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COMPUTER SCIENCE (1160 journals)            First | 1 2 3 4 5 6     

Showing 801 - 872 of 872 Journals sorted alphabetically
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Karbala International Journal of Modern Science     Open Access   (Followers: 3)
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Molecular Simulation     Hybrid Journal   (Followers: 3)
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  First | 1 2 3 4 5 6     

In Silico Biology
  [2 followers]  Follow
  This is an Open Access Journal Open Access journal
   ISSN (Print) 1386-6338 - ISSN (Online) 1434-3207
   This journal is no longer being updated because:
  • A simple model for Lutz and Bujard's controllable promoters and its
           application for analyzing a simple genetic oscillator

    • Abstract: We develop an exact and flexible mathematical model for Lutz and Bujard's controllable promoters. It can be used as a building block for modeling genetic systems based on them. Special attention is paid to deduce all the model parameters from reported (in vitro) experimental data. We validate our model by comparing the regulatory ranges measured in vivo by Lutz and Bujard against the ranges predicted by the model, and which are calculated as the reporter activity obtained under inducing conditions divided by the activity measured under maximal repression. In particular, we verify Bond et al. assertion that the cooperativity between two lac operators can be assumed to be negligible when their central base pairs are separated by 22 or 32 bp [Gene repression by minimal lac loops in vivo, Nucleic Acids Res, 38 (2010) 8072–8082]. Moreover, we also find that the probability that two repressors LacI bind to these operators at the same time can be assumed to be negligible as well. We finally use the model for the promoter PLlacO-1 to analyze a synthetic genetic oscillator recently build by Stricker et al. [A fast, robust and tunable synthetic gene oscillator, Nature, 456 (2008) 516–519].
      Content Type Journal Article
      Pages -
      DOI 10.3233/ISB-150465
      C. G. Zamora-Chimal, Centro de Investigación y de Estudios Avanzados del IPN, Unidad Monterrey, Parque de Investigación e Innovación Tecnológica, Apodaca NL, México
      M. S. Zeron, Centro de Investigación y de Estudios Avanzados del IPN, Departamento de Matemáticas, Av. Instituto Politécnico Nacional México DF, México
      Journal In Silico Biology
      Online ISSN 1434-3207
      Print ISSN 1386-6338
      PubDate: Thu, 26 Feb 2015 21:11:16 GMT
  • Exploiting stoichiometric redundancies for computational efficiency and
           network reduction

    • Abstract: Analysis of metabolic networks typically begins with construction of the stoichiometry matrix, which characterizes the network topology. This matrix provides, via the balance equation, a description of the potential steady-state flow distribution. This paper begins with the observation that the balance equation depends only on the structure of linear redundancies in the network, and so can be stated in a succinct manner, leading to computational efficiencies in steady-state analysis. This alternative description of steady-state behaviour is then used to provide a novel method for network reduction, which complements existing algorithms for describing intracellular networks in terms of input-output macro-reactions (to facilitate bioprocess optimization and control). Finally, it is demonstrated that this novel reduction method can be used to address elementary mode analysis of large networks: the modes supported by a reduced network can capture the input-output modes of a metabolic module with significantly reduced computational effort.
      Content Type Journal Article
      Pages -
      DOI 10.3233/ISB-140464
      Brian P. Ingalls, Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada
      Eric Bembenek, Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada
      Journal In Silico Biology
      Online ISSN 1434-3207
      Print ISSN 1386-6338
      PubDate: Mon, 29 Dec 2014 20:34:07 GMT
  • The utility of simple mathematical models in understanding gene regulatory

