Aims & Scope
In Silico Biology is a scientific research journal for the advancement of computational models and simulations applied to complex biological phenomena. We publish peer-reviewed leading-edge biological, biomedical and biotechnological research in which computer-based (i.e., "in silico") modeling and analysis tools are developed and utilized to predict and elucidate dynamics of biological systems, their design and control, and their evolution. Experimental support may also be provided to support the computational analyses.
In Silico Biology aims to advance the knowledge of the principles of organization of living systems. We strive to provide computational frameworks for understanding how observable biological properties arise from complex systems. In particular, we seek for integrative formalisms to decipher cross-talks underlying systems level properties, ultimate aim of multi-scale models.
Studies published in In Silico Biology generally use theoretical models and computational analysis to gain quantitative insights into regulatory processes and networks, cell physiology and morphology, tissue dynamics and organ systems. Areas of interest include signal transduction and information processing, gene expression and gene regulatory networks, metabolism, proliferation, differentiation and morphogenesis, among others. Multi-scale modeling to connect molecular and cellular systems to the level of organisms and populations, interface between -omics integration and modeling, and development of algorithms for modeling purposes are of particular interest.
In Silico Biology also publishes foundational research in which novel algorithms are developed to facilitate modeling and simulations. Such research must demonstrate application to a concrete biological problem.
In Silico Biology frequently publishes special issues on seminal topics and trends. Special issues are handled by Special Issue Editors appointed by the Editor-in-Chief. Proposals for special issues should be sent to the Editor-in-Chief.
About In Silico Biology
The term "in silico" is a pendant to "in vivo" (in the living system) and "in vitro" (in the test tube) biological experiments, and implies the gain of insights by computer-based simulations and model analyses.
In Silico Biology (ISB) was founded in 1998 as a purely online journal. IOS Press became the publisher of the printed journal shortly after. Today, ISB is dedicated exclusively to biological systems modeling and multi-scale simulations and is published solely by IOS Press. The previous online publisher, Bioinformation Systems, maintains a website containing studies published between 1998 and 2010 for archival purposes.
We strongly support open communications and encourage researchers to share results and preliminary data with the community. Therefore, results and preliminary data made public through conference presentations, conference proceeding or posting of unrefereed manuscripts on preprint servers will not prohibit publication in ISB. However, authors are required to modify a preprint to include the journal reference (including DOI), and a link to the published article on the ISB website upon publication.
Mads Kaern, PhD
Jack Leunissen †
Diego di Bernardo
David Gómez Míguez
Academic Source Complete
Chemical Abstracts Service
Chemical Abstracts Service (CAS)
Microsoft Academic Search
Ulrich's Periodicals Directory
Web of Science: Biological Abstracts
Web of Science: BIOSIS Previews
Mailings & Sign Ups: If you do not already receive the ISB newsletter, we invite you to sign up to receive notification of new ISB issues, plus other related news. Sign up via this link. You can read the latest newsletter here.
Free open access will be provided to all papers submitted for review prior to Dec 31, 2021.
Please also visit the In Silico Biology website: www.insilicobiologyjournal.com
Discover the contents of the latest journal issue:
Cancer immunoediting: A game theoretical approach
Javad Salimi Sartakhti, Fatemeh Tavakoli, Mohammad Hossein Manshaei, David Basanta
Modeling and characterization of inter-individual variability in CD8 T cell responses in mice
Daphné Laubreton, Chloe Audebert, Christophe Arpin, Olivier Gandrillon, Jacqueline Marvel, Fabien Crauste
A computational framework for finding parameter sets associated with chaotic dynamics
E. Dimitrova, S. Koshy-Chenthittayil, E.W. Jenkins, B.C. Dean