Efficient Boolean implementation of universal sequence maps (bUSM).
Ontology highlight
ABSTRACT:
SUBMITTER: Schwacke J
PROVIDER: S-EPMC137598 | biostudies-literature | 2002 Oct
REPOSITORIES: biostudies-literature
Publications
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]
Similar Datasets
Project description:MOTIVATION:Molecular interaction maps have emerged as a meaningful way of representing biological mechanisms in a comprehensive and systematic manner. However, their static nature provides limited insights to the emerging behaviour of the described biological system under different conditions. Computational modelling provides the means to study dynamic properties through in silico simulations and perturbations. We aim to bridge the gap between static and dynamic representations of biological systems with CaSQ, a software tool that infers Boolean rules based on the topology and semantics of molecular interaction maps built with CellDesigner. RESULTS:We developed CaSQ by defining conversion rules and logical formulas for inferred Boolean models according to the topology and the annotations of the starting molecular interaction maps. We used CaSQ to produce executable files of existing molecular maps that differ in size, complexity and the use of Systems Biology Graphical Notation (SBGN) standards. We also compared, where possible, the manually built logical models corresponding to a molecular map to the ones inferred by CaSQ. The tool is able to process large and complex maps built with CellDesigner (either following SBGN standards or not) and produce Boolean models in a standard output format, Systems Biology Marked Up Language-qualitative (SBML-qual), that can be further analyzed using popular modelling tools. References, annotations and layout of the CellDesigner molecular map are retained in the obtained model, facilitating interoperability and model reusability. AVAILABILITY AND IMPLEMENTATION:The present tool is available online: https://lifeware.inria.fr/?soliman/post/casq/ and distributed as a Python package under the GNU GPLv3 license. The code can be accessed here: https://gitlab.inria.fr/soliman/casq. SUPPLEMENTARY INFORMATION:Supplementary data are available at Bioinformatics online.
| S-EPMC7575051 | biostudies-literature
Project description:Among the promising approaches for implementing high-performance computing, reconfigurable logic gates and logic-in-memory (LIM) approaches have been drawing increased research attention. These allow for improved functional scaling of a chip, owing to the improved functionality per unit area. Although numerous studies have been conducted independently for either reconfigurable logic or LIM units, attempts to construct a hybrid structure based on reconfigurable logic and LIM units remain relatively rare. In this study, we merge reconfigurable logic gates and LIM units to achieve a universal logic-in-memory (ULIM) cell for enabling all basic Boolean logic operations and data storage in a single cell. A ULIM cell consisting of silicon memory devices with reconfigurable n- and p-program modes can reconfigure logic operations within the complete set of Boolean logic operations. Moreover, the ULIM cell exhibits memory behaviors for storing output logic values without supply voltages for a certain period, resulting in zero static power consumption. Hence, this study provides a way to realize high-performance electronics by utilizing the silicon devices with a hybrid function of reconfigurable logic and LIM.
| S-EPMC9684131 | biostudies-literature
Project description:Coupling molecular biology to high throughput sequencing has revolutionized the study of biology. Molecular genomics techniques are continually refined to provide higher resolution mapping of nucleic acid interactions and nucleic acid structure. These assays are converging on single-nucleotide resolution measurements, but the sequence preferences of molecular biology enzymes can interfere with the accurate interpretation of the data. Enzymatic sequence preferences manifest more prominently as the resolution of these assays increase. We developed seqOutBias to seek out enzymatic sequence bias from experimental data and scale individual sequence reads to correct the bias. We show that this software efficiently and successfully corrects the sequence bias resulting from DNase-seq, TACh-seq, ATAC-seq, MNase-seq, and PRO-seq data.
2016-12-21 | GSE92674 | GEO
Project description:Boolean satisfiability is a propositional logic problem of interest in multiple fields, e.g., physics, mathematics, and computer science. Beyond a field of research, instances of the SAT problem, as it is known, require efficient solution methods in a variety of applications. It is the decision problem of determining whether a Boolean formula has a satisfying assignment, believed to require exponentially growing time for an algorithm to solve for the worst-case instances. Yet, the efficient solution of many classes of Boolean formulae eludes even the most successful algorithms, not only for the worst-case scenarios, but also for typical-case instances. Here, we introduce a memory-assisted physical system (a digital memcomputing machine) that, when its non-linear ordinary differential equations are integrated numerically, shows evidence for polynomially-bounded scalability while solving "hard" planted-solution instances of SAT, known to require exponential time to solve in the typical case for both complete and incomplete algorithms. Furthermore, we analytically demonstrate that the physical system can efficiently solve the SAT problem in continuous time, without the need to introduce chaos or an exponentially growing energy. The efficiency of the simulations is related to the collective dynamical properties of the original physical system that persist in the numerical integration to robustly guide the solution search even in the presence of numerical errors. We anticipate our results to broaden research directions in physics-inspired computing paradigms ranging from theory to application, from simulation to hardware implementation.
