Comparison in gene expression of secretory human endometrium using laser microdissection

Background  

The endometrium prepares for implantation under the control of steroid hormones. It has been suggested that there are complicated interactions between the epithelium and stroma in the endometrium during menstrual cycle. In this study, we demonstrate a difference in gene expression between the epithelial and stromal areas of the secretory human endometrium using microdissection and macroarray technique.     

Assessing the evolutionary rate of positional orthologous genes in prokaryotes using synteny data

Background  

Comparison of completely sequenced microbial genomes has revealed how fluid these genomes are. Detecting synteny blocks requires reliable methods to determining the orthologs among the whole set of homologs detected by exhaustive comparisons between each pair of completely sequenced genomes. This is a complex and difficult problem in the field of comparative genomics but will help to better understand the way prokaryotic genomes are evolving.     

Classification of Myoviridae bacteriophages using protein sequence similarity

Background  

We advocate unifying classical and genomic classification of bacteriophages by integration of proteomic data and physicochemical parameters. Our previous application of this approach to the entirely sequenced members of the Podoviridae fully supported the current phage classification of the International Committee on Taxonomy of Viruses (ICTV). It appears that horizontal gene transfer generally does not totally obliterate evolutionary relationships between phages.     

Inference of gene pathways using mixture Bayesian networks

Background  

Inference of gene networks typically relies on measurements across a wide range of conditions or treatments. Although one network structure is predicted, the relationship between genes could vary across conditions. A comprehensive approach to infer general and condition-dependent gene networks was evaluated. This approach integrated Bayesian network and Gaussian mixture models to describe continuous microarray gene expression measurements, and three gene networks were predicted.     

DISCLOSE : DISsection of CLusters Obtained by SEries of transcriptome data using functional annotations and putative transcription factor binding sites

Background  

A typical step in the analysis of gene expression data is the determination of clusters of genes that exhibit similar expression patterns. Researchers are confronted with the seemingly arbitrary choice between numerous algorithms to perform cluster analysis.     

Edge detection in microscopy images using curvelets

Background  

Despite significant progress in imaging technologies, the efficient detection of edges and elongated features in images of intracellular and multicellular structures acquired using light or electron microscopy is a challenging and time consuming task in many laboratories.     

Finding coevolving amino acid residues using row and column weighting of mutual information and multi-dimensional amino acid representation

Background  

Some amino acid residues functionally interact with each other. This interaction will result in an evolutionary co-variation between these residues – coevolution. Our goal is to find these coevolving residues.     

Detection of Helicobacter pylori in stool samples of young children using real‐time polymerase chain reaction

Background

The aims of this study were to develop and validate a multiplex real‐time polymerase chain reaction (q‐PCR) assay of Helicobacter pylori in stool samples of healthy children. Additionally, we determined the prevalence of clarithromycin resistance and cagA gene in H. pylori‐positive samples.

Materials and methods

Archived stool samples from 188 children aged 6‐9 years and 272 samples of 92 infants aged 2‐18 months were tested for H. pylori antigens using enzyme immunoassay (EIA). A multiplex q‐PCR assay was designed to detect H. pylori 16S rRNA and urease and the human RNase P gene as an internal control. Kappa coefficient was calculated to assess the agreement between q‐PCR and EIA.

Results

Laboratory validation of the q‐PCR assay using quantitated H. pylori ATCC 43504 extracted DNA showed S‐shaped amplification curves for all genes; the limit of detection was 1 CFU/reaction. No cross‐reactivity with other bacterial pathogens was noted. Applying the multiplex q‐PCR to DNA extracted from fecal samples showed clear amplification curves for urease gene, but not for 16S rRNA. The prevalence of H. pylori infection was 50% (95% CI 43%‐57%) by q‐PCR (urease cycle threshold <44) vs 59% (95% CI 52%‐66%) by EIA. Kappa coefficient was .80 (P < .001) and .44 (P < .001) for children aged 6‐9 years and 2‐18 months, respectively. Sixteen samples were positive for cagA and three were positive for clarithromycin resistance mutation (A2143G) as confirmed by sequencing.

Conclusions

The developed q‐PCR can be used as a cotechnique to enhance the accuracy of H. pylori detection in epidemiological studies and in clinical settings.     

Predicting functional associations from metabolism using bi-partite network algorithms

Background  

Metabolic reconstructions contain detailed information about metabolic enzymes and their reactants and products. These networks can be used to infer functional associations between metabolic enzymes. Many methods are based on the number of metabolites shared by two enzymes, or the shortest path between two enzymes. Metabolite sharing can miss associations between non-consecutive enzymes in a serial pathway, and shortest-path algorithms are sensitive to high-degree metabolites such as water and ATP that create connections between enzymes with little functional similarity.     

Improved protein structure selection using decoy-dependent discriminatory functions

Background  

A key component in protein structure prediction is a scoring or discriminatory function that can distinguish near-native conformations from misfolded ones. Various types of scoring functions have been developed to accomplish this goal, but their performance is not adequate to solve the structure selection problem. In addition, there is poor correlation between the scores and the accuracy of the generated conformations.     

160-fold acceleration of the Smith-Waterman algorithm using a field programmable gate array (FPGA)

Background  

To infer homology and subsequently gene function, the Smith-Waterman (SW) algorithm is used to find the optimal local alignment between two sequences. When searching sequence databases that may contain hundreds of millions of sequences, this algorithm becomes computationally expensive.     

Classification of microarray data using gene networks

Background  

Microarrays have become extremely useful for analysing genetic phenomena, but establishing a relation between microarray analysis results (typically a list of genes) and their biological significance is often difficult. Currently, the standard approach is to map a posteriori the results onto gene networks in order to elucidate the functions perturbed at the level of pathways. However, integrating a priori knowledge of the gene networks could help in the statistical analysis of gene expression data and in their biological interpretation.     

Prediction of protein binding sites in protein structures using hidden Markov support vector machine

Background  

Predicting the binding sites between two interacting proteins provides important clues to the function of a protein. Recent research on protein binding site prediction has been mainly based on widely known machine learning techniques, such as artificial neural networks, support vector machines, conditional random field, etc. However, the prediction performance is still too low to be used in practice. It is necessary to explore new algorithms, theories and features to further improve the performance.     

Single-step autoantibody profiling in antiphospholipid syndrome using a multi-line dot assay

Introduction  

Diagnosis of antiphospholipid syndrome (APS) still remains a laboratory challenge due to the great diversity of antiphospholipid antibodies (aPL) and their significance regarding APS-diagnostic criteria.     

Mistaken Identifiers: Gene name errors can be introduced inadvertently when using Excel in bioinformatics

Background  

When processing microarray data sets, we recently noticed that some gene names were being changed inadvertently to non-gene names.