The mixture-Gaussian model-based clustering method has received much attention in clustering gene expression profiles in the literature of bioinformatics. However, this method suffers from two difficulties in applications. The first one is on the parameter estimation, which becomes difficult when the dimension of the data is high or the size of a cluster is small. The second one is on the norma...

white matter lesions (wmls) are commonly observed in strokepatients with small vessel disease (svd) and are thought toresult from a progressive, irreversible disease process followingarteriolosclerosis. in this study, we report a case of partialdisappearance of wmls 1 year after a lacunar stroke in a69-year-old man with evidence of svd. we also discuss possiblemechanisms associated with this ob...

Swine vesicular disease (SVD) is a highly contagious viral disease that causes vesicular disease in pigs. The importance of the disease is due to its indistinguishable clinical signs from those of foot-and-mouth disease, which prevents international trade of swine and related products. SVD-specific antibody detection via an enzyme-linked immunosorbent assay (ELISA) is the most versatile and com...

introduction non-invasive fluorescent reflectance imaging (fri) is used for accessing physiological and molecular processes in biological media. the aim of this article is to separate the overlapping emission spectra of quantum dots within tissue-equivalent phantom using svd, jacobi svd, and nmf methods in the fri mode. materials and methods in this article, a tissue-like phantom and an optical...

Discovering protein sequence motif information is one of the most crucial tasks in bioinformatics research. In this work, we try to obtain protein recurring patterns which are universally conserved across protein family boundaries. In order to generate higher quality protein sequence motif information from Protein Sequence Culling Server (PISCES) dataset, we tried several different advanced clu...

We study the topic of dimensionality reduction for k-means clustering. Dimensionality reduction encompasses the union of two approaches: 1) feature selection and 2) feature extraction. A feature selection-based algorithm for k-means clustering selects a small subset of the input features and then applies k-means clustering on the selected features. A feature extraction-based algorithm for k-mea...

Background: Temporomandibular joint disorder (TMD) might be manifested as structural changes in bone through modification, adaptation or direct destruction. We propose to use Local Binary Pattern (LBP) characteristics and histogram-oriented gradients on the recorded images as a diagnostic tool in TMD assessment.Material and Methods: CBCT images of 66 patients (132 joints) with TMD and 66 normal...

Manual grading of students’ work takes a long time and it is stressful. Evaluator may be holistic or analytic, lenient non-lenient, experienced inexperienced; which leads to non-uniformity in the assessment. Therefore, essential do automated students' overcome human inadequacies through uniform assessment also, reduces workload evaluators. A novel automatic PowerPoint presentation skills using ...