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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: Transcription is one of the basic processes of gene expression, controlled by a complex network of biochemical reactions. Despite its importance, most work on the visualisation of biochemical networks focuses on the representation of metabolic pathways. The visualisation of the complex networks controlling transcription requires the implementation of a hierarchical approach that allows the display of the structure of each regulatory region with its transcription factors and regulated operons. This paper presents…a web-based application for the visualisation of transcriptional control networks. It takes as case study the organism Escherichia coli. The definition of the visual components implemented is mainly based on those proposed by Shen-Orr et al., 2002, slightly extended to visualise complex networks.
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Abstract: We performed a detailed bioinformatic study of the catalytic step of fructose-6-phosphate phosphorylation in glycolysis based on the raw genomic draft of Propionibacterium freudenreichii subsp. shermanii (P. shermanii) ATCC9614 [Meurice et al., 2004]. Our results provide the first in silico evidence of the coexistence of genes coding for an ATP-dependent phosphofructokinase (ATP-PFK) and a PPi-dependent phosphofructokinase (PPi-PFK), whereas the fructose-1,6-bisphosphatase (FBP) and ADP-dependent phosphofructokinase (ADP-PFK) are absent. The deduced amino acid sequence…corresponding to the PPi-PFK (AJ508922) shares 100% similarity with the already characterised propionibacterial protein (P29495; Ladror et al., 1991]. The unexpected ATP-PFK gene (AJ509827) encodes a protein of 373 aa which is highly similar (50% positive residues) along at least 95% of its sequence length to different well-characterised ATP-PFKs. The characteristic PROSITE pattern important for the enzyme function of ATP-PFKs (PS00433) was conserved in the putative ATP-PFK sequence: 8 outof.
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Abstract: Pathogen recognition and signal transduction during plant pathogenesis is essential for the activation of plant defense mechanisms. To facilitate easy access to published data and to permit comparative studies of different pathogen response pathways, a database is indispensable to give a broad overview of the components and reactions so far known. PathoPlant® has been developed as a relational database to display relevant components and reactions involved in signal transduction related to plant-pathogen…interactions. On the organism level, the tables 'plant', 'pathogen' and 'interaction' are used to describe incompatible interactions between plants and pathogens or diseases. On the molecular level, plant pathogenesis related information is organized in PathoPlant's main tables 'molecule', 'reaction' and 'location'. Signal transduction pathways are modeled as consecutive sequences of known molecules and corresponding reactions. PathoPlant entries are linked to associated internal records as well as to entries in external databases such as SWISS-PROT, GenBank, PubMed, and TRANSFAC®. PathoPlant is available as a web-based service at http://www.pathoplant.de.
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Keywords: database, plant, pathogen, phytopathogen, interaction, signal transduction, signal perception, pathway, virulence, resistance, susceptibility, avirulence factor, plant defense
Abstract: The Drosophila H2A-H2B histone spacer, a small region that functions as a bidirectional promoter for the gene pair, was used as a test sequence for generation of a computationally derived organizational model of transcription factor (TF) binding sites. Expression studies of the spacer revealed that it contains the necessary sequences to confer replication-dependent transcription in partially synchronized cells in culture. Informatics analysis of the spacer uncovered a number of binding sites for specific TFs, none of…which had been previously associated with this particular promoter. Each of the TFs in the promoter organizational model are also known to participate in stages of fly development that are characterized by DNA replication and/or cell division, thus providing a biologically functional rationale for an association. Moreover, phylogenetic analysis of the binding sites provides evidence for evolutionary conservation of the essential features of the organizational model. The model, if correct, provides information about the molecules that couple developmental specific demands and histone gene transcription.
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Abstract: Porins are outermembrane β-barrel proteins. They have varied biological functionality ranging from phage receptors, immunogenicity, pathogenicity to apoptosis. However, only a small number has been structurally and functionally characterised. A validation mechanism and a database of porins would be useful for target selection in proteomics and structural genomics work. Here we report a validation mechanism developed for membrane porins. A database server for porins, PRNDS, has been created containing experimentally proven porins…and likely putative porins. Each porin is validated and ranked using a weighted scoring system developed based on six, structure and sequence based criteria. The server also predicts possible porins.
