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Efficient Boolean implementation of universal sequence maps (bUSM).

ABSTRACT: BACKGROUND:Recently, Almeida and Vinga offered a new approach for the representation of arbitrary discrete sequences, referred to as Universal Sequence Maps (USM), and discussed its applicability to genomic sequence analysis. Their work generalizes and extends Chaos Game Representation (CGR) of DNA for arbitrary discrete sequences. RESULTS:We have considered issues associated with the practical implementation of USMs and offer a variation on the algorithm that: 1) eliminates the overestimation of similar segment lengths, 2) permits the identification of arbitrarily long similar segments in the context of finite word length coordinate representations, 3) uses more computationally efficient operations, and 4) provides a simple conversion for recovering the USM coordinates. Computational performance comparisons and examples are provided. CONCLUSIONS:We have shown that the desirable properties of the USM encoding of nucleotide sequences can be retained in a practical implementation of the algorithm. In addition, the proposed implementation enables determination of local sequence identity at increased speed.

SUBMITTER: Schwacke J

PROVIDER: S-EPMC137598 | biostudies-literature | 2002 Oct

REPOSITORIES: biostudies-literature

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Efficient Boolean implementation of universal sequence maps (bUSM).

Schwacke John J Almeida Jonas S JS

BMC bioinformatics 20021021

<h4>Background</h4>Recently, Almeida and Vinga offered a new approach for the representation of arbitrary discrete sequences, referred to as Universal Sequence Maps (USM), and discussed its applicability to genomic sequence analysis. Their work generalizes and extends Chaos Game Representation (CGR) of DNA for arbitrary discrete sequences.<h4>Results</h4>We have considered issues associated with the practical implementation of USMs and offer a variation on the algorithm that: 1) eliminates the o ...[more]

PMID: 12387731

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Project description:BACKGROUND: Various computational models have been of interest due to their use in the modelling of gene regulatory networks (GRNs). As a logical model, probabilistic Boolean networks (PBNs) consider molecular and genetic noise, so the study of PBNs provides significant insights into the understanding of the dynamics of GRNs. This will ultimately lead to advances in developing therapeutic methods that intervene in the process of disease development and progression. The applications of PBNs, however, are hindered by the complexities involved in the computation of the state transition matrix and the steady-state distribution of a PBN. For a PBN with n genes and N Boolean networks, the complexity to compute the state transition matrix is O(nN22n) or O(nN2n) for a sparse matrix. RESULTS: This paper presents a novel implementation of PBNs based on the notions of stochastic logic and stochastic computation. This stochastic implementation of a PBN is referred to as a stochastic Boolean network (SBN). An SBN provides an accurate and efficient simulation of a PBN without and with random gene perturbation. The state transition matrix is computed in an SBN with a complexity of O(nL2n), where L is a factor related to the stochastic sequence length. Since the minimum sequence length required for obtaining an evaluation accuracy approximately increases in a polynomial order with the number of genes, n, and the number of Boolean networks, N, usually increases exponentially with n, L is typically smaller than N, especially in a network with a large number of genes. Hence, the computational efficiency of an SBN is primarily limited by the number of genes, but not directly by the total possible number of Boolean networks. Furthermore, a time-frame expanded SBN enables an efficient analysis of the steady-state distribution of a PBN. These findings are supported by the simulation results of a simplified p53 network, several randomly generated networks and a network inferred from a T cell immune response dataset. An SBN can also implement the function of an asynchronous PBN and is potentially useful in a hybrid approach in combination with a continuous or single-molecule level stochastic model. CONCLUSIONS: Stochastic Boolean networks (SBNs) are proposed as an efficient approach to modelling gene regulatory networks (GRNs). The SBN approach is able to recover biologically-proven regulatory behaviours, such as the oscillatory dynamics of the p53-Mdm2 network and the dynamic attractors in a T cell immune response network. The proposed approach can further predict the network dynamics when the genes are under perturbation, thus providing biologically meaningful insights for a better understanding of the dynamics of GRNs. The algorithms and methods described in this paper have been implemented in Matlab packages, which are attached as Additional files.

Project description:Transvaginal measurement of cervical length (CL) has been advocated as a screening tool to prevent preterm birth, but controversy remains regarding the overall utility of universal screening.We aimed to evaluate the acceptability of a universal CL screening program. Additionally we evaluated risk factors associated with declining screening and subsequent delivery outcomes of women who accepted or declined screening.This was a retrospective cohort study of transvaginal CL screening at a single institution from July 1, 2011, through December 31, 2014. Institutional protocol recommended transvaginal CL measurement at the time of anatomic survey between 17-23 weeks in all women with singleton, viable pregnancies, without current or planned cerclage, with patients able to opt out. Patients with CL ?20 mm were considered to have clinically significant cervical shortening and were offered treatment. We assessed acceptance rate, risk factors for declining CL screening, and the trend of acceptance of CL screening over time. We also calculated the prevalence of CL ?25, ?20, and ?15 mm, and estimated the association between CL screening and spontaneous preterm birth.Of 12,740 women undergoing anatomic survey during the study period, 10,871 (85.3%; 95% confidence interval [CI], 84.7-85.9%) underwent CL screening. Of those, 215 (2.0%) had a CL ?25 mm and 131 (1.2%) had a CL ?20 mm. After the first 6 months of implementation, there was no change in rates of acceptance of CL screening over time (P for trend = .15). Women were more likely to decline CL screening if they were African American (adjusted odds ratio [aOR], 2.17; 95% CI, 1.93-2.44), obese (aOR, 1.18; 95% CI, 1.06-1.31), multiparous (aOR, 1.45; 95% CI, 1.29-1.64), age <35 years (aOR, 1.24; 95% CI, 1.08-1.43), or smokers (aOR, 1.42; 95% CI, 1.20-1.68). Rates of spontaneous preterm birth <28 weeks were higher in those who declined CL screening (aOR, 2.01; 95% CI, 1.33-3.02).Universal CL screening was implemented successfully with 85% of women screened. Overall incidence of short cervix was low and women with significant risk factors for preterm birth were more likely to decline screening. Patients who declined CL screening were more likely to be African American, obese, multiparous, age <35 years, and smokers. Rates of early, but not late, spontaneous preterm birth were significantly higher among women who did not undergo CL screening.

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Efficient Boolean implementation of universal sequence maps (bUSM).

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Efficient Boolean implementation of universal sequence maps (bUSM).

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