Search results for "Abstract data type"
showing 10 items of 1140 documents
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…
Main Steps in Image Processing and Quantification: The Analysis Workflow
2019
In the last decades, the variety of programs, algorithms, and strategies that researchers have at their disposal to process and analyze image files has grown extensively. However, these are only pointless tools if not applied with the careful planning required to achieve a succesful image analysis. In order to do so, the analyst must establish a meaningful and effective sequence of orderly operations that is able to (1) overcome all the problems derived from the image manipulation and (2) successfully resolve the question that was originally posed. In this chapter, the authors suggest a set of strategies and present a reflection on the main milestones that compose the image processing workf…
Reverse-safe data structures for text indexing
2021
We introduce the notion of reverse-safe data structures. These are data structures that prevent the reconstruction of the data they encode (i.e., they cannot be easily reversed). A data structure D is called z-reverse-safe when there exist at least z datasets with the same set of answers as the ones stored by D. The main challenge is to ensure that D stores as many answers to useful queries as possible, is constructed efficiently, and has size close to the size of the original dataset it encodes. Given a text of length n and an integer z, we propose an algorithm which constructs a z-reverse-safe data structure that has size O(n) and answers pattern matching queries of length at most d optim…