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  Subjects -> COMPUTER SCIENCE (Total: 1734 journals)
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COMPUTER SCIENCE (1124 journals)            First | 1 2 3 4 5 6 7 8 | Last

IEEE Transactions on Image Processing     Hybrid Journal   (Followers: 22)
IEEE Transactions on Information Theory     Hybrid Journal   (Followers: 13)
IEEE Transactions on Multimedia     Hybrid Journal   (Followers: 6)
IEEE Transactions On Nanotechnology     Hybrid Journal   (Followers: 9)
IEEE Transactions on Network and Service Management     Hybrid Journal   (Followers: 8)
IEEE Transactions on Neural Networks     Full-text available via subscription   (Followers: 11)
IEEE Transactions on Parallel and Distributed Systems     Hybrid Journal   (Followers: 12)
IEEE Transactions on Signal Processing     Hybrid Journal   (Followers: 22)
IEEE Transactions on Very Large Scale Integration (VLSI) Systems     Hybrid Journal   (Followers: 14)
IEEE Transactions on Wireless Communications     Hybrid Journal   (Followers: 10)
IEEE Wireless Communications     Full-text available via subscription   (Followers: 10)
IEEE/ACM Transactions on Computational Biology and Bioinformatics     Hybrid Journal   (Followers: 8)
IEEE/ACM Transactions on Networking     Hybrid Journal   (Followers: 10)
IEICE - Transactions on Communications     Full-text available via subscription   (Followers: 5)
IEICE - Transactions on Information and Systems     Full-text available via subscription   (Followers: 7)
IERI Procedia     Open Access  
IET Computer Vision     Hybrid Journal   (Followers: 7)
IET Computers & Digital Techniques     Hybrid Journal   (Followers: 3)
IET Control Theory & Applications     Hybrid Journal   (Followers: 10)
IET Software     Hybrid Journal   (Followers: 11)
IMA Journal of Management Mathematics     Hybrid Journal   (Followers: 1)
Image and Vision Computing     Hybrid Journal   (Followers: 8)
In Silico Biology     Open Access   (Followers: 1)
Industrial Electronics, IEEE Transactions on     Hybrid Journal   (Followers: 9)
Industry Applications, IEEE Transactions on     Hybrid Journal   (Followers: 5)
Info     Hybrid Journal  
Informatics     Open Access   (Followers: 2)
Informatics in Primary Care     Full-text available via subscription   (Followers: 10)
Informatik-Spektrum     Hybrid Journal  
Information     Open Access   (Followers: 122)
Information & Communications Technology Law     Hybrid Journal   (Followers: 13)
Information and Organization     Hybrid Journal   (Followers: 136)
Information Processing in Agriculture     Open Access  
Information Retrieval     Hybrid Journal   (Followers: 188)
Information Services and Use     Hybrid Journal   (Followers: 7)
Information Systems Management     Hybrid Journal   (Followers: 20)
Information Technology and Libraries     Open Access   (Followers: 262)
Information Technology and Management     Hybrid Journal   (Followers: 9)
Information Technology for Development     Hybrid Journal   (Followers: 7)
INFORMS Journal on Computing     Full-text available via subscription   (Followers: 4)
InKoj. Interlingvistikaj Kajeroj     Open Access  
Innovation in Teaching and Learning in Information and Computer Sciences     Open Access   (Followers: 2)
Innovations in Education and Teaching International     Hybrid Journal   (Followers: 74)
Innovations in Systems and Software Engineering     Hybrid Journal   (Followers: 5)
Innovative Systems Design and Engineering     Open Access   (Followers: 2)
Insight - Non-Destructive Testing and Condition Monitoring     Full-text available via subscription   (Followers: 4)
Integral Equations and Operator Theory     Hybrid Journal  
Integrated Computer-Aided Engineering     Hybrid Journal  
Integration, the VLSI Journal     Hybrid Journal   (Followers: 1)
Intelligence     Hybrid Journal   (Followers: 1)
Intelligent Data Analysis     Hybrid Journal   (Followers: 3)
Intelligent Decision Technologies     Hybrid Journal   (Followers: 1)
Intelligent Information Management     Open Access   (Followers: 5)
Intelligent Systems in Accounting, Finance & Management: International Journal     Hybrid Journal   (Followers: 4)
