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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.,
) 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
is a pendant to
(in the living system) and
(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: Laccases are industrially attractive enzymes and their applications have expanded to the field of bioremediation. The challenge of today's biotechnology in enzymatic studies is to design enzymes that not only have a higher activity but are also more stable and could fit well with the condition requirements. Laccases are known to oxidize non-natural substrates like polycyclic aromatic hydrocarbons (PAHs). We suppose by increasing the hydrophobicity of laccase, it would increase the chance of the enzyme to…meet the hydrophobic substrates in a contamination site, therefore increasing the bioremediation efficacy of PAHs from environment. In this attempt, the applications of evolutionary trace (ET), molecular surface accessibility and hydrophobicity analysis on laccase sequences and laccase's crystal structure (1KYA) are described for optimal design of an enzyme with higher hydrophobicity. Our analysis revealed that Q23A, Q45I, N141A, Q237V, N262L, N301V, N331A, Q360L and Q482A could be promising exchanges to be tested in mutagenesis experiments.
Abstract: Bacterial small RNAs (sRNAs) have gained considerable attention due to their multivalent roles in the survival and pathogenesis of bacteria and mostly identified through bio-computational methods. A manually curated web-resource, sRNAbase has been constructed to give comprehensive and exhaustive information on non-coding small RNAs excluding tRNAs and rRNAs in Enterobacteriaceae family. The sRNA entries curated in sRNAbase contain experimentally verified small RNAs available in the literature and their partial/non-homologs reported within the…related genomes from our earlier studies. The sRNAbase aims to facilitate the scientific community by providing information on the physical genomic location of the non-coding small RNAs, its alias names, sequences, strand orientation, gene identification numbers of the conserved genes that sandwiches the particular sRNA with possible functional role and a link to the PubMed literatures. Currently, sRNAbase holding information on 1986 entries belongs to 80 sRNA families spread over 45 Enterobacteriaceae genomes. The sRNAbase is accessible on the web at http://bicmku.in:8081/srnabase/.
Abstract: Unlike evolution of genes and proteins, evolution of regulatory systems is a relatively new area of research. In particular, little systematic study has been done on evolution of DNA binding motifs in transcription factor families. We suggest an algorithm that reconstructs the most parsimonious scenario for changes in DNA binding motifs along an evolutionary tree of transcription factor binding sites. The algorithm was validated on several artificial datasets and then applied to reconstruct the evolutionary history…of the NrdR, MntR, LacI, FNR, Irr, Fur and Rrf2 transcription factor families. The algorithm seems to be sufficiently robust to be applicable in realistic situations. In most transcription factor families the changes in binding motifs are limited to several branches. Changes in consensus nucleotides proceed via an intermediate stage when the respective position is not conserved.
Keywords: Evolutionary scenario, regulatory signal, frequency matrix, evolution along a tree, transcription factor tree
Abstract: Under physiological conditions, many proteins that include a region lacking well-defined three-dimensional structures have been identified, especially in eukaryotes. These regions often play an important biological cellular role, although they cannot form a stable structure. Therefore, they are biologically remarkable phenomena. From an industrial perspective, they can provide useful information for determining three-dimensional structures or designing drugs. For these reasons, disordered regions have attracted a great deal of attention in recent years.…Their accurate prediction is therefore anticipated to provide annotations that are useful for wide range of applications. POODLE-I (where "I" stands for integration) is a web-based disordered region prediction system. POODLE-I integrates prediction results obtained from three kinds of disordered region predictors (POODLEs) developed from the viewpoint that the characteristics of disordered regions change according to their length. Furthermore, POODLE-I combines that information with predicted structural information by application of a workflow approach. When compared with server teams that showed best performance in CASP8, POODLE-I ranked among the top and exhibited the highest performance in predicting unfolded proteins. POODLE-I is an efficient tool for detecting disordered regions in proteins solely from the amino acid sequence. The application is freely available at http://mbs.cbrc.jp/poodle/poodle-i.html.
Abstract: Background: In the field of bioinformatics interchangeable data formats based on XML are widely used. XML-type data is also at the core of most web services. With the increasing amount of data stored in XML comes the need for storing and accessing the data. In this paper we analyse the suitability of different database systems for storing and querying large datasets in general and Medline in particular. Results: All reviewed database systems perform well when…tested with small to medium sized datasets, however when the full Medline dataset is queried a large variation in query times is observed. Conclusions: There is not one system that is vastly superior to the others in this comparison and, depending on the database size and the query requirements, different systems are most suitable. The best all-round solution is the Oracle 11~g database system using the new binary storage option. Alias-i's Lingpipe is a more lightweight, customizable and sufficiently fast solution. It does however require more initial configuration steps. For data with a changing XML structure Sedna and BaseX as native XML database systems or MySQL with an XML-type column are suitable.