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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: SIRE1 is a 2,000-copy member of the Ty1/copia retroelement family found in the soybean genome and is closely related to sireviruses found in the genomes of other legumes. Although these elements closely resemble typical plant members of the Ty1/copia family, they are unusual in that they possess an envelope-like coding region immediately downstream of the reverse transcriptase gene. Despite its copy number, very few members of the SIRE1 family are currently present in publicly available…genomic assemblies or draft contigs. However, fragments of family members are well-represented as BAC-ends in the GenBank Genome Survey Sequence database. This database was queried using the 5' and 3' ends of SIRE1 in order to catalog sequences into which SIRE1 members have integrated. Seven hundred and eighty-one unique SIRE1 insertions were identified and the majority of insertion sites constituted other repetitive elements, including Class I and Class II transposable elements and satellite DNAs. Ninety-four insertions were in single- or low-copy number sequences and three of these were homologous to characterized protein-coding genes. Examination of the ten bases flanking either side of SIRE1 revealed no clear consensus sequence, but the the distributions of A, C, G, and T at most of the positions were biased with strong statistical significance.
Abstract: Gene expression profiles of 16 Alzheimer's (AD) patients, diagnosed as incipient or healthy using Mini-Mental State Examination and Neurofibrillary Tangles scores, were analyzed to validate the reclassification of 4 subjects previously identified as being misdiagnosed. Three datasets were created using original classifications (D1), new classifications, based on a misclassification algorithm (D2), and by removing questionable subjects (D3). Mixed model analysis was used to identify differentially expressed genes. Many genes related to the…nervous system and AD were found to be differentially expressed in D2 and D3, while few genes, none related to NS or AD, were found using D1. Several additional relevant genes were found when using D2 versus D3, which were likely due to differences in sample size. These results suggest the 4 questionable subjects were likely misclassified in D1. The similarities between results obtained using D2 and D3 provides further evidence of the adequacy of the misclassification algorithm.
Keywords: Gene expression, Alzheimer's Disease, misclassification algorithm, mixed model analysis, Mini-Mental Sate Examination (MMSE) and Neurofibrillary Tangles