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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: The avian influenza (bird flu) is an infectious disease of birds, ranging from a mild to a severe form of illness. Influenza viruses pose significant challenges to both human and animal health. The proteins, nucleoprotein (NP), neuraminidase (NA) and hemagglutinin (HA) of influenza A virus (Bird flu virus) sub-type A/Hatay/2004/(H5N1) from chicken were selected for this study. Our in silico analysis predicted that HA of influenza A virus is highly sensitive to mutations and hence it…is significant for its pathogenic nature. None of the mutations was detected as an important change except in NA where K332R was at a PKC phosphorylation site. Analysis of the sequence comparison showed that the maximum number of mutations were observed in HA. These mutations are significant as they are involved in change in polarity or hydrophobicity as well as in propensity of each amino acid residue to stabilize the secondary structure. The program MAPMUTATION can be used to monitor the mutations, and predict the trend of mutations.
Keywords: Nucleoprotein, neuraminidase, hemagglutinin, mutation, protein kinase C phosphorylation
Abstract: Neurospora crassa has been the model filamentous fungus for the study of many fundamental cellular mechanisms of transport and metabolism. The recently completed genome sequence of N. crassa has over 10,000 genes without significant matches for a large number of genes (41%) in the sequence databases, indeed presents many challenges for new discoveries. Using transporter database and BLAST searches a total of 65 open reading frames for putative cation transporter genes have been identified in N.…crassa. These were further confirmed by characteristic features of the family like transmembrane domains (TOPPRED 2), conserved motifs (Clustal W) and phylogenetic analysis (TREETOP). In Neurospora cation transporter genes constitute nearly 18.3% of the total membrane transport systems, which is higher than E. coli (8.8%), S. cerevisiae (13.7%), S. pombe (17.2%), A. fumigatus (10.1%), A. thaliana (16.8%) and H. sapiens (15.6%). We refer to the complete complement of metal ion transporter genes as "Metal Transportome". There are a total of 33 putative transporters for alkali and alkaline earth metals constituting 18 for calcium (P-ATPase, VIC, CaCA, Mid1), 7 for sodium (P-ATPase, CPA1, CPA2), 4 for potassium (Trk, VIC, KUP), and 4 for magnesium (MIT). Transition metal ion transporters account for 32 transporters including 7 for zinc (ZIP), 6 for copper (Ctr2, Ctr1), 2 each for manganese (Nramp), iron (OFeT), arsenite (ArsAB, ACR3) and other metal ions (ABC and P-ATPase) and 1 each for nickel (NiCoT) and chromate (CHR). N. crassa has 7 linkage groups of which LGI harbors 21 of metal ion transporters and in contrast LGVII has only 2. Studies on metal transportomes of different organisms will help to unravel the role of metal ion transporters in homeostasis.
Keywords: Metal ion transporters, transportome, metals, transporters, Neurospora crassa
Abstract: A G2/M genetic network simulation is trained with tumor incidence data from knockout experiments. The genetic network is implemented using a neural network; knockout genotypes are simulated by removing nodes in the neural network. Two analyses are used to interpret the resulting network weights. We use a novel approach of fixing the network topology that allows knockout TSG (tumor suppressor gene) data from multiple studies to overlap and indirectly inform one another. The trained simulation is…validated by reproducing qualitative mammary cancer susceptibilities of ATM, BRCA1, and p53 TSGs. The work described is valuable because it allows TSG mammary cancer susceptibility to be quantified using genetic network topology and in vivo knockout data.
Abstract: We present a simple ordinary differential equation (ODE) model of the adaptive response to an osmotic shock in the yeast Saccharomyces cerevisiae. The model consists of two main components. First, a biophysical model describing how the cell volume and the turgor pressure are affected by varying extra-cellular osmolarity. The second component describes how the cell controls the biophysical system in order to keep turgor pressure, or equivalently volume, constant. This is done by adjusting the…glycerol production and the glycerol outflow from the cell. The complete model consists of 4 ODEs, 3 algebraic equations and 10 parameters. The parameters are constrained from various literature sources and estimated from new and previously published absolute time series data on intra-cellular and total glycerol. The qualitative behaviour of the model has been successfully tested on data from other genetically modified strains as well as data for different input signals. Compared to a previous detailed model of osmoregulation, the main strength of our model is its lower complexity, contributing to a better understanding of osmoregulation by focusing on relationships which are obscured in the more detailed model. Besides, the low complexity makes it possible to obtain more reliable parameter estimates.
Abstract: This paper reports a novel symbol-to-signal mapping for DNA sequences, based on the concept of categorical periodograms. A categorical periodogram is a numeric sequence with the n-th element of the sequence indicating the number of occurrences of cycles with period n in it. The period of the cycle is defined as the number of intervening events plus one. Spectral analysis studies have been conducted on Cumulative Categorical Periodogram (CCP) of 10 genes from the data set…of Burset and Guigo. It is observed that the spectral signatures in CCP are functionally equivalent to the established N/3 peak in the spectrum of indicator sequences of genomes. Being a single sequence compared to four sequences in the case of indicator sequence representation, the method is claimed to be functionally equivalent, but computationally better for identification of gene coding regions in sequences.
