Machine Learning methods have been widely used in bioinformatics, mainly for data classification and pattern recognition. The detection of genes in DNA sequences is still an open problem. Identifying the promoter region laying prior the gene itself is an important aid to detect a gene. This paper aims at applying several Machine Learning methods to the construction of classifiers for detection ...

Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensiona...

A vast amount of knowledge exists within biomedical literature, publications, clinical notes and online content. Identifying hidden, interesting or previously unknown biomedical knowledge from free text resources using an automated approach remains an important challenge. Towards this problem, we investigate the use of deep learning methods that have shown significant promise in identifying hid...

In this paper we present an efficient algorithm for camera tracking applicable for mobile devices. In particular, the work is motivated by the limited computational power and memory, precluding the use of existing methods for estimation of the 6-DoF pose of a mobile device (camera) relative to a previously unknown planar object. Similar to existing methods, we introduce a keypoint based approac...

The identification of conditional dependences in longitudinal data is provided through structure learning of dynamic Bayesian networks (DBN). Several methods for DBN learning are concerned with identifying inter-slice dependences, but often disregard the intra-slice connectivity. We propose an algorithm that jointly finds the optimal inter and intra time-slice connectivity in a transition netwo...

Convolution kernels for trees provide simple means for learning with tree-structured data. The computation time of tree kernels is quadratic in the size of the trees, since all pairs of nodes need to be compared. Thus, large parse trees, obtained from HTML documents or structured network data, render convolution kernels inapplicable. In this article, we propose an effective approximation techni...

User attitude and their perceptions are increasingly being explored by a variation of methods. This thesis addresses the perception that one might have for employing smart glasses as a potential online educational tool. Furthermore, it explores the challenges that are associated with designing educational apps for smart glasses as a medium for e-learning in general. For addressing and identifyi...

PURPOSE OF REVIEW Mixtures, or combinations and interactions between multiple environmental exposures, are hypothesized to be causally linked with disease and health-related phenotypes. Established and emerging molecular measurement technologies to assay the exposome, the comprehensive battery of exposures encountered from birth to death, promise a new way of identifying mixtures in disease in ...