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ISSN 1386-6338 (P)
ISSN 1434-3207 (E)
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. Special areas of interest include signal transduction and information processing, gene expression and gene regulatory networks, metabolism, proliferation, differentiation and morphogenesis, among others, and the use of multi-scale modeling to connect molecular and cellular systems to the level of organisms and populations.
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.
Abstract: To assess the relevance of molecular markers it is required to combine clinical and genetic information. For reliable assessment of parameters relevant to diagnostics and therapy large patient collectives must be characterized both with respect to phenotype and genotype. Matching of genetic data like gene expression profiles, molecular genetics and cytogenetics with clinical data like follow-up, morphological findings and diagnoses involves integration of complex databases. In the context of a nationwide leukemia…research network in Germany we designed an integrated database covering both genetic and clinical data of patients. The system contains follow-up data and relevant laboratory modalities, i. e. cytomorphology, cytogenetics, molecular genetics, FISH, immunophenotyping and gene expression profiling. So far 13541 cases from 7746 patients treated by 1225 physicians are documented. The data structure consists of up to 888 variables per case. From our experience, integration of clinical and genetic information requires significant efforts - including data protection issues -, but is feasible and improves data quality leading to faster and more reliable research results for the benefit of the patients.
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Abstract: Pattern formation in multicellular spheroids is addressed with a hybrid lattice-gas cellular automaton model. Multicellular spheroids serve as experimental model system for the study of avascular tumor growth. Typically, multicellular spheroids consist of a necrotic core surrounded by rings of quiescent and proliferating tumor cells, respectively. Furthermore, after an initial exponential growth phase further spheroid growth is significantly slowed down even if further nutrient is supplied. The cellular automaton model explicitly takes…into account mitosis, apoptosis and necrosis as well as nutrient consumption and a diffusible signal that is emitted by cells becoming necrotic. All cells follow identical interaction rules. The necrotic signal induces a chemotactic migration of tumor cells towards maximal signal concentrations. Starting from a small number of tumor cells automaton simulations exhibit the self-organized formation of a layered structure consisting of a necrotic core, a ring of quiescent tumor cells and a thin outer ring of proliferating tumor cells.
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Abstract: To gain further knowledge about rare genetic diseases, a world wide method for data collection via the Internet has been established. This new approach will improve collecting valuable data from single case reports. Ramedis saves standardised patient data which will be usable for statistics, longitudinal examinations and cooperative studies in future time. Embedded in the scene of the German Human Genome Project, Ramedis directly will enable phenotype-genotype correlations. Beside the better characterisation of clinical…heterogeneity of rare metabolic diseases, there may be a great benefit for the treatment of these patients in whom prospective studies are otherwise expensive and difficult to perform. This contribution presents the motivation for this system, introduces features, current state and the future of the project. Additionally, first experiences of using Ramedis by health professionals are explained.
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Keywords: case study, database, genotype-phenotype correlation, information system, rare metabolic disease, remote data entry
Abstract: BioPath is a prototype system for the interactive exploration of biochemical pathways. It has been developed as an electronic version of the famous Boehringer Biochemical Pathways map and offers various ways to access information on substances and pathways and to navigate through pathways. This paper describes the main features and the software architecture of BioPath. The companion paper [11] focuses on the advanced visualization incorporated into BioPath.
Abstract: Glycosylated proteins are ubiquitous components of extracellular matrices and cellular surfaces where their oligosaccharide moieties are implicated in a wide range of cellcell and cellmatrix recognition events. Glycans constitute highly flexible molecules. Only a small number of glycan X-ray structures is available for which sufficient electron density for an entire oligosaccharide chain has been observed. An unambiguous structure deter-mination based on NMR-derived geometric constraints alone is often not possible. Time consuming computational…approaches such as Monte Carlo calculations and molecular dynamics simulations have been widely used to explore the conformational space accessible to complex carbohydrates. The generation of a comprehensive data base for N-glycan fragments based on long time molecular dynamics simulations is presented. The fragments are chosen in such a way that the effects of branched N-glycan structures are taken into account. The prediction database consti-tutes the basis of a procedure to generate a complete set of all possible conformations for a given N-glycan. The constructed conformations are ranked according to their energy content. The resulting conformations are in reason-able agreement with experimental data. A web interface has been established (http://www.dkfz.de/spec/glydict/), which enables to input any N-glycan of interest and to receive an ensemble of generated conformations within a few minutes.
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Keywords: conformations of N-glycans, molecular dynamics simulations, database of N-glycan fragments, glycoproteins