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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 human genome is revisited using exon and intron distribution profiles. The 26,564 annotated genes in the human genome (build October, 2003) contain 233,785 exons and 207,344 introns. On average, there are 8.8 exons and 7.8 introns per gene. About 80% of the exons on each chromosome are < 200 bp in length. < 0.01% of the introns are < 20 bp in length and < 10% of introns are more than 11,000 bp in length. These results suggest constraints…on the splicing machinery to splice out very long or very short introns and provide insight to optimal intron length selection. Interestingly, the total length in introns and intergenic DNA on each chromosome is significantly correlated to the determined chromosome size with a coefficient of correlation r = 0.95 and r = 0.97, respectively. These results suggest their implication in genome design.
Abstract: DNA-binding transcription factors play a central role in transcription regulation, and the annotation of transcription-factor binding sites in upstream regions of human genes is essential for building a genome-wide regulatory network. We describe methodology to accurately predict the transcription-factor binding sites in the proximal-promoter region of function-specific genes. In order to increase the accuracy of transcription factor binding-site prediction, we rely on recent genome sequence data, known transcription factor binding-site matrices, and…Gene Ontology biological-function-based gene classification. Using TRANSFAC position-frequency matrices, we detected individual and cooperating transcription-factor binding sites in proximal promoters of ENSEMBL annotated human genes. We used the over representation of detected binding sites in the proximal promoters as compared to the second exons to control specificity. We confirmed the majority of transcription-factor binding sites predicted in proximal promoters of immune-response genes with evidence from existing literature. We validated the predicted cooperation between transcription factors NF-κB and IRF in the regulation of gene expression with microarray transcript profiling data and literature-derived protein-protein interaction network. We also identified over-represented individual and pairs of transcription-factor binding sites in the proximal promoters of each Gene Ontology biological-process gene group. Our tools and analysis provide a new resource for deciphering transcription regulation in different biological paradigms.
Abstract: We describe a web-based resource to identify, search and analyze sequence patterns conserved in the multiple sequence alignments of orthologous promoters from closely related/distant Saccharomyces spp. The webtool interfaces with a database where conserved sequence patterns (greater than 4 bp) have been previously extracted from genome-wide promoter alignments, allowing one to carry out user-defined genome-wide searches for conserved sequences to assist in the discovery of novel promoter elements based on comparative genomics.…The web-based server can be accessed at http://www2.imtech.res.in/anand/sacch_prom_pat.html.
Abstract: Common complex polygenic diseases as autoimmune diseases have not been completely understood on a molecular level. While many genes are known to be involved in the pathways responsible for the phenotype, explicit causes for the susceptibility of the disease remain to be elucidated. The susceptibility to disease is thought to be the result of genetic epistatic interactions between common polymorphic genes. This polymorphism is mostly caused by single nucleotide polymorphisms (SNPs). Human subpopulations are known to…differ in the susceptibility to the diseases and generally in the distribution of single nucleotide polymorphisms. The here presented approach retrieves SNPs with the most divergent frequencies for selected human subpopulations to help defining properties for the experimental verification of SNPs within defined regions. A web-accessible program implementing this approach was evaluated for multiple sclerosis (MS), a common human polygenic disease. A link to a summary of data from "The SNP Consortium" (TSC) with sex-dependencies of SNPs is available. Associations of SNPs to genes, genetic markers and chromosomal loci are retrieved from the Ensembl project. This tool is recommended to be used in conjunction with microarray analyses or marker association studies that link genes or chromosomal loci to particular diseases.
Keywords: SNP selection by population frequencies, association studies, multiple sclerosis, ensembl
Abstract: We report the generation and initial characterization of a large-scale collection of sequences of putative promoter regions (PPRs) of human and mouse genes. Based on our unique collection of 400,225 and 580,209 human and mouse full-length cDNAs, we determined exact transcriptional start sites (TSSs). Using positional information of the TSSs, we could retrieve adjacent sequences as PPRs for 8,793 and 6,875 human and mouse genes, respectively. The positions of the PPRs were 4 kb upstream to…previously reported 5'-ends of cDNAs on average, demonstrating that full-length cDNA information is indispensable for this purpose. Among those PPRs supported by experimentally validated TSSs, 3,324 could be paired as mutually homologous genes between human and mouse and were used for the comprehensive comparative studies. The sequence identities in the proximal regions of the TSSs were 45% on average, and 22,794 putative transcription factor binding sites that are conserved between human and mouse were identified. The data resource created in the present work and the results of the sequences' initial characterization should lay the firm foundation for deciphering the transcriptional modulations of human genes. All the data were deposited and made available through a database for comparative studies, DBTSS.
