An integrated approach to the prediction of domain-domain interactions

Background  

The development of high-throughput technologies has produced several large scale protein interaction data sets for multiple species, and significant efforts have been made to analyze the data sets in order to understand protein activities. Considering that the basic units of protein interactions are domain interactions, it is crucial to understand protein interactions at the level of the domains. The availability of many diverse biological data sets provides an opportunity to discover the underlying domain interactions within protein interactions through an integration of these biological data sets.     

M-GCAT: interactively and efficiently constructing large-scale multiple genome comparison frameworks in closely related species

Background  

Due to recent advances in whole genome shotgun sequencing and assembly technologies, the financial cost of decoding an organism's DNA has been drastically reduced, resulting in a recent explosion of genomic sequencing projects. This increase in related genomic data will allow for in depth studies of evolution in closely related species through multiple whole genome comparisons.     

MegaSNPHunter: a learning approach to detect disease predisposition SNPs and high level interactions in genome wide association study

Background  

The interactions of multiple single nucleotide polymorphisms (SNPs) are highly hypothesized to affect an individual's susceptibility to complex diseases. Although many works have been done to identify and quantify the importance of multi-SNP interactions, few of them could handle the genome wide data due to the combinatorial explosive search space and the difficulty to statistically evaluate the high-order interactions given limited samples.     

Nonparametric tests for differential gene expression and interaction effects in multi-factorial microarray experiments

Background  

Numerous nonparametric approaches have been proposed in literature to detect differential gene expression in the setting of two user-defined groups. However, there is a lack of nonparametric procedures to analyze microarray data with multiple factors attributing to the gene expression. Furthermore, incorporating interaction effects in the analysis of microarray data has long been of great interest to biological scientists, little of which has been investigated in the nonparametric framework.     

A general and efficient method for estimating continuous IBD functions for use in genome scans for QTL

Background  

Identity by descent (IBD) matrix estimation is a central component in mapping of Quantitative Trait Loci (QTL) using variance component models. A large number of algorithms have been developed for estimation of IBD between individuals in populations at discrete locations in the genome for use in genome scans to detect QTL affecting various traits of interest in experimental animal, human and agricultural pedigrees. Here, we propose a new approach to estimate IBD as continuous functions rather than as discrete values.     

PeanutMap: an online genome database for comparative molecular maps of peanut

Background  

Molecular maps have been developed for many species, and are of particular importance for varietal development and comparative genomics. However, despite the existence of multiple sets of linkage maps, databases of these data are lacking for many species, including peanut.     

A Simple Sign for Recognizing Off–Axis OCT Measurement Beam Placement in the Context of Multicentre Studies

Purpose

Optical coherence tomography (OCT) allows quantification of the thickness of the retinal nerve fibre layer (RNFL) thickness, a potential biomarker for neurodegeneration. The estimated annual RNFL loss in multiple sclerosis amounts to 2 μm using time domain OCT. The recognition of measurement artifacts exceeding this limit is relevant for the successful use of OCT as a secondary outcome measure in clinical trials.

Methods

Prospective study design. An exploratory pilot study (ring and volume scans) followed by a cohort study (1,980 OCT ring scans). The OCT measurement beam was placed off–axis to the left, right, top and bottom of the subjects pupil and RNFL thickness of these scans were compared to the centrally placed reference scans.

Results

Off–axis placement of the OCT measurement beam resulted in significant artifacts in RNFL thickness measurements (95%CI 9μm, maximal size of error 42μm). Off–axis placement gave characteristic patterns of the OCT live images which are not necessarily saved for review. Off–axis placement also causes regional inhomogeneity of reflectivity in the outer nuclear (ONL) and outer plexiform layers (OPL) which remains visible on scans saved for review.

Conclusion

Off–axis beam placement introduces measurement artifacts at a magnitude which may mask recognition of RNFL loss due to neurodegeneration in multiple sclerosis. The resulting pattern in the OCT live image can only be recognised by the technician capturing the scans. Once the averaged scans have been aligned this pattern is lost. Retrospective identification of this artifact is however possible by presence of regional inhomogeneity of ONL/OPL reflectivity. This simple and robust sign may be considered for quality control criteria in the setting of multicentre OCT studies. The practical advice of this study is to keep the OCT image in the acquisition window horizontally aligned whenever possible.     

Comparison of 3T MR scanners in regional cartilage-thickness analysis in osteoarthritis: a cross-sectional multicenter,multivendor study

Introduction  

Cartilage thickness from MR images has been identified as a possible biomarker in knee osteoarthritis (OA) research. The ability to acquire MR data at multiple centers by using different vendors' scanners would facilitate patient recruitment and shorten the duration of OA trials. Several vendors manufacture 3T MR scanners, including Siemens, Philips Medical Systems, and GE Healthcare. This study investigates whether quantitative MR assessments of cartilage morphology are comparable between scanners of three different vendors.     

