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In Silico Biology - Volume 11, issue 5-6

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Price: EUR N/A
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.
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Molecular modeling and docking analysis of Beta-lactamases with inhibitors: A comparative study

Authors: Danishuddin, Mohd | Khan, Asad U.

Article Type: Research Article

Abstract: Beta-lactamases are bacterial enzymes which impart resistance against β-lactam-antibiotics. CTX-Ms are the β-lactamases that target cephalosporin antibiotics (e.g. cefotaxime and ceftazidime) while SME-1, KPC-2, IMI-1 and SFC-1 target carbapenems. Clavulanic acid, sulbactam and tazobactam are traditional β-lactamase inhibitors while LN1-255 and NXL-104 whereas novel inhibitors, inhibiting the activity of these enzymes. Studying the binding pattern of these drugs is helpful in predicting the versatile inhibitors for betalactamases. The aims of the study were: describing the mode of interaction of CTX-M (modeled from the bla CTX-M gene of this study) and the said carbapenemases with their respective target drugs and … Show more

Keywords: Carbapenemases, docking, inhibitors, modelling, multidrug resistance

DOI: 10.3233/ISB-2012-0443

Citation: In Silico Biology, vol. 11, no. 5-6, pp. 273-280, 2012

Price: EUR 27.50

miRNA-mRNA network detects hub mRNAs and cancer specific miRNAs in lung cancer

Authors: Devaraj, Saranya | Natarajan, Jeyakumar

Article Type: Research Article

Abstract: MicroRNA expression profiles can improve classification, diagnosis, and prognostic information of malignancies, including lung cancer. In this paper, we undertook to develop a miRNA-mRNA network and uncover unique growth suppressive miRNAs in lung cancer using microarray data. The miRNA-mRNA network was developed based on a bipartite graph theory approach, and a number of miRNA-mRNA modules have been identified to mine associations between miRNAs and mRNAs. From the network, we identified totally 29 protective miRNA-mRNA regulatory modules, since we restricted our search to protective miRNAs. Subsequently we analyzed the pathways for the target genes in the protective miRNA-mRNA modules using Pathway-Express. … Show more

Keywords: miRNA-mRNA network, lung cancer, protective miRNAs

DOI: 10.3233/ISB-2012-0444

Citation: In Silico Biology, vol. 11, no. 5-6, pp. 281-295, 2012

Price: EUR 27.50
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