Intelligent Transportation Systems Magazine, IEEE     Full-text available via subscription   (Followers: 1)
Interacting with Computers     Hybrid Journal   (Followers: 5)
Interaction Studies     Full-text available via subscription   (Followers: 6)
Interactions Magazine     Full-text available via subscription   (Followers: 5)
Interfaces     Full-text available via subscription   (Followers: 5)
International Communication Gazette     Hybrid Journal   (Followers: 2)
International Journal for Computational Biology     Open Access  
International Journal for Numerical Methods in Engineering     Hybrid Journal   (Followers: 16)
International Journal of Accounting Information Systems     Hybrid Journal   (Followers: 1)
International Journal of Actor-Network Theory and Technological Innovation     Full-text available via subscription   (Followers: 4)
International Journal of Ad Hoc and Ubiquitous Computing     Hybrid Journal   (Followers: 8)
International Journal of Adaptive and Innovative Systems     Hybrid Journal  
International Journal of Advanced Computer Science and Applications     Open Access  
International Journal of Advanced Intelligence Paradigms     Hybrid Journal   (Followers: 2)
International Journal of Advanced Mechatronic Systems     Hybrid Journal   (Followers: 2)
International Journal of Advanced Media and Communication     Hybrid Journal   (Followers: 12)
International Journal of Advancements in Technology     Open Access   (Followers: 2)
International Journal of Advances in Engineering Sciences and Applied Mathematics     Hybrid Journal  
International Journal of Agent-Oriented Software Engineering     Hybrid Journal   (Followers: 2)
International Journal of Agile Systems and Management     Hybrid Journal   (Followers: 4)
International Journal of Algebra and Computation     Hybrid Journal   (Followers: 1)
International Journal of Applied Management and Technology     Open Access   (Followers: 1)
International Journal of Applied Systemic Studies     Hybrid Journal  
International Journal of Approximate Reasoning     Hybrid Journal   (Followers: 1)
International Journal of Architectural Computing     Full-text available via subscription   (Followers: 4)
International Journal of Artificial Intelligence and Soft Computing     Hybrid Journal   (Followers: 8)
International Journal of Artificial Intelligence in Education     Hybrid Journal   (Followers: 2)
International Journal of Arts and Technology     Hybrid Journal   (Followers: 4)
International Journal of Automation and Computing     Hybrid Journal   (Followers: 1)
International Journal of Automation and Control     Hybrid Journal   (Followers: 3)
International Journal of Automation and Control Engineering     Open Access   (Followers: 1)
International Journal of Autonomic Computing     Hybrid Journal   (Followers: 1)
International Journal of Autonomous and Adaptive Communications Systems     Hybrid Journal   (Followers: 4)
International Journal of Child-Computer Interaction     Hybrid Journal  
International Journal of Chinese Culture and Management     Hybrid Journal   (Followers: 1)
International Journal of Cloud Computing and Services Science     Open Access   (Followers: 11)
International Journal of Cognitive Performance Support     Hybrid Journal   (Followers: 2)
International Journal of Combinatorics     Open Access   (Followers: 1)
International Journal of Communication Networks and Distributed Systems     Hybrid Journal   (Followers: 5)
International Journal of Computational Geometry and Applications     Hybrid Journal   (Followers: 2)
International Journal of Computational Intelligence and Applications     Hybrid Journal  
International Journal of Computational Intelligence Studies     Hybrid Journal  
International Journal of Computational Intelligence Systems     Hybrid Journal  
International Journal of Computational Methods     Hybrid Journal   (Followers: 1)
International Journal of Computational Models and Algorithms in Medicine     Full-text available via subscription   (Followers: 1)
International Journal of Computational Science and Engineering     Hybrid Journal   (Followers: 3)

