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  1. Article ; Online: Role of genetic heterogeneity in determining the epidemiological severity of H1N1 influenza.

    Narmada Sambaturu / Sumanta Mukherjee / Martín López-García / Carmen Molina-París / Gautam I Menon / Nagasuma Chandra

    PLoS Computational Biology, Vol 14, Iss 3, p e

    2018  Volume 1006069

    Abstract: Genetic differences contribute to variations in the immune response mounted by different individuals to a pathogen. Such differential response can influence the spread of infectious disease, indicating why such diseases impact some populations more than ... ...

    Abstract Genetic differences contribute to variations in the immune response mounted by different individuals to a pathogen. Such differential response can influence the spread of infectious disease, indicating why such diseases impact some populations more than others. Here, we study the impact of population-level genetic heterogeneity on the epidemic spread of different strains of H1N1 influenza. For a population with known HLA class-I allele frequency and for a given H1N1 viral strain, we classify individuals into sub-populations according to their level of susceptibility to infection. Our core hypothesis is that the susceptibility of a given individual to a disease such as H1N1 influenza is inversely proportional to the number of high affinity viral epitopes the individual can present. This number can be extracted from the HLA genetic profile of the individual. We use ethnicity-specific HLA class-I allele frequency data, together with genome sequences of various H1N1 viral strains, to obtain susceptibility sub-populations for 61 ethnicities and 81 viral strains isolated in 2009, as well as 85 strains isolated in other years. We incorporate these data into a multi-compartment SIR model to analyse the epidemic dynamics for these (ethnicity, viral strain) epidemic pairs. Our results show that HLA allele profiles which lead to a large spread in individual susceptibility values can act as a protective barrier against the spread of influenza. We predict that populations skewed such that a small number of highly susceptible individuals coexist with a large number of less susceptible ones, should exhibit smaller outbreaks than populations with the same average susceptibility but distributed more uniformly across individuals. Our model tracks some well-known qualitative trends of influenza spread worldwide, suggesting that HLA genetic diversity plays a crucial role in determining the spreading potential of different influenza viral strains across populations.
    Keywords Biology (General) ; QH301-705.5
    Subject code 612
    Language English
    Publishing date 2018-03-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Convergence Time Evaluation of Algorithms in MANETs

    Krittaya Chunhaviriyakul / Narmada Sambaturu / Annapurna P.Patil

    International Journal of Computer Science and Information Security, Vol 5, Iss 1, Pp 141-

    2009  Volume 149

    Abstract: Since the advent of wireless communication, the need for mobile ad hoc networks has been growing exponentially. This has opened up a Pandora’s Box of algorithms for dealing with mobile ad hoc networks, or MANETs, as they are generally referred to. Most ... ...

    Abstract Since the advent of wireless communication, the need for mobile ad hoc networks has been growing exponentially. This has opened up a Pandora’s Box of algorithms for dealing with mobile ad hoc networks, or MANETs, as they are generally referred to. Most attempts made at evaluating these algorithms so far have focused on parameters such as throughput, packet delivery ratio, overhead etc. An analysis of the convergence times of these algorithms is still an open issue. The work carried out fills this gap by evaluating the algorithms on the basis of convergence time. Algorithms for MANETs can be classified into 3 categories: reactive, proactive, and hybrid protocols. In this project, we compare the convergence times of representative algorithms in each category, namely Ad hoc On-Demand Distance Vector (AODV)-reactive, Destination Sequence Distance Vector protocol (DSDV)-proactive, and Temporally Ordered Routing Algorithm (TORA)-hybrid. The algorithm performances are compared by simulating them in ns2. Tcl is used to conduct the simulations, while perl is used to extract data from the simulation output and calculate convergence time. The design of the experiments carriered on is documented using Unified modeling Language. Also, a user interface is created using perl, which enables the user to either run a desired simulation and measure convergence time, or measure the convergence time of a simulation that has been run earlier. After extensive testing, it was found that the two algorithms AODV and DSDV are suited to opposite ends of the spectrum of possible scenarios. AODV was observed to outperform DSDV when the node density was low and pause time was high (sparsely populated very dynamic networks), while DSDV performed better when the node density was high and pause time was low (densely populated, relatively static networks). The implementation of TORA in ns2 was found to contain bugs, and hence analysis of TORA was not possible.Future enhancements include rectifying the bugs in TORA and performing convergence time analysis of TORA as well. Also, a system could be developed which can switch between protocols in real time if it is found that another protocol is better suited to the current network environment.
    Keywords IJCSIS ; Journal of Computer Science ; Electronic computers. Computer science ; QA75.5-76.95 ; Instruments and machines ; QA71-90 ; Mathematics ; QA1-939 ; Science ; Q ; DOAJ:Computer Science ; DOAJ:Technology and Engineering
    Subject code 005
    Language English
    Publishing date 2009-09-01T00:00:00Z
    Publisher LJS Publisher and IJCSIS Press
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Correction