    • Abstract: In this review, we survey work that has been carried out in the attempts of biomathematicians to understand the dynamic behaviour of simple bacterial operons starting with the initial work of the 1960's. We concentrate on the simplest of situations, discussing both repressible and inducible systems and then turning to concrete examples related to the biology of the lactose and tryptophan operons. We conclude with a brief discussion of the role of both extrinsic noise and so-called intrinsic noise in the form of translational and/or transcriptional bursting.
      Content Type Journal Article
      Category Review
      Pages -
      DOI 10.3233/ISB-140463
      Michael C. Mackey, Departments of Physiology, Physics & Mathematics, McGill University, 3655 Promenade Sir William Osler, Montreal, Quebec H3G 1Y6, Canada
      Moisés Santillán, Centro de Investigación y de Estudios Avanzados del IPN, Unidad Monterrey, Vía del Conocimiento 201, Parque de Investigación e Innovación Tecnológica, Apodaca NL, México
      Marta Tyran-Kamińska, Institute of Mathematics, University of Silesia, Bankowa, Katowice, Poland
      Eduardo S. Zeron, Departamento de Matem'aticas, Centro de Investigaci'on y de Estudios Avanzados del IPN, Apartado Postal, M'exico DF, M'exico
      Journal In Silico Biology
      Online ISSN 1434-3207
      Print ISSN 1386-6338
      PubDate: Fri, 14 Nov 2014 22:15:28 GMT
  • In silico analysis of division times of Escherichia coli populations as a
           function of the partitioning scheme of non-functional proteins

    • Abstract: Recent evidence suggests that cells employ functionally asymmetric partitioning schemes in division to cope with aging. We explore various schemes in silico, with a stochastic model of Escherichia coli that includes gene expression, non-functional proteins generation, aggregation and polar retention, and molecule partitioning in division. The model is implemented in SGNS2, which allows stochastic, multi-delayed reactions within hierarchical, transient, interlinked compartments. After setting parameter values of non-functional proteins' generation and effects that reproduce realistic intracellular and population dynamics, we investigate how the spatial organization of non-functional proteins affects mean division times of cell populations in lineages and, thus, mean cell numbers over time. We find that division times decrease for increasingly asymmetric partitioning. Also, increasing the clustering of non-functional proteins decreases division times. Increasing the bias in polar segregation further decreases division times, particularly if the bias favors the older pole and aggregates' polar retention is robust. Finally, we show that the non-energy consuming retention of inherited non-functional proteins at the older pole via nucleoid occlusion is a source of functional asymmetries and, thus, is advantageous. Our results suggest that the mechanisms of intracellular organization of non-functional proteins, including clustering and polar retention, affect the vitality of E. coli populations.
      Content Type Journal Article
      Category Research
      Pages -
      DOI 10.3233/ISB-140462
      Abhishekh Gupta, Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
      Jason Lloyd-Price, Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
      Andre S. Ribeiro, Laboratory of Biosystem Dynamics, Department of Signal Processing, Tampere University of Technology, Tampere, Finland
      Journal In Silico Biology
      Online ISSN 1434-3207
      Print ISSN 1386-6338
      PubDate: Mon, 13 Oct 2014 16:30:45 GMT
  • Limits of computational biology

    • Abstract: Are we close to a complete inventory of living processes so that we might expect in the near future to reproduce every essential aspect necessary for life' Or are there mechanisms and processes in cells and organisms that are presently inaccessible to us' Here I argue that a close examination of a particularly well-understood system—that of Escherichia coli chemotaxis—shows we are still a long way from a complete description. There is a level of molecular uncertainty, particularly that responsible for fine-tuning and adaptation to myriad external conditions, which we presently cannot resolve or reproduce on a computer. Moreover, the same uncertainty exists for any process in any organism and is especially pronounced and important in higher animals such as humans. Embryonic development, tissue homeostasis, immune recognition, memory formation, and survival in the real world, all depend on vast numbers of subtle variations in cell chemistry most of which are presently unknown or only poorly characterized. Overcoming these limitations will require us to not only accumulate large quantities of highly detailed data but also develop new computational methods able to recapitulate the massively parallel processing of living cells.
      Content Type Journal Article
      Category Opinion
      Pages -
      DOI 10.3233/ISB-140461
      Dennis Bray, Department of Physiology, Development and Neuroscience, University of Cambridge, Cambridge, UK
      Journal In Silico Biology
      Online ISSN 1434-3207
      Print ISSN 1386-6338
      PubDate: Mon, 13 Oct 2014 16:30:00 GMT
  • Numerical detection, measuring and analysis of differential interferon
           resistance for individual HCV intra-host variants and its influence on the
           therapy response