Abstract: In order to bridge the gap between proteins with three-dimensional (3-D) structural information and those without 3-D structures, extensive experimental and computational efforts for structure recognition are being invested. One of the rapid and simple computational approaches for structure recognition makes use of sequence profiles with sensitive profile matching procedures to identify remotely related homologous families. While adopting this approach we used profiles that are generated from structure-based sequence alignment of homologous…protein domains of known structures integrated with sequence homologues. We present an assessment of this fast and simple approach. About one year ago, using this approach, we had identified structural homologues for 315 sequence families, which were not known to have any 3-D structural information. The subsequent experimental structure determination for at least one of the members in 110 of 315 sequence families allowed a retrospective assessment of the correctness of structure recognition. We demonstrate that correct folds are detected with an accuracy of 96.4% (106/110). Most (81/106) of the associations are made correctly to the specific structural family. For 23/106, the structure associations are valid at the superfamily level. Thus, profiles of protein families of known structure when used with sensitive profile-based search procedure result in structure association of high confidence. Further assignment at the level of superfamily or family would provide clues to probable functions of new proteins. Importantly, the public availability of these profiles from us could enable one to perform genome wide structure assignment in a local machine in a fast and accurate manner.
Keywords: protein fold, superfamily, profiles, protein family, fold recognition, structural genomics, remote homologues
Abstract: In the last years, biostatistical research has begun to apply linear models and design theory to develop efficient experimental designs and analysis tools for gene expression microarray data. With two-colour microarrays, direct comparisons of RNA-targets are possible and lead to incomplete block designs. In this setting, efficient designs for simple and factorial microarray experiments have mainly been proposed for technical replicates. But for biological replicates, which are crucial to obtain inference that can be…generalised to a biological population, this question has only been discussed recently and is not fully solved yet. In this paper, we propose efficient designs for independent two-sample experiments using two-colour microarrays enabling biologists to measure their biological random samples in an efficient manner to draw generalisable conclusions. We give advice for experimental situations with differing group sizes and show the impact of different designs on the variance and degrees of freedom of the test statistics. The designs proposed in this paper can be evaluated using SAS PROC MIXED or S+/R lme.
Keywords: microarray, design, biological replication, mixed linear model, ANOVA
Abstract: The rapid proliferation of genomic DNA sequences has created a significant need for software that can both focus on relatively small areas (such as within genes or promoters) and provide wide-zoom views of patterns across entire genomes. We present our DNA Motif Lexicon that enables users to perform genome-wide searches for motifs of interest and create customizable results pages, where results differ in the degree and extent of annotation. Searching for a particular motif is akin…to a word search in a natural language; our motif lexicon speaks to this new time when we will increasingly rely upon DNA dictionaries that offer rich types of annotation. Indeed, the concept of "lexomics", introduced in this paper may be appropriate to the types of meta-analyses relevant to the deciphering of regulatory information. Currently supporting five genomes, our web-based lexicon allows users to look up motifs of interest and build user-defined result pages to include the following: (1) all base pair locations where a motif is found with links to further search the "neighborhoods" near each of these locations; whether each location of the motif is genic (within) a gene, intergenic, or a bridging sequence (overlapping a gene boundary) (2) NCBI hot-links to nearest upstream and downstream genes for each location (3) statistical information about the query (4) whether the motif is a certain type of repeat (5) links for the reverse, complement and reverse-complement of the motif of interest and (6) hot-links to PubMed abstracts which mention the motif of interest. A software framework facilitates the continual development of new annotation modules. The tool is located at: http://genomics.wheatoncollege.edu/cgi-bin/lexicon.exe.
Abstract: In the presented work we search for transcription factor binding sites (BS) by including additional information about typical BS patterns. The new proposed score combines the ordinary profile score based on TRANSFAC-matrices together with a score based on pairs of BS. The latter score positively weights pairs of BS that tend to occur together in many regulatory DNA-sequences, in contrast to a random background model. The empirical BS pair frequencies result from our evaluation of a…large dataset of orthologous genes.
Keywords: recognition of genes and regulatory elements, transcription factor binding site, score matrix
Abstract: IFNγ, a cytokine promoting cell-mediated immunity and antiviral effects, regulates the expression of a large set of genes involved in the immune response. Based on logistic regression, an in silico model for predicting IFNγ regulated transcription has been developed by scoring the transcription factor binding sites on the putative promoters of regulated versus not regulated genes derived from the microarray data of IFNγ treated human macrophages. The model effectively discriminates the transcription…factor binding sites that confer responsiveness to IFNγ from those that do not. The model has 65% true positive and 22% false positive rates when evaluated on a small validation set. In order to identify potential IFNγ regulated genes in the whole genome, the model has been used to screen 13,668 promoter pairs of human-mouse orthologs/homologs from Ensembl, and 1,387 of them were predicted to be potentially regulated by IFNγ. In the pilot experiment, the regulation pattern of a subset of predicted genes that were not detected by microarray approach was evaluated by quantitative PCR. The results for the four novel genes, which are up regulated by IFNγ in human macrophages and identified by this approach, are described in the present communication.
Keywords: IFNγ, transcription, transcription factor binding site (TFBS), promoter, logistic regression model