| S-EPMC7665037 | biostudies-literature
Project description:Networks (or graphs) are used to model the dyadic relations between entities in complex systems. Analyzing the properties of the networks reveal important characteristics of the underlying system. However, in many disciplines, including social sciences, bioinformatics, and technological systems, multiple relations exist between entities. In such cases, a simple graph is not sufficient to model these multiple relations, and a multilayer network is a more appropriate model. In this paper, we explore community detection in multilayer networks. Specifically, we propose a novel network decoupling strategy for efficiently combining the communities in the different layers using the Boolean primitives AND, OR, and NOT. Our proposed method, network decoupling, is based on analyzing the communities in each network layer individually and then aggregating the analysis results. We (i) describe our network decoupling algorithms for finding communities, (ii) present how network decoupling can be used to express different types of communities in multilayer networks, and (iii) demonstrate the effectiveness of using network decoupling for detecting communities in real-world and synthetic data sets. Compared to other algorithms for detecting communities in multilayer networks, our proposed network decoupling method requires significantly lower computation time while producing results of high accuracy. Based on these results, we anticipate that our proposed network decoupling technique will enable a more detailed analysis of multilayer networks in an efficient manner.
| S-EPMC10481956 | biostudies-literature
Project description:The rise of emerging technologies such as Big Data, the Internet of Things, and artificial intelligence, which requires efficient power schemes, is driving brainstorming in data computing and storage technologies. In this study, merely relying on the fundamental structure of two memristors and a resistor, arbitrary Boolean logic can be reconfigured and calculated in two steps, while no additional voltage sources are needed beyond "±VP " and 0, and all state reversals are based on memristor set switching. Utilizing the proposed logic scheme in an elegant form of unity structure and minimum cost, the implementation of a 1-bit adder is demonstrated economically, and a promising circuit scheme for the N-bit adder is exhibited. Some critical issues including the crosstalk problem, energy consumption, and peripheral circuits are further simulated and discussed. Compared with existing works on memristive logic, such methods support building a memristor-based digital in-memory calculation system with high functional reconfigurability, simple voltage sources, and low power and area consumption.
| S-EPMC9130921 | biostudies-literature
Project description:The unique complementary switching behaviour of complementary resistive switches (CRSs) makes them very attractive for logic applications. The implementation of complete Boolean logic functions in a single CRS cell is certainly an extremely important step towards the commercialisation of related logic circuits, but it has not been accomplished to date. Here, we report two methods for the implementation of complete Boolean logic functions in a single CRS cell. The first method is based on the intrinsic switchable diode of a peculiar CRS cell that is composed of two anti-serial bipolar resistive switches with a rectifying high resistance state, while the second method is based directly on the complementary switching behaviour itself of any single CRS cell. The feasibilities of both methods have been theoretically predicted and then experimentally demonstrated on the basis of a Ta/Ta2O5/Pt/Ta2O5/Ta CRS cell. Therefore, these two methods-in particular the complementary switching behaviour itself-based method, which has natural immunity to the sneak-path issue of crossbar logic circuits-are believed to be capable of significantly advancing both our understanding and commercialization of related logic circuits. Moreover, peculiar CRS cells have been demonstrated to be feasible for tri-level storage, which can serve as an alternative method of realising ultra-high-density data storage.
| S-EPMC4614354 | biostudies-literature
Project description:In our previous computational work, we showed that gene digital circuits can be automatically designed in an electronic fashion. This demands, first, a conversion of the truth table into Boolean formulas with the Karnaugh map method and, then, the translation of the Boolean formulas into circuit schemes organized into layers of Boolean gates and Pools of signal carriers. In our framework, gene digital circuits that take up to three different input signals (chemicals) arise from the composition of three kinds of basic Boolean gates, namely YES, NOT, and AND. Here we present a library of YES, NOT, and AND gates realized via plasmidic DNA integration into the yeast genome. Boolean behavior is reproduced via the transcriptional control of a synthetic bipartite promoter that contains sequences of the yeast VPH1 and minimal CYC1 promoters together with operator binding sites for bacterial (i.e. orthogonal) repressor proteins. Moreover, model-driven considerations permitted us to pinpoint a strategy for re-designing gates when a better digital performance is required. Our library of well-characterized Boolean gates is the basis for the assembly of more complex gene digital circuits. As a proof of concepts, we engineered two 2-input OR gates, designed by our software, by combining YES and NOT gates present in our library.
| S-EPMC3926364 | biostudies-literature
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.
| S-EPMC3532238 | biostudies-literature
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.
| S-EPMC4810783 | biostudies-literature