    • Abstract: Hepatitis C virus (HCV) is a major cause of liver disease world-wide. Current interferon and ribavirin (IFN/RBV) therapy is effective in 50%–60% of patients. HCV exists in infected patients as a large viral population of intra-host variants (quasispecies), which may be differentially resistant to interferon treatment. We present a method for measuring differential interferon resistance of HCV quasispecies based on mathematical modeling and analysis of HCV population dynamics during the first hours of interferon therapy. The mathematical models showed that individual intra-host HCV variants have a wide range of resistance to IFN treatment in each patient. Analysis of differential IFN resistance among intra-host HCV variants allows for accurate prediction of response to IFN therapy. The models strongly suggest that resistance to interferon may vary broadly among closely related variants in infected hosts and therapy outcome may be defined by a single or a few variants irrespective of their frequency in the intra-host HCV population before treatment.
      Content Type Journal Article
      Pages 263-269
      DOI 10.3233/ISB-2012-0460
      Pavel Skums,
      David S. Campo,
      Zoya Dimitrova,
      Gilberto Vaughan,
      Daryl T. Lau,
      Yury Khudyakov,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:20 GMT
  • Improved transcriptome quantification and reconstruction from RNA-Seq
           reads using partial annotations

    • Abstract: The paper addresses the problem of how to use RNA-Seq data for transcriptome reconstruction and quantification, as well as novel transcript discovery in partially annotated genomes. We present a novel annotation-guided general framework for transcriptome discovery, reconstruction and quantification in partially annotated genomes and compare it with existing annotation-guided and genome-guided transcriptome assembly methods. Our method, referred as Discovery and Reconstruction of Unannotated Transcripts (DRUT), can be used to enhance existing transcriptome assemblers, such as Cufflinks [3], as well as to accurately estimate the transcript frequencies. Empirical analysis on synthetic datasets confirms that Cufflinks enhanced by DRUT has superior quality of reconstruction and frequency estimation of transcripts.
      Content Type Journal Article
      Pages 251-261
      DOI 10.3233/ISB-2012-0459
      Serghei Mangul,
      Adrian Caciula,
      Olga Glebova,
      Ion Mandoiu,
      Alex Zelikovsky,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:20 GMT
  • Mixture model analysis reflecting dynamics of the population diversity of
           2009 pandemic H1N1 influenza virus

    • Abstract: Influenza A viruses have been responsible for large losses of lives around the world and continue to present a great public health challenge. In April 2009, a novel swine-origin H1N1 virus emerged in North America and caused the first pandemic of the 21st century. Toward the end of 2009, two waves of outbreaks occurred, and then the disease moderated. It will be critical to understand how this novel pandemic virus invaded and adapted to a human population. To understand the molecular dynamics and evolution in this pandemic H1N1 virus, we applied an Expectation-Maximization algorithm to estimate the Gaussian mixture in the genetic population of the hemagglutinin (HA) gene of these H1N1 viruses from April of 2009 to January of 2010 and compared them with the viruses that cause seasonal H1N1 influenza. Our results show that, after it was introduced to human population, the 2009 H1N1 viral HA gene changed its population structure from a single Gaussian distribution to two major Gaussian distributions. The breadths of HA genetic diversity of 2009 H1N1 virus also increased from the first wave to the second wave of this pandemic. Phylogenetic analyses demonstrated that only certain HA sublineages of 2009 H1N1 viruses were able to circulate throughout the pandemic period. In contrast, the influenza HA population structure of seasonal H1N1 virus was relatively stable, and the breadth of HA genetic diversity within a single season population remained similar. This study revealed an evolutionary mechanism for a novel pandemic virus. After the virus is introduced to human population, the influenza virus would expand their molecular diversity through both random mutations (genetic drift) and selections. Eventually, multiple levels of hierarchical Gaussian distributions will replace the earlier single distribution. An evolutionary model for pandemic H1N1 influenza A virus was proposed and demonstrated with a simulation.
      Content Type Journal Article
      Pages 225-236
      DOI 10.3233/ISB-2012-0457
      Li-Ping Long,
      Changhe Yuan,
      Zhipeng Cai,
      Huiping Xu,
      Xiu-Feng Wan,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • Reconstructing viral quasispecies from NGS amplicon reads