Keywords: Digital signature, categorical periodogram, cumulative categorical periodogram, mapping, indicator sequences, genomic signal processing
Abstract: Prophage loci often remain under-annotated or even unrecognized in prokaryotic genome sequencing projects. A PHP application, Prophage Finder, has been developed and implemented to predict prophage loci, based upon clusters of phage-related gene products encoded within DNA sequences. This application provides results detailing several facets of these clusters to facilitate rapid prediction and analysis of prophage sequences. Prophage Finder was tested using previously annotated prokaryotic genomic sequences with manually curated prophage loci…as benchmarks. Additional analyses from Prophage Finder searches of several draft prokaryotic genome sequences are available through the Web site (http://bioinformatics.uwp.edu/~phage/DOEResults.php) to illustrate the potential of this application.
Abstract: Structure prediction methods aim to identify the relationship between the amino acid sequence of an unknown protein and information comprised in databases of known protein structures. Towards this end, we created a database by combining the amino acid sequences and the corresponding three-dimensional atomic coordinates for all the 25% non-redundant protein chains available in the Protein Data Bank. It contains information about the peptide fragments that are 5 to 10 residues long. In addition, options are…provided for the users to visualize the individual motifs and the superposed fragments in the client machine. Further, useful functionalities are provided to look for similar sequence motifs in all the sequence databases like PDB, 90% non-redundant protein chains, Genome database, PIR and Swiss-Prot. The database is being updated at regular intervals and the same can be accessed over the World Wide Web interface at the following URL: http://pranag.physics.iisc.ernet.in/sms/.
Keywords: Protein sequences, database, structural rigidity, Protein Data Bank, genome sequences, superposition, World Wide Web, non-redundant structures
Abstract: Most transcriptional regulatory elements are located in non-coding DNA. In particular, some first introns play a vital role in transcriptional control and splicing. The length and GC-content of first exons and introns in complex organisms suggests that these structural units are likely to be important functional elements in large genomes. Hence, in this paper we perform a systematic comparison of exon-intron structure and GC content on all known genes in the human genome. Our in-silico analysis…found that the GC content of introns and exons varies significantly depending on their length. On average, the first intron of a gene is significantly longer than other introns in the same gene. Our results also show that first introns and exons are more GC rich than last and internal. This study provides insight into the structure of eukaryotic genes. These results confirm and expand the previously identified regulatory potential of first exons and introns.
Abstract: AthaMap generates a map for cis-regulatory sequences for the whole Arabidopsis thaliana genome. AthaMap was initially developed by matrix-based detection of putative transcription factor binding sites (TFBS) mostly determined from random binding site selection experiments. Now, also experimentally verified TFBS have been included for 48 different Arabidopsis thaliana transcription factors (TF). Based on these sequences, 89,416 very similar putative TFBS were determined within the genome of A. thaliana and annotated…to AthaMap. Matrix- and single sequence-based binding sites can be included in colocalization analysis for the identification of combinatorial cis-regulatory elements. As an example, putative target genes of the WRKY18 transcription factor that is involved in plant-pathogen interaction were determined. New functions of AthaMap include descriptions for all annotated Arabidopsis thaliana genes and direct links to TAIR, TIGR and MIPS. Transcription factors used in the binding site determination are linked to TAIR and TRANSFAC® databases. AthaMap is freely available at http://www.athamap.de.
Abstract: Monte Carlo simulations are useful to verify the significance of data. Genomic regularities, such as the nucleotide correlations or the not uniform distribution of the motifs throughout genomic or mature mRNA sequences, exist and their significance can be checked by means of the Monte Carlo test. The test needs good quality random sequences in order to work, moreover they should have the same nucleotide distribution as the sequences in which the regularities have been found. Random…DNA sequences are also useful to estimate the background score of an alignment, that is a threshold below which the resulting score is merely due to chance. We have developed RANDNA, a free software which allows to produce random DNA or RNA sequences setting both their length and the percentage of nucleotide composition. Sequences having the same nucleotide distribution of exonic, intronic or intergenic sequences can be generated. Its graphic interface makes it possible to easily set the parameters that characterize the sequences being produced and saved in a text format file. The pseudo-random number generator function of Borland Delphi 6 is used, since it guarantees a good randomness, a long cycle length and a high speed. We have checked the quality of sequences generated by the software, by means of well-known tests, both by themselves and versus genuine random sequences. We show the good quality of the generated sequences. The software, complete with examples and documentation, is freely available to users from: http://www.introni.it/en/software.
Keywords: Random nucleotides, entropy, information theory, pseudo-random generator