50 research outputs found
Classification of heterogeneous microarray data by maximum entropy kernel
<p>Abstract</p> <p>Background</p> <p>There is a large amount of microarray data accumulating in public databases, providing various data waiting to be analyzed jointly. Powerful kernel-based methods are commonly used in microarray analyses with support vector machines (SVMs) to approach a wide range of classification problems. However, the standard vectorial data kernel family (linear, RBF, etc.) that takes vectorial data as input, often fails in prediction if the data come from different platforms or laboratories, due to the low gene overlaps or consistencies between the different datasets.</p> <p>Results</p> <p>We introduce a new type of kernel called maximum entropy (ME) kernel, which has no pre-defined function but is generated by kernel entropy maximization with sample distance matrices as constraints, into the field of SVM classification of microarray data. We assessed the performance of the ME kernel with three different data: heterogeneous kidney carcinoma, noise-introduced leukemia, and heterogeneous oral cavity carcinoma metastasis data. The results clearly show that the ME kernel is very robust for heterogeneous data containing missing values and high-noise, and gives higher prediction accuracies than the standard kernels, namely, linear, polynomial and RBF.</p> <p>Conclusion</p> <p>The results demonstrate its utility in effectively analyzing promiscuous microarray data of rare specimens, e.g., minor diseases or species, that present difficulty in compiling homogeneous data in a single laboratory.</p
Aspergillus fumigatus carrying TR34/L98H resistance allele causing complicated suppurative otitis media in Tanzania: Call for improved diagnosis of fungi in sub-Saharan Africa
Whole-genome genotyping of grape using a panel of microsatellite
The use of microsatellite markers in large-scale genetic studies is limited by its low throughput and high cost and labor requirements. Here, we provide a panel of 45 multiplex PCRs for fast and cost-efficient genome-wide fluorescence-based microsatellite analysis in grapevine. The developed multiplex PCRs panel (with up to 15-plex) enables the scoring of 270 loci covering all the grapevine genome (9 to 20 loci/chromosome) using only 45 PCRs and sequencer runs. The 45 multiplex PCRs were validated using a diverse grapevine collection of 207 accessions, selected to represent most of the cultivated Vitis vinifera genetic diversity. Particular attention was paid to quality control throughout the whole process (assay replication, null allele detection, ease of scoring). Genetic diversity summary statistics and features of electrophoretic profiles for each studied marker are provided, as are the genotypes of 25 common cultivars that could be used as references in other studies
Study of metallo-β-lactamase production in clinical isolates of Pseudomonas aeruginosa
A study of metallo-β-lactamase (MBL) production was done in
clinical isolates of Pseudomonas aeruginosa . Isolates resistant to
ceftazidime and imipenem were screened for MBL production by double
disc synergy test (DDST) and minimum inhibitory concentration reduction
test. There was complete correlation between two methods for imipenem.
For ceftazidime, there was correlation between the two methods in all
except four strains. In the screening test for MBL, ceftazidime - EDTA
combination was better than imipenem - EDTA combination. 8.05% strains
were MBL producers. Presence of MBL producer P. aeruginosa is a cause
of concern. Simple DDST can be helpful for monitoring of these emerging
resistant determinants