    • Abstract: This paper addresses the problem of reconstructing viral quasispecies from next-generation sequencing reads obtained from amplicons (i.e., reads generated from predefined amplified overlapping regions). We compare the parsimonious and likelihood models for this problem and propose several novel assembling algorithms. The proposed methods have been validated on simulated error-free HCV and real HBV amplicon reads. The new algorithms have been shown to outperform the method of Prosperi et. al [24]. Our experiments also show that viral quasispecies can be reconstructed in most cases more accurately from amplicon reads rather than shotgun reads. All algorithms have been implemented and made available at
      Content Type Journal Article
      Pages 237-249
      DOI 10.3233/ISB-2012-0458
      Nicholas Mancuso,
      Bassam Tork,
      Pavel Skums,
      Lilia Ganova-Raeva,
      Ion Măndoiu,
      Alex Zelikovsky,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • Coordinated evolution among hepatitis C virus genomic sites is coupled to
           host factors and resistance to interferon

    • Abstract: Machine-learning methods in the form of Bayesian networks (BN), linear projection (LP) and self-organizing tree (SOT) models were used to explore association among polymorphic sites within the HVR1 and NS5a regions of the HCV genome, host demographic factors (ethnicity, gender and age) and response to the combined interferon (IFN) and ribavirin (RBV) therapy. The BN models predicted therapy outcomes, gender and ethnicity with accuracy of 90%, 90% and 88.9%, respectively. The LP and SOT models strongly confirmed associations of the HVR1 and NS5A structures with response to therapy and demographic host factors identified by BN. The data indicate host specificity of HCV evolution and suggest the application of these models to predict outcomes of IFN/RBV therapy.
      Content Type Journal Article
      Pages 213-224
      DOI 10.3233/ISB-2012-0456
      James Lara,
      John E. Tavis,
      Maureen J. Donlin,
      William M. Lee,
      He-Jun Yuan,
      Brian L. Pearlman,
      Gilberto Vaughan,
      Joseph C. Forbi,
      Guo-Liang Xia,
      Yury E. Khudyakov,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • QColors: An algorithm for conservative viral quasispecies reconstruction
           from short and non-contiguous next generation sequencing reads

    • Abstract: Next generation sequencing technologies have recently been applied to characterize mutational spectra of the heterogeneous population of viral genotypes (known as a quasispecies) within HIV-infected patients. Such information is clinically relevant because minority genetic subpopulations of HIV within patients enable viral escape from selection pressures such as the immune response and antiretroviral therapy. However, methods for quasispecies sequence reconstruction from next generation sequencing reads are not yet widely used and remains an emerging area of research. Furthermore, the majority of research methodology in HIV has focused on 454 sequencing, while many next-generation sequencing platforms used in practice are limited to shorter read lengths relative to 454 sequencing. Little work has been done in determining how best to address the read length limitations of other platforms.The approach described here incorporates graph representations of both read differences and read overlap to conservatively determine the regions of the sequence with sufficient variability to separate quasispecies sequences. Within these tractable regions of quasispecies inference, we use constraint programming to solve for an optimal quasispecies subsequence determination via vertex coloring of the conflict graph, a representation which also lends itself to data with non-contiguous reads such as paired-end sequencing. We demonstrate the utility of the method by applying it to simulations based on actual intra-patient clonal HIV-1 sequencing data.
      Content Type Journal Article
      Pages 193-201
      DOI 10.3233/ISB-2012-0454
      Austin Huang,
      Rami Kantor,
      Allison DeLong,
      Leeann Schreier,
      Sorin Istrail,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • Association of antigenic properties to structure of the hepatitis C virus
           NS3 protein