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Abstract: A family of hypothetical proteins, identified predominantly from archaeal genomes, has been analyzed in order to understand its functional characteristics. Using extensive sequence similarity searches it is inferred that this family is remotely related (best sequence identity is 19%) to ClpP proteinases that belongs to serine proteinase class. This family of hypothetical proteins is referred to as SDH proteinase family based on conserved sequential order of Ser, Asp and His residues and predicted serine…proteinase activity. Results of fold recognition of SDH family sequences confirmed the remote relationship between SDH proteinases and Clp proteinases and revealed similar tertiary location of putative catalytic triad residues critical for serine proteinase function. However, the best sequence alignment we could obtain suggests that while catalytic Ser is conserved across Clp and SDH proteinases the location of the other catalytic triad residues, namely, His and Asp are swapped in their amino acid alignment positions and hence in 3-D structure. The evidence of conserved catalytic triad suggests that SDH could be a new family of serine proteinases with the fold of Clp proteinase, however sharing the catalytic triad order of carboxypeptidase clan. Signal peptide sequence identified at the N-terminus of some of the homologues suggests that these might be secretory serine proteinases involved in cleavage of extracellular proteins while the remote homologues, ClpP proteinases, are known to work in intracellular environment.
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Abstract: In silico proteomics complements computational genomics in characterizing genome evolution. Here we examine cluster patterns in archaeal and bacterial proteomes using compositional properties of protein sequences in contrast to the traditionally used sequence alignment procedures. Application of standard Principal Component Analysis to the multi-dimensional data identified cluster patterns. Two types of cluster patterns exist in bacterial proteomes. Proteomes of type I have one major cluster with few isolated points in space revealing…an underlying largely homogeneous compositional structure. In type II proteomes two clusters of protein distribution were discernible. The two clusters differ in size and were separated from each other although the boundary was somewhat fuzzy. Proteins falling in the major cluster were labeled as 'typical' and proteins of the minor cluster were called 'atypical'. The atypical proteins were mapped to Cluster of Orthologous Groups. Species distribution in COGs maps with respect to atypical proteins illuminated the biological relationships of extreme diversity among the archaeal members and of diversity among bacteria in relation to their niche. Amino acids that were over-represented in the atypical proteins had higher biosynthetic cost compared to 'typical' ribosomal proteins. However, archaea and bacteria economize by preferring the less costly amino acid to others closely related in chemical structure. Further, over-representation of serine in atypical proteins of archaeal members suggests re-examining these proteomes for the presence of Serine/Threonine phosphatases and kinases in Archaea. Our computational procedure can serve as a useful addition to the existing tools for carrying out in silico proteomics.
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Abstract: Traditional sequence-based search methods such as BLAST and FASTA can be used to identify sequence similarities. Recently, there is a growing interest in performing RNA shape similarity searches inside selected genes to locate RNA structure motifs that are known to possess functionally important roles. For example, in the newly discovered RNA genetic control elements called "riboswitches", the box domain is known to be highly conserved among various bacterial species in both its nucleotide composition and shape.…However, in non-bacterial species, shape conservation is likely to become more important than sequence conservation when searching for riboswitch patterns. For this purpose, we present an approach tailored for detecting RNA shape similarities. We extend the Structure to String (STR^{2} ) method that was initially proposed to locate shape similarities in proteins to identify predicted secondary structures of RNAs. The STR^{2} for RNAs is a translation of a secondary structure to a string of characters, after which known sequence-based search algorithms with an efficient implementation are being used. We validate that the STR^{2} succeeds to locate G-box riboswitches in prokaryotes, as expected. Subsequently we show running examples when attempting to detect G-box riboswitch candidates in eukaryotes.
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Abstract: We report here probable nutrient-sensing signal transduction pathways in Aspergillus nidulans, a model filamentous fungus, based on sequence homology studies with known Saccharomyces cerevisiae and Schizosaccharomyces pombe proteins. Specifically, we identified A. nidulans homologs for yeast proteins involved in (1) filamentation-invasion, (2) cAMP-PKA, (3) pheromone response, (4) cell integrity and (5) TOR signaling pathways. We have also studied autophagy, one of the most important cellular responses regulated by TOR signaling. The Basic…Local Alignment Search Tool program "blastp" was used to assess the homology of proteins. We note that by using a highly conservative approach, 70% of the S. cerevisiae signal transduction proteins (107 proteins out of 153 proteins studied) have significant homologs in A. nidulans. Using a slightly less conservative approach, we are able to identify homologs for as high as 91% of the S. cerevisiae signal transduction proteins (139 proteins out of 153 proteins studied). The filamentation-invasion, cell integrity and TOR signaling pathways showed greatest similarity with S. cerevisiae, while the cAMP-PKA and pheromone response pathways showed greater similarity with S. pombe. Based on these results, probable pathways in A. nidulans were constructed using well-established S. cerevisiae and S. pombe models.
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