  First | 1 2 3 4 5 6 7 8 | Last

In Silico Biology
   [3 followers]  Follow    
  This is an Open Access Journal Open Access journal
     ISSN (Print) 1386-6338 - ISSN (Online) 1434-3207
     Published by IOS Press Homepage  [93 journals]   [SJR: 0.199]   [H-I: 35]
  • 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

      Authors
      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
       
  • 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

      Authors
      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
       
  • 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

      Authors
      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

      Authors
      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

      Authors
      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 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

      Authors
      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
       
  • 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 https://bitbucket.org/nmancuso/bioa/.
      Content Type Journal Article
      Pages 237-249

      DOI 10.3233/ISB-2012-0458

      Authors
      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
       
  • 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

      Authors
      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
       
  • miRNA-mRNA network detects hub mRNAs and cancer specific miRNAs in lung
           cancer

    • 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

      Authors
      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
       
  • 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

      Authors
      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
       
  • 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

      Authors
      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
       
  • 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

      Authors
      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

      Authors
      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

      Authors
      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

      Authors
      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
       
  • Computer System for Analysis of Molecular Evolution Modes (SAMEM):
           Analysis of molecular evolution modes at deep inner branches of the
           phylogenetic tree

    • Abstract: SAMEM (System for Analysis of Molecular Evolution Modes), a web-based pipeline system for inferring modes of molecular evolution in genes and proteins (http://pixie.bionet.nsc.ru/samem/), is presented. Pipeline 1 performs analyses of protein-coding gene evolution; pipeline 2 performs analyses of protein evolution; pipeline 3 prepares datasets of genes and/or proteins, performs their primary analysis, and builds BLOSUM matrices; pipeline 4 checks if these genes really are protein-coding. Pipeline 1 has an all-new feature, which allows the user to obtain KR/KC estimates using several different methods. An important feature of pipeline 2 is an original method for analyzing the rates of amino acid substitutions at the branches of a phylogenetic tree. The method is based on Markov modeling and a non-parametric permutation test, which compares expected and observed frequencies of amino acid substitutions, and infers the modes of molecular evolution at deep inner branches.
      Content Type Journal Article
      Pages 109-123

      DOI 10.3233/ISB-2012-0446

      Authors
      Konstantin V. Gunbin,
      Valentin V. Suslov,
      Mikhail A. Genaev,
      Dmitry A. Afonnikov,
      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 20:45:31 GMT
       
  • Towards a virtual C. elegans: A framework for simulation and visualization
           of the neuromuscular system in a 3D physical environment

    • Abstract: The nematode C. elegans is the only animal with a known neuronal wiring diagram, or “connectome”. During the last three decades, extensive studies of the C. elegans have provided wide-ranging data about it, but few systematic ways of integrating these data into a dynamic model have been put forward. Here we present a detailed demonstration of a virtual C. elegans aimed at integrating these data in the form of a 3D dynamic model operating in a simulated physical environment. Our current demonstration includes a realistic flexible worm body model, muscular system and a partially implemented ventral neural cord. Our virtual C. elegans demonstrates successful forward and backward locomotion when sending sinusoidal patterns of neuronal activity to groups of motor neurons. To account for the relatively slow propagation velocity and the attenuation of neuronal signals, we introduced “pseudo neurons” into our model to simulate simplified neuronal dynamics. The pseudo neurons also provide a good way of visualizing the nervous system’s structure and activity dynamics.
      Content Type Journal Article
      Pages 137-147

      DOI 10.3233/ISB-2012-0445

      Authors
      Andrey Palyanov,
      Sergey Khayrulin,
      Stephen D. Larson,
      Alexander Dibert,
      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 20:45:31 GMT
       
