to the development of newtheories that explain and predict the behaviour of complex adaptive systems, new computational models and technologies that are responsible to society, business, policy, and law, new methods for inte

Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).The following are the principal areas of interest of the journal:Modeling using PDEs.Analysis of mathematical models, formulated in terms of PDEs.Discretization Methods and Numerical Analysis for PDEs.Numerical linear and nonlinear algebra. Fast numerical algorithms.Algorithms and Data Structures. Adaptivity. Computational Geometry.Software Design, Code verification and Quality Assurance (QA).Verification and Validation.Benefits to authorsWe also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our support pages: http://support.elsevier.com

Computing publishes original papers, short communications and surveys on all fields of computing. The contributions should be written in English and may be of theoretical or applied nature, the essential criteria are computational relevance and systematic foundation of results.
Subjects include
- autonomic, adaptive, dependable computing
- parallel computing
- services computing and cloud computing
- green computing
- internet computing
- business process computing
- software evolution and mining
- architectural concepts for systems
- network science, social networks, collective intelligence

Constructive Approximation is an international mathematics journal dedicated to Approximations and Expansions and related research in computation, function theory, functional analysis, interpolation spaces and interpolation of operators, numerical analysis, space of functions, special functions, and applications.

Current Bioinformatics aims to publish all the latest and outstanding developments in bioinformatics. Each issue contains a series of timely, in-depth reviews, drug clinical trial studies and guest edited thematic issues written by leaders in the field, covering a wide range of the integration of biology with computer and information science.

Digital Discovery welcomes both experimental and computational work on all topics related to the acceleration of discovery such as screening, robotics, databases and advanced data analytics, broadly defined, but anchored in chemistry. The journal welcomes Artificial intelligence and data science methodologies for chemical, materials science, biochemical, biomedical or biophysical sciences including Computer-assisted retrosynthesis, Generative models for scientific design, Machine learning classification and regression models, Modern molecular, materials, and biological representations, Methods for Bayesian optimization and design of experiments, Advances and applications of interpretable models, Image recognition, Natural language processing, Literature mining tools, Advanced data workflows, Advances in robotics for science, Experimental control software, Databases, New robotic setups, New automated sensors, Novel synthetic methodologies and workflows, High-throughput computational science, Directed or accelerated evolution, DNA Encoded Library Technology, Cryptochemistry, and Blockchain-enabled science.

Dynamic Games and Applications is devoted to the development of all classes of dynamic games, namely, differential games, discrete-time dynamic games, evolutionary games, repeated and stochastic games, and their applications in all fields, including:* biology:* computer science:* ecology:* economics:* engineering:* management science:* operations research:* political science:* psychology. DGAA seeks original research that makes significant methodological, conceptual, algorithmic, or empirical contributions to various disciplines. DGAA also considers work in static game theory and dynamic optimization provided that authors establish a clear, potential link to dynamic games. DGAA publishes regular papers, technical notes, survey articles, and case studies.All submissions should be original in nature. During the peer review process, to promote scientific honesty and high standards, submitted manuscripts go through one or more revision stages leading up to acceptance or rejection.  Each paper is reviewed by at least two experts in the field.

EPJ Data Science is a peer-reviewed open access journal published under the SpringerOpen brand.

Data-driven science is rapidly emerging as a complementary approach to the traditional hypothesis-driven method. This revolution accompanying the paradigm shift from reductionism to complex systems sciences has already largely transformed the natural sciences and is about to bring the same changes to the techno-socio-economic sciences, viewed broadly. The journal EPJ Data Science addresses the challenges of the data revolution across academic disciplines: ·         how to extract meaningful data from systems with ever-increasing complexity·         how to analyze data in ways that inspire new insights·         how to generate data that is needed but not yet available·         how to develop new empirical laws, or more fundamental theories, concerning the function of complex natural or artificial systems EPJ Data Science spans a broad range of research areas and applications with a focus on social systems, where it comprises those research lines that regard digital traces of human behavior as first-order objects for scientific investigation. This includes human and animal social behavior and interaction, economic and financial systems, management and business networks, socio-technical infrastructure, health and environmental systems, the science of science, as well as general risk and crisis scenario forecasting.

ESAIM: COCV publishes rapidly and efficiently papers and surveys in the areas of control, optimisation and calculus of variations. Articles may be theoretical,computational, or both, and they will cover contemporary subjects with impact on forefront technology, biosciences, materials science, computer vision, continuum physics, decision sciences and other allied disciplines.

The journal publishes original research papers of high scientific quality in two areas: Mathematical Modelling, and Numerical Analysis. Mathematical Modelling comprises the development and study - e.g. structure, well-posedness, solution properties - of a mathematical formulation of a problem (or class of problems). Numerical Analysis comprises the formulation and study - e.g. stability, convergence, computational complexity - of a numerical approximation or solution approach to a mathematically formulated problem (or class of problems).

This journal is specifically dedicated to the dissemination of the latest developments of new engineering analysis techniques using boundary elements and other mesh reduction methods.Boundary element (BEM) and mesh reduction methods (MRM) are very active areas of research with the techniques being applied to solve increasingly complex problems. The journal stresses the importance of these applications as well as their computational aspects, reliability and robustness.The main criteria for publication will be the originality of the work being reported, its potential usefulness and applications of the methods to new fields.In addition to regular issues, the journal publishes a series of special issues dealing with specific areas of current research.The journal has, for many years, provided a channel of communication between academics and industrial researchers working in mesh reduction methodsFields Covered:• Boundary Element Methods (BEM)• Mesh Reduction Methods (MRM)• Meshless Methods• Integral Equations• Applications of BEM/MRM in Engineering• Numerical Methods related to BEM/MRM• Computational Techniques• Combination of Different Methods• Advanced FormulationsRelated Conferences:Conferences with links to websites, are listed under Related websites.

g the exchange of information among researchers involved in both the theoretical and practical aspects of computational systems drawing their inspiration from nature. Particular emphasis is placed on evolutionary models of computation such as genetic algorithms (GA), evolutionary strategies (ES), classifier systems (CS), evolutionary programming (EP), genetic programming (GP), and related fields such as swarm intelligence (Ant Colony Optimization and Particle Swarm Optimization), and other evolutionary computation techniques.