    • Abstract: Sequence heterogeneity substantially affects antigenic properties of the major epitope in the hepatitis C virus (HCV) NS3 protein. To facilitate protein engineering of NS3 antigens immunologically reactive with antibody against the broad diversity of HCV variants we constructed a set of Bayesian Networks (BN) for predicting antigenicity based on structural parameters. Using homology modeling, tertiary (3D) structures of NS3 variants with known antigenic properties were predicted. Energy force field estimated using the 3D-models was found to be most strongly associated with the antigenic properties. The best BN-models showed 100% accuracy of prediction of immunological reactivity with tested serum specimens in 10-fold cross validation. Bootstrap analyses of BN’s constructed using selected features showed that secondary structure and electrostatic potential assessed from 3D-models are the most robust attributes associated with immunological reactivity of NS3 antigens. The data suggest that the BN models may guide the development of NS3 antigens with improved diagnostically relevant properties.
      Content Type Journal Article
      Pages 203-212
      DOI 10.3233/ISB-2012-0455
      James Lara,
      Yury Khudyakov,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • Evaluation of viral heterogeneity using next-generation sequencing,
           end-point limiting-dilution and mass spectrometry

    • Abstract: Hepatitis C Virus sequence studies mainly focus on the viral amplicon containing the Hypervariable region 1 (HVR1) to obtain a sample of sequences from which several population genetics parameters can be calculated. Recent advances in sequencing methods allow for analyzing an unprecedented number of viral variants from infected patients and present a novel opportunity for understanding viral evolution, drug resistance and immune escape. In the present paper, we compared three recent technologies for amplicon analysis: (i) Next-Generation Sequencing; (ii) Clonal sequencing using End-point Limiting-dilution for isolation of individual sequence variants followed by Real-Time PCR and sequencing; and (iii) Mass spectrometry of base-specific cleavage reactions of a target sequence. These three technologies were used to assess intra-host diversity and inter-host genetic relatedness in HVR1 amplicons obtained from 38 patients (subgenotypes 1a and 1b). Assessments of intra-host diversity varied greatly between sequence-based and mass-spectrometry-based data. However, assessments of inter-host variability by all three technologies were equally accurate in identification of genetic relatedness among viral strains. These results support the application of all three technologies for molecular epidemiology and population genetics studies. Mass spectrometry is especially promising given its high throughput, low cost and comparable results with sequence-based methods.
      Content Type Journal Article
      Pages 183-192
      DOI 10.3233/ISB-2012-0453
      Z. Dimitrova,
      D.S. Campo,
      S. Ramachandran,
      G. Vaughan,
      L. Ganova-Raeva,
      Y. Lin,
      J.C. Forbi,
      G. Xia,
      P. Skums,
      B. Pearlman,
      Y. Khudyakov,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:19 GMT
  • Coordinated evolution of the Hepatitis B Virus Polymerase

    • Abstract: The detection of compensatory mutations that abrogate negative fitness effects of drug-resistance and vaccine-escape mutations indicates the important role of epistatic connectivity in evolution of viruses, especially under the strong selection pressures. Mapping of epistatic connectivity in the form of coordinated substitutions should help to characterize molecular mechanisms shaping viral evolution and provides a tool for the development of novel anti-viral drugs and vaccines. We analyzed coordinated variation among amino acid sites in 370 the hepatitis B virus (HBV) polymerase sequences using Bayesian networks. Among the HBV polymerase domains the spacer domain separating terminal protein from the reverse-transcriptase domain, showed the highest network centrality. Coordinated substitutions preserve the hydrophobicity and charge of Spacer. Maximum likelihood estimates of codon selection showed that Spacer contains the highest number of positively selected sites. Identification of 67% of the domain lacking an ordered structure suggests that Spacer belongs to the class of intrinsically disordered domains and proteins whose crucial functional role in the regulation of transcription, translation and cellular signal transduction has only recently been recognized. Spacer plays a central role in the epistatic network associating substitutions across the HBV genome, including those conferring viral virulence, drug resistance and vaccine escape. The data suggest that Spacer is extensively involved in coordination of HBV evolution.
      Content Type Journal Article
      Pages 175-182
      DOI 10.3233/ISB-2012-0452
      D.S. Campo,
      Z. Dimitrova,
      J. Lara,
      M. Purdy,
      H. Thai,
      S. Ramachandran,
      L. Ganova-Raeva,
      X. Zhai,
      J.C. Forbi,
      C.G. Teo,
      Y. Khudyakov,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:18 GMT
  • Differences in variability of hypervariable region 1 of hepatitis C virus
           (HCV) between acute and chronic stages of HCV infection