AnovArray: a set of SAS macros for the analysis of variance of gene expression data

Background  

Analysis of variance is a powerful approach to identify differentially expressed genes in a complex experimental design for microarray and macroarray data. The advantage of the anova model is the possibility to evaluate multiple sources of variation in an experiment.     

<Emphasis Type="Italic">ClustalXeed</Emphasis>: a GUI-based grid computation version for high performance and terabyte size multiple sequence alignment

Background  

There is an increasing demand to assemble and align large-scale biological sequence data sets. The commonly used multiple sequence alignment programs are still limited in their ability to handle very large amounts of sequences because the system lacks a scalable high-performance computing (HPC) environment with a greatly extended data storage capacity.     

Rank-invariant resampling based estimation of false discovery rate for analysis of small sample microarray data

Background  

The evaluation of statistical significance has become a critical process in identifying differentially expressed genes in microarray studies. Classical p-value adjustment methods for multiple comparisons such as family-wise error rate (FWER) have been found to be too conservative in analyzing large-screening microarray data, and the False Discovery Rate (FDR), the expected proportion of false positives among all positives, has been recently suggested as an alternative for controlling false positives. Several statistical approaches have been used to estimate and control FDR, but these may not provide reliable FDR estimation when applied to microarray data sets with a small number of replicates.     

Dispensed drugs and multiple medications in the Swedish population: an individual-based register study

Background  

Multiple medications is a well-known potential risk factor in terms of patient's health. The aim of the present study was to estimate the prevalence of dispensed drugs and multiple medications in an entire national population, by using individual based data on dispensed drugs.     

FunSpec: a web-based cluster interpreter for yeast

Background  

For effective exposition of biological information, especially with regard to analysis of large-scale data types, researchers need immediate access to multiple categorical knowledge bases and need summary information presented to them on collections of genes, as opposed to the typical one gene at a time.     

FDG PET scans as evaluation of clinical response to dendritic cell vaccination in patients with malignant melanoma

Background

Measurements of tumour metabolism by [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) have been successfully applied to monitor tumour response after chemo- and chemo-radiotherapy and may not have the same limitations as other morphological imaging techniques. In this study it is investigated whether FDG-PET might add information on the efficacy of immune therapy.

Materials and methods

In a retrospective analysis data from patients with advanced progressive melanoma, treated with DC vaccinations and evaluated by PET/CT scans at baseline as well as after 6 vaccinations were analysed. If a patient achieved stable disease according to RECIST, additional vaccinations were given. The PET scans were evaluated according to EORTC guidelines.

Results

PET/CT scans from 13 patients were evaluated. According to RECIST 3 patients achieved stable disease and 10 patients progressed. Interestingly, when evaluated by PET scans 2 patients had partial metabolic response and 1 patient had complete metabolic response of the 2 index lesions even though a new lesion appeared simultaneously. Ten patients were seen to have stable or progressive metabolic disease.

Conclusion

By adding PET scans to the CT evaluation of patients treated with DC vaccines, a more detailed picture of the single lesions was found. This seems to improve the clinical evaluation of the treatment. The lack of correlation between the PET and CT scans suggests that some of the increases in target lesions seen in CT scans might be due to oedema or immune-infiltrates and not progression of the disease. Thus, further investigation into the contribution of PET scans to the evaluation of cancer immunotherapy is needed.     

The Firegoose: two-way integration of diverse data from different bioinformatics web resources with desktop applications

Background  

Information resources on the World Wide Web play an indispensable role in modern biology. But integrating data from multiple sources is often encumbered by the need to reformat data files, convert between naming systems, or perform ongoing maintenance of local copies of public databases. Opportunities for new ways of combining and re-using data are arising as a result of the increasing use of web protocols to transmit structured data.     

An improved ontological representation of dendritic cells as a paradigm for all cell types

Background  

Recent increases in the volume and diversity of life science data and information and an increasing emphasis on data sharing and interoperability have resulted in the creation of a large number of biological ontologies, including the Cell Ontology (CL), designed to provide a standardized representation of cell types for data annotation. Ontologies have been shown to have significant benefits for computational analyses of large data sets and for automated reasoning applications, leading to organized attempts to improve the structure and formal rigor of ontologies to better support computation. Currently, the CL employs multiple is_a relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL's utility for computation and for cross-species data integration.     

Filtering,FDR and power

Background  

In high-dimensional data analysis such as differential gene expression analysis, people often use filtering methods like fold-change or variance filters in an attempt to reduce the multiple testing penalty and improve power. However, filtering may introduce a bias on the multiple testing correction. The precise amount of bias depends on many quantities, such as fraction of probes filtered out, filter statistic and test statistic used.     

Kalign – an accurate and fast multiple sequence alignment algorithm

Background  

The alignment of multiple protein sequences is a fundamental step in the analysis of biological data. It has traditionally been applied to analyzing protein families for conserved motifs, phylogeny, structural properties, and to improve sensitivity in homology searching. The availability of complete genome sequences has increased the demands on multiple sequence alignment (MSA) programs. Current MSA methods suffer from being either too inaccurate or too computationally expensive to be applied effectively in large-scale comparative genomics.