Search results for "Data type"
showing 10 items of 1183 documents
Dissipation in suspension system augmented by piezoelectric stack: port-Hamiltonian approach
2020
Analysis of damping in semi-active and active suspension systems is prerequisite for an advanced control and, eventually, energy harvesting functions. This paper addresses the damping in suspension system augmented by the piezoelectric (PE) stack. The Hamiltonian system approach with port-power modeling of single subsystems is used for describing and studying the dissipative properties of piezoelectric stack element, integrated in series with a standard quarter-car suspension. The slightly improved, compared to the underlying passive suspension system, frequency response of the sprung mass acceleration is demonstrated. Moreover, the overall power flow in the system, caused by the disturbing…
Evaluating the stability of pharmacophore features using molecular dynamics simulations.
2016
Abstract Molecular dynamics simulations of twelve protein—ligand systems were used to derive a single, structure based pharmacophore model for each system. These merged models combine the information from the initial experimental structure and from all snapshots saved during the simulation. We compared the merged pharmacophore models with the corresponding PDB pharmacophore models, i.e., the static models generated from an experimental structure in the usual manner. The frequency of individual features, of feature types and the occurrence of features not present in the static model derived from the experimental structure were analyzed. We observed both pharmacophore features not visible in …
FastaHerder2: Four Ways to Research Protein Function and Evolution with Clustering and Clustered Databases.
2016
The accelerated growth of protein databases offers great possibilities for the study of protein function using sequence similarity and conservation. However, the huge number of sequences deposited in these databases requires new ways of analyzing and organizing the data. It is necessary to group the many very similar sequences, creating clusters with automated derived annotations useful to understand their function, evolution, and level of experimental evidence. We developed an algorithm called FastaHerder2, which can cluster any protein database, putting together very similar protein sequences based on near-full-length similarity and/or high threshold of sequence identity. We compressed 50…
Variable Ranking Feature Selection for the Identification of Nucleosome Related Sequences
2018
Several recent works have shown that K-mer sequence representation of a DNA sequence can be used for classification or identification of nucleosome positioning related sequences. This representation can be computationally expensive when k grows, making the complexity in spaces of exponential dimension. This issue effects significantly the classification task computed by a general machine learning algorithm used for the purpose of sequence classification. In this paper, we investigate the advantage offered by the so-called Variable Ranking Feature Selection method to select the most informative k − mers associated to a set of DNA sequences, for the final purpose of nucleosome/linker classifi…
Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies
2016
Mieth, Bettina et al.
SpaceScanner: COPASI wrapper for automated management of global stochastic optimization experiments
2017
Abstract Motivation Due to their universal applicability, global stochastic optimization methods are popular for designing improvements of biochemical networks. The drawbacks of global stochastic optimization methods are: (i) no guarantee of finding global optima, (ii) no clear optimization run termination criteria and (iii) no criteria to detect stagnation of an optimization run. The impact of these drawbacks can be partly compensated by manual work that becomes inefficient when the solution space is large due to combinatorial explosion of adjustable parameters or for other reasons. Results SpaceScanner uses parallel optimization runs for automatic termination of optimization tasks in case…
Identification of control targets in Boolean molecular network models via computational algebra
2015
Motivation: Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The pot…
SWhybrid: A Hybrid-Parallel Framework for Large-Scale Protein Sequence Database Search
2017
Computer architectures continue to develop rapidly towards massively parallel and heterogeneous systems. Thus, easily extensible yet highly efficient parallelization approaches for a variety of platforms are urgently needed. In this paper, we present SWhybrid, a hybrid computing framework for large-scale biological sequence database search on heterogeneous computing environments with multi-core or many-core processing units (PUs) based on the Smith- Waterman (SW) algorithm. To incorporate a diverse set of PUs such as combinations of CPUs, GPUs and Xeon Phis, we abstract them as SIMD vector execution units with different number of lanes. We propose a machine model, associated with a unified …
An Integrative Framework for the Construction of Big Functional Networks
2018
We present a methodology for biological data integration, aiming at building and analysing large functional networks which model complex genotype-phenotype associations. A functional network is a graph where nodes represent cellular components (e.g., genes, proteins, mRNA, etc.) and edges represent associations among such molecules. Different types of components may cohesist in the same network, and associations may be related to physical[biochemical interactions or functional/phenotipic relationships. Due to both the large amount of involved information and the computational complexity typical of the problems in this domain, the proposed framework is based on big data technologies (Spark a…
Discovering unbounded unions of regular pattern languages from positive examples
1996
The problem of learning unions of certain pattern languages from positive examples is considered. We restrict to the regular patterns, i.e., patterns where each variable symbol can appear only once, and to the substring patterns, which is a subclass of regular patterns of the type xαy, where x and y are variables and α is a string of constant symbols. We present an algorithm that, given a set of strings, finds a good collection of patterns covering this set. The notion of a ‘good covering’ is defined as the most probable collection of patterns likely to be present in the examples, assuming a simple probabilistic model, or equivalently using the Minimum Description Length (MDL) principle. Ou…