The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
An efficient and reliable network alignment serves to find the mapping with maximum similarity between different networks, which is a way to improve our understanding of biology system and biological process. To build such network alignment is a foremost challenging task in computational biology because it involves the bipartite graph matching problem, which is an NP-hard problem. In this work, we...
Pebble game rigidity analysis is an efficient method for extracting rigidity and flexibility information of biomolecules without performing costly molecular dynamics simulations. The standard algorithm works on a multi-graph associated to a mechanical model constructed from an arbitrary atom-bond network. Motivated by large scale protein flexibility and simulated unfolding applications, we have developed...
In order to understand the structure and folding of proteins, Hydrophobic-Polar (HP) model on 2D square lattice is one of the most explored models but parity problem of square lattice make it inefficient for biological applications. This work is dedicated to solve parity issues in 2D square lattice model. This work proposes a revised energy function and presents a case study for protein structure...
Species distribution modeling (SDM) calculates a species’ probabilistic distribution by combining Environmental raster layers with species datasets. Such models can help to answer complex questions in Ecology/Biology/Health, e.g., by calculating impacts of climate changes in Biodiversity, or the potential for a disease spread (vectors’ modeling). Machine learning is largely applied in SDM, being the...
The Smith-Waterman algorithm, which produces the optimal local alignment between pairwise sequences, is universally used as a key component in bioinformatics fields. It is more sensitive than heuristic approaches, but also more time-consuming. To speed up the algorithm, Single-Instruction Multiple-Data (SIMD) instructions have been used to parallelize the algorithm by leveraging data parallel strategy...
Membrane computing also called P system, seeks to discover new computational models from the study of cellular membranes. In this study, we reported our initial efforts to classify Macao visitor expenditure profile using a membrane computing approach. Specifically, we designed a novel P system including specific membrane structure and membrane rules to realize an improved k-medoids clustering algorithm...
The LOD is an important technology of scene model management. The multi-resolution LOD based on viewpoint is one of the research focuses. In the paper, a progressive mesh algorithm based on edge collapse is improved, in which a distance between the viewpoint and model is regarded as a discriminant condition, and a half-edge collapse is used to simplify the model. The algorithm will realize the multi-resolution...
Planning for large-scale epidemiological outbreaks in livestock populations often involves executing compute-intensive disease spread simulations. To capture the probabilities of various outcomes, these simulations are executed several times over a collection of representative input scenarios, producing voluminous data. The resulting datasets contain valuable insights, including sequences of events...
The 2-body correlation function (2-BCF) is a group of statistical measurements that found applications in many scientific domains. One type of 2-BCF named the Spatial Distance Histogram (SDH) is of vital importance in describing the physical features of natural systems. While a naïve way of computing SDH requires quadratic time, efficient algorithms based on resolving nodes in spatial trees have been...
Finite mixture models have been widely used for the modelling and analysis of data from heterogeneous populations. Maximum likelihood estimation of the parameters is typically carried out via the Expectation-Maximization (EM) algorithm. The complexity of the implementation of the algorithm depends on the parametric distribution that is adopted as the component densities of the mixture model. In the...
Identification of gene expression patterns when studying complex and dynamic biological processes such as gene regulatory functions is critical. Gene expression is a continuous biological phenomenon and can be represented by a continuous function (curve). Each gene behaving in such a continuous functions often shares similar functional forms. However, patterns such as numbers, shape, and the identities...
With the parallelism and high-density storage, the biomolecular computing has been used to solve many graph theory problems. When the data set becomes huge in the big data age, the clustering algorithms are confronted with more challenging. The patterns with their Euclidean distances can be considered as a complete graph and the clustering problem also can be considered as the graph theory problem...
Given a graph G = (V, E), a node is called perfect (with respect to a set S ⊆ V) if its closed neighborhood contains exactly one node in set S, a node is called nearly perfect if it is not perfect but is adjacent to a perfect node. S is called a perfect neighborhood set if each node is either perfect or nearly perfect. We present the first self-stabilizing algorithm for computing a perfect neighborhood...
Today, scientific and business applications generate huge amounts of data. Users of data grid, who are distributed all over the grid geographically, need such data. So ensuring the access to this distributed data efficiently is one of the most important challenges in Data grid network. Data replication algorithms are known as the most common method used to overcome this problem. They distribute several...
This paper presents a new kind of learning algorithm to help agents learn sensorimotor skills through their contact with the environment. The learning mechanism is based on Skinner's theory of operant conditioning (OC), which is improving the probabilities of good actions, and reducing the probabilities of bad actions. The concept of curiosity is introduced as the intrinsic motivation for an agent...
Modeling an electromagnetic (EM) structure with curved boundaries using a conformal finite-difference time-domain (CFDTD) method retains a second order accuracy while using a staircased FDTD one only gives a first order accuracy. Although the CFDTD algorithm has been demonstrated being very accurate for simulating some vacuum electronic devices which usually operated at fundamental modes, this is...
In this paper, we present a DNA based algorithm to simulate the logic functionality of any Boolean Circuit. The inherent hybridization property of Deoxyribonucleic acid (DNA) is the key operation used throughout the model. The contribution of this paper is to introduce an algorithm involving a relatively less number of biochemical reactions. The proposed theoretical model is reusable and has a wide...
Version control for models is not yet supported in an adequate way. In this paper, we address three-way merging of model versions. Based on a common base version b, two alternative versions a1 and a2 were developed by copying and modifying the base version. To reconcile these changes, a merged version m is to be created as a common successor of a1 and a2. We present a graph algorithm to solve an important...
The reproduction and replication of reported scientific results is a hot topic within the academic community. The retraction of numerous studies from a wide range of disciplines, from climate science to bioscience, has drawn the focus of many commentators, but there exists a wider socio-cultural problem that pervades the scientific community. Sharing code, data and models often requires extra effort,...
Recently, the several applications of the probabilistic model based on two of the main concepts in quantum physics - a density matrix and the Born rule, have been introduced. It was shown that the model can be suitable for the modeling of learning algorithms in biologically plausible artificial neural networks framework, like it is the case of on-line learning algorithms for Independent /Principal/Minor...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.