    • Abstract: Distinguishing between acute and chronic HCV infections is clinically important given that early treatment of infected patients leads to high rates of sustained virological response. Analysis of 2179 clonal sequences derived from hypervariable region 1 (HVR1) of the HCV genome in samples obtained from patients with acute (n = 49) and chronic (n = 102) HCV infection showed that intra-host HVR1 diversity was 1.8 times higher in patients with chronic than acute infection. Significant differences in frequencies of 5 amino acids (positions 5, 7, 12, 16 and 18) and the average genetic distances among intra-host HVR1 variants were found using analysis of molecular variance. Differences were also observed in the polarity, volume and hydrophobicity of 10 amino acids (at positions 1, 4, 5, 12, 14, 15, 16, 21, 22 and 29). Based on these properties, a classification model could be constructed, which permitted HVR1 variants from acute and chronic cases to be discriminated with an accuracy of 88%. Progression from acute to chronic stage of HCV infection is accompanied by characteristic changes in amino acid composition of HVR1. Identifying these changes may permit diagnosis of recent HCV infection.
      Content Type Journal Article
      Pages 163-173
      DOI 10.3233/ISB-2012-0451
      I.V. Astrakhantseva,
      D.S. Campo,
      A. Araujo,
      C.-G. Teo,
      Y. Khudyakov,
      S. Kamili,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:18 GMT
  • miRNA-mRNA network detects hub mRNAs and cancer specific miRNAs in lung

    • Abstract: MicroRNA expression profiles can improve classification, diagnosis, and prognostic information of malignancies, including lung cancer. In this paper, we undertook to develop a miRNA-mRNA network and uncover unique growth suppressive miRNAs in lung cancer using microarray data. The miRNA-mRNA network was developed based on a bipartite graph theory approach, and a number of miRNA-mRNA modules have been identified to mine associations between miRNAs and mRNAs. From the network, we identified totally 29 protective miRNA-mRNA regulatory modules, since we restricted our search to protective miRNAs. Subsequently we analyzed the pathways for the target genes in the protective miRNA-mRNA modules using Pathway-Express. The miRNA-mRNA network efficiently detects hub mRNAs deregulated by the protective miRNAs and identifies cancer specific miRNAs in lung cancer. From the pathway analysis results, the ECM receptor pathway, Focal adhesion pathway and cell adhesion molecules pathway seem to be more interesting to investigate, since these pathways were related to all the ten protective miRNAs. Furthermore, protective miRNA target analysis revealed that genes VCAN, SIL, CD44 and MMP14 were found to have an important role in these pathways. Hence, it was inferred that these genes can be important putative targets for those protective miRNAs. A greater understanding of the mechanisms regulating VCAN, SIL, CD44 and MMP14 expression and activity will assist in the development of specific inhibitors of cancer cell metastasis. Thus these observations are expected to have an intense implication in cancer and may be useful for further research.
      Content Type Journal Article
      Pages 281-295
      DOI 10.3233/ISB-2012-0444
      Saranya Devaraj,
      Jeyakumar Natarajan,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:18 GMT
  • Molecular modeling and docking analysis of Beta-lactamases with
           inhibitors: A comparative study

