Search results for "ALGORITHMS"
showing 10 items of 1716 documents
Conduct disorder and ADHD: evaluation of conduct problems as a categorical and quantitative trait in the international multicentre ADHD genetics stud…
2008
Contains fulltext : 71374.pdf (Publisher’s version ) (Closed access) Attention-deficit/hyperactivity disorder (ADHD) is typically characterized by inattention, excessive motor activity, impulsivity, and distractibility. Individuals with ADHD have significant impairment in family and peer relations, academic functioning, and show high co-morbidity with a wide range of psychiatric disorders including oppositional defiant disorder (ODD), conduct disorder (CD), anxiety disorder, depression, substance abuse, and pervasive developmental disorder (PDD). Family studies suggest that ADHD + CD represents a specific subtype of the ADHD disorder with familial risk factors only partly overlapping with t…
Gene Duplication Models and Reconstruction of Gene Regulatory Network Evolution from Network Structure
2016
The work was supported by Latvian Council of Science grant 258/2012 and Latvian State Research programme project NexIT (2014-2017).
Evidence of Recombination in Intrapatient Populations of Hepatitis C Virus.
2008
Hepatitis C virus (HCV) is a major cause of liver disease worldwide and a potential cause of substantial morbidity and mortality in the future. HCV is characterized by a high level of genetic heterogeneity. Although homologous recombination has been demonstrated in many members of the family Flaviviridae, to which HCV belongs, there are only a few studies reporting recombination on natural populations of HCV, suggesting that these events are rare in vivo. Furthermore, these few studies have focused on recombination between different HCV genotypes/subtypes but there are no reports on the extent of intra-genotype or intra-subtype recombination between viral strains infecting the same patient.…
Population genetic analysis of bi-allelic structural variants from low-coverage sequence data with an expectation-maximization algorithm
2014
Background Population genetics and association studies usually rely on a set of known variable sites that are then genotyped in subsequent samples, because it is easier to genotype than to discover the variation. This is also true for structural variation detected from sequence data. However, the genotypes at known variable sites can only be inferred with uncertainty from low coverage data. Thus, statistical approaches that infer genotype likelihoods, test hypotheses, and estimate population parameters without requiring accurate genotypes are becoming popular. Unfortunately, the current implementations of these methods are intended to analyse only single nucleotide and short indel variation…
Estimation of Purkinje trees from electro-anatomical mapping of the left ventricle using minimal cost geodesics
2015
The electrical activation of the heart is a complex physiological process that is essential for the understanding of several cardiac dysfunctions, such as ventricular tachycardia (VT). Nowadays, patient-specific activation times on ventricular chambers can be estimated from electro-anatomical maps, providing crucial information to clinicians for guiding cardiac radio-frequency ablation treatment. However, some relevant electrical pathways such as those of the Purkinje system are very difficult to interpret from these maps due to sparsity of data and the limited spatial resolution of the system. We present here a novel method to estimate these fast electrical pathways from the local activati…
Reliability Analysis of a Controlled Stage-Constructed and Reinforced Embankment on Soft Ground Using 2D and 3D Models
2020
Geosynthetic reinforcement has become a very practical technique to improve geotechnical structure safety. In spite of improved soil behavior, structures are affected by uncertainties related to soil and reinforcement material properties. This paper aims to present a reliability analysis in order to take statistical information (uncertainties) into account in a safety analysis of reinforced embankments. The analysis was used in a case study on a controlled stage-constructed embankment on soft ground in order to investigate its probabilistic stability. Modeling was performed by commercial geotechnical software usage (GeoStudio and RocScience packs, SIGMA/W+SLOPE/W and SLIDE³, respectively) a…
Gray code for permutations with a fixed number of cycles
2007
AbstractWe give the first Gray code for the set of n-length permutations with a given number of cycles. In this code, each permutation is transformed into its successor by a product with a cycle of length three, which is optimal. If we represent each permutation by its transposition array then the obtained list still remains a Gray code and this allows us to construct a constant amortized time (CAT) algorithm for generating these codes. Also, Gray code and generating algorithm for n-length permutations with fixed number of left-to-right minima are discussed.
Donor/recipient algorithm for management of the middle hepatic vein in right graft live donor liver transplantation
2010
Abstract Background The aim of this study was to delineate an algorithm for donor and recipient criteria and middle hepatic vein (MHV) management in right-graft live-donor liver transplantation (LDLT) on the basis of computerized 3-dimensional computed tomographic image analysis. Methods Data on 94 consecutive right-graft LDLTs were prospectively collected. Graft and remnant data for the first 23 cases were retrospectively evaluated by means of 3-dimensional computed tomographic reconstructions, and on the basis of that preliminary series, a graft selection algorithm using 3 parameters—hepatic vein dominance classification, graft and remnant graft volume/body weight ratios, and congestion v…
Incremental Gaussian Discriminant Analysis based on Graybill and Deal weighted combination of estimators for brain tumour diagnosis
2011
In the last decade, machine learning (ML) techniques have been used for developing classifiers for automatic brain tumour diagnosis. However, the development of these ML models rely on a unique training set and learning stops once this set has been processed. Training these classifiers requires a representative amount of data, but the gathering, preprocess, and validation of samples is expensive and time-consuming. Therefore, for a classical, non-incremental approach to ML, it is necessary to wait long enough to collect all the required data. In contrast, an incremental learning approach may allow us to build an initial classifier with a smaller number of samples and update it incrementally…
Fast Image Restoration Algorithms Based on PDE Models Using Modified Hopfield Neural Network
2010
Two image restoration algorithms based on modified Hop field neural network and variational partial differential equations (PDE) were proposed in our previous work [1, 2]. But the convergence rate of the proposed algorithms was slow. In this paper, we develop a fast update rule based on modified Hop field neural network (MHNN) of continuous state change and two fast image restoration algorithms. Experimental results show that, when compared with the previous algorithms, our proposed algorithms have better performance both in convergence rate and in image restoration quality.