  • Haploid evolutionary constructor: New features and further challenges

    • Abstract: In this paper we consider the recent advances in methodology for modeling of prokaryotic communities evolution and new features of the software package “Haploid evolutionary constructor” (http://evol-constructor.bionet.nsc.ru). We show the principles of building complex computer models in our software tool. These models describe several levels of biological organization: genetic, metabolic, population, ecological. New features of the haploid evolutionary constructor include the modeling of gene networks and phage infections.
      Content Type Journal Article
      Pages 125-135

      DOI 10.3233/ISB-2012-0447

      Authors
      Sergey A. Lashin,
      Yury G. Matushkin,
      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 20:45:31 GMT
       
  • Fragment-Based Molecular Design of New Competitive Dengue Den2 Ns2b/Ns3
           Inhibitors from the Components of Fingerroot (Boesenbergia rotunda)

    • Abstract:
      Content Type Journal Article
      Pages 29-37

      DOI 10.3233/ISB-2012-0442

      Authors
      Neni Frimayanti, Department of Chemistry, Faculty of Science, University of Malaya Lembah Pantai, Kuala Lumpur, Malaysia
      Sharifuddin M. Zain, Department of Chemistry, Faculty of Science, University of Malaya Lembah Pantai, Kuala Lumpur, Malaysia
      Vannajan Sanghiran Lee, Department of Chemistry, Faculty of Science, University of Malaya Lembah Pantai, Kuala Lumpur, Malaysia
      Habibah A. Wahab, Pharmaceutical Design and Simulation Laboratory, School of Pharmaceutical Sciences, Universiti Sains Malaysia, Penang, Malaysia
      Rohana Yusof, Department of Molecular Medicine, Faculty of Medicine, University Malaya, Kuala Lumpur, Malaysia
      Noorsaadah Abd. Rahman, Department of Chemistry, Faculty of Science, University of Malaya Lembah Pantai, Kuala Lumpur, Malaysia
      Journal In Silico Biology

      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 1-2 / 2011/2012
      PubDate: Wed, 04 Apr 2012 18:32:05 GMT
       
  • Gene Expression Data Analysis Using Multiobjective Clustering Improved
           with SVM Based Ensemble

    • Abstract: Microarray technology facilitates the monitoring of the expression levels of thousands of genes over different experimental conditions simultaneously. Clustering is a popular data mining tool which can be applied to microarray gene expression data to identify co-expressed genes. Most of the traditional clustering methods optimize a single clustering goodness criterion and thus may not be capable of performing well on all kinds of datasets. Motivated by this, in this article, a multiobjective clustering technique that optimizes cluster compactness and separation simultaneously, has been improved through a novel support vector machine classification based cluster ensemble method. The superiority of MOCSVMEN (MultiObjective Clustering with Support Vector Machine based ENsemble) has been established by comparing its performance with that of several well known existing microarray data clustering algorithms. Two real-life benchmark gene expression datasets have been used for testing the comparative performances of different algorithms. A recently developed metric, called Biological Homogeneity Index (BHI), which computes the clustering goodness with respect to functional annotation, has been used for the comparison purpose.
      Content Type Journal Article
      Pages 19-27

      DOI 10.3233/ISB-2012-0441

      Authors
      Anirban Mukhopadhyay, Department of Computer Science and Engineering, University of Kalyani, Kalyani, India
      Ujjwal Maulik, Department of Computer Science and Engineering, Jadavpur University, Kolkata, India
      Sanghamitra Bandyopadhyay, Machine Intelligence Unit, Indian Statistical Institute, Kolkata, India
      Journal In Silico Biology

      Online ISSN 1386-6338
      Journal Volume Volume 11
      Journal Issue Volume 11, Number 1-2 / 2011/2012
      PubDate: Wed, 04 Apr 2012 18:31:20 GMT
       
 
 
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