    Jayavel Sridhar / Narmada Sambaturu / Radhakrishna Sabarinathan / Hong-Yu Ou / Zixin Deng / Kanagaraj Sekar / Ziauddin Ahamed Rafi / Kumar Rajakumar

    PLoS ONE, Vol 5, Iss

    sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes.

    2010  Volume 9

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2010-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: Correction

    Jayavel Sridhar / Narmada Sambaturu / Radhakrishna Sabarinathan / Hong-Yu Ou / Zixin Deng / Kanagaraj Sekar / Ziauddin Ahamed Rafi / Kumar Rajakumar

    PLoS ONE, Vol 5, Iss

    sRNAscanner: A Computational Tool for Intergenic Small RNA Detection in Bacterial Genomes

    2010  Volume 9

    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2010-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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    Inter-library loan at ZB MED

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  5. Article ; Online: sRNAscanner

    Jayavel Sridhar / Narmada Sambaturu / Radhakrishnan Sabarinathan / Hong-Yu Ou / Zixin Deng / Kanagaraj Sekar / Ziauddin Ahamed Rafi / Kumar Rajakumar

    PLoS ONE, Vol 5, Iss 8, p e

    a computational tool for intergenic small RNA detection in bacterial genomes.

    2010  Volume 11970

    Abstract: BACKGROUND: Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches ... ...

    Abstract BACKGROUND: Bacterial non-coding small RNAs (sRNAs) have attracted considerable attention due to their ubiquitous nature and contribution to numerous cellular processes including survival, adaptation and pathogenesis. Existing computational approaches for identifying bacterial sRNAs demonstrate varying levels of success and there remains considerable room for improvement. METHODOLOGY/PRINCIPAL FINDINGS: Here we have proposed a transcriptional signal-based computational method to identify intergenic sRNA transcriptional units (TUs) in completely sequenced bacterial genomes. Our sRNAscanner tool uses position weight matrices derived from experimentally defined E. coli K-12 MG1655 sRNA promoter and rho-independent terminator signals to identify intergenic sRNA TUs through sliding window based genome scans. Analysis of genomes representative of twelve species suggested that sRNAscanner demonstrated equivalent sensitivity to sRNAPredict2, the best performing bioinformatics tool available presently. However, each algorithm yielded substantial numbers of known and uncharacterized hits that were unique to one or the other tool only. sRNAscanner identified 118 novel putative intergenic sRNA genes in Salmonella enterica Typhimurium LT2, none of which were flagged by sRNAPredict2. Candidate sRNA locations were compared with available deep sequencing libraries derived from Hfq-co-immunoprecipitated RNA purified from a second Typhimurium strain (Sittka et al. (2008) PLoS Genetics 4: e1000163). Sixteen potential novel sRNAs computationally predicted and detected in deep sequencing libraries were selected for experimental validation by Northern analysis using total RNA isolated from bacteria grown under eleven different growth conditions. RNA bands of expected sizes were detected in Northern blots for six of the examined candidates. Furthermore, the 5'-ends of these six Northern-supported sRNA candidates were successfully mapped using 5'-RACE analysis. CONCLUSIONS/SIGNIFICANCE: We have developed, computationally examined and ...
    Keywords Medicine ; R ; Science ; Q
    Subject code 572
    Language English
    Publishing date 2010-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

    Full text online

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    Inter-library loan at ZB MED

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