    • Abstract: Beta-lactamases are bacterial enzymes which impart resistance against β-lactam-antibiotics. CTX-Ms are the β-lactamases that target cephalosporin antibiotics (e.g. cefotaxime and ceftazidime) while SME-1, KPC-2, IMI-1 and SFC-1 target carbapenems. Clavulanic acid, sulbactam and tazobactam are traditional β-lactamase inhibitors while LN1-255 and NXL-104 whereas novel inhibitors, inhibiting the activity of these enzymes. Studying the binding pattern of these drugs is helpful in predicting the versatile inhibitors for betalactamases. The aims of the study were: describing the mode of interaction of CTX-M (modeled from the blaCTX-M gene of this study) and the said carbapenemases with their respective target drugs and inhibitors and to perform an in silico comparison of the efficacies of traditional and novel β-lactamase-inhibitors based on fitness score. The blaCTX-M marker was PCR-amplified from plasmid DNA of E. coli strain isolated from community-acquired urinary tract infection. E. coli C600 cells (harboring cloned blaCTX-M) were found positive for extended-spectrum-β-lactamase (ESBL) production by the double-disk-synergy test. The three dimensional structures of CTX-M-15, SME-1 and IMI-1 were predicted by Swiss Model Server. The interaction between selected structures and inhibitors was performed by GOLD 5.0. On the basis of the docking score and binding pattern, we conclude that compound LN1-255 followed by tazobactam is best inhibitor against all the selected target enzymes as compared to clavulanate, sulbactam and NXL-104. Five conserved amino acids, Ser70, Ser130, Lys235, Thr236 and Gly237 were found crucial in stabilizing the complexes through hydrogen bonding and hydrophobic interactions.
      Content Type Journal Article
      Pages 273-280
      DOI 10.3233/ISB-2012-0443
      Mohd Danishuddin,
      Asad U. Khan,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 5 / 2012
      PubDate: Fri, 30 Nov 2012 14:03:11 GMT
  • Obituary

    • Abstract: Obituary
      Content Type Journal Article
      Pages 95-95
      DOI 10.3233/ISB-2012-0450
      J.E. van den Ende,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 3-4 / 2011/2012 2012
      PubDate: Mon, 27 Aug 2012 20:46:26 GMT
  • ANDVisio: A new tool for graphic visualization and analysis of literature
           mined associative gene networks in the ANDSystem

    • Abstract: The ANDVisio tool is designed to reconstruct and analyze associative gene networks in the earlier developed Associative Network Discovery System (ANDSystem) software package. The ANDSystem incorporates utilities for automated extraction of knowledge from Pubmed published scientific texts, analysis of factographic databases, also the ANDCell database containing information on molecular-genetic events retrieved from texts and databases. ANDVisio is a new user’s interface to the ANDCell database stored in a remote server. ANDVisio provides graphic visualization, editing, search, also saving of associative gene networks in different formats resulting from user’s request. The associative gene networks describe semantic relationships between molecular-genetic objects (proteins, genes, metabolites and others), biological processes, and diseases. ANDVisio is provided with various tools to support filtering by object types, relationships between objects and information sources; graph layout; search of the shortest pathway; cycles in graphs.
      Content Type Journal Article
      Pages 149-161
      DOI 10.3233/ISB-2012-0449
      P.S. Demenkov,
      T.V. Ivanisenko,
      N.A. Kolchanov,
      V.A. Ivanisenko,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 3 / 2011/2012
      PubDate: Mon, 27 Aug 2012 20:46:26 GMT
  • ExpertDiscovery and UGENE integrated system for intelligent analysis of
           regulatory regions of genes

    • Abstract: The task of automatic extraction of the hierarchical structure of eukaryotic gene regulatory regions is in the junction of the fields of biology, mathematics and information technologies. A solution of the problem involves understanding of sophisticated mechanisms of eukaryotic gene regulation and applying advanced data mining technologies. In the paper the integrated system, implementing a powerful relation mining of biological data method, is discussed. The system allows taking into account prior information about the gene regulatory regions that is known by the biologist, performing the analysis on each hierarchical level, searching for a solution from a simple hypothesis to a complex one. The integration of ExpertDiscovery system into UGENE toolkit provides a convenient environment for conducting complex research and automating the work of a biologist. For demonstration, the system has been applied for recognition of SF1, SREBP, HNF4 vertebrate binding sites and for the analysis the human gene regulatory regions that promote liver-specific transcription.
      Content Type Journal Article
      Pages 97-108
      DOI 10.3233/ISB-2012-0448
      Y.Y. Vaskin,
      I.V. Khomicheva,
      E.V. Ignatieva,
      E.E. Vityaev,
      Journal In Silico Biology
      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 3 / 2011/2012
      PubDate: Mon, 27 Aug 2012 20:45:32 GMT
School of Mathematical and Computer Sciences
Heriot-Watt University
Edinburgh, EH14 4AS, UK
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Fax: +00 44 (0)131 4513327
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