Cranial bone morphometric study among mouse strains

Background  

Little is known about the molecular mechanism which regulates how the whole cranium is shaped. Mouse models currently available for genetic research include several hundreds of unique inbred strains and genetically engineered mutants.     

Algorithms for locating extremely conserved elements in multiple sequence alignments

Background  

In 2004, Bejerano et al. announced the startling discovery of hundreds of "ultraconserved elements", long genomic sequences perfectly conserved across human, mouse, and rat. Their announcement stimulated a flurry of subsequent research.     

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.     

GCOD - GeneChip Oncology Database

Background  

DNA microarrays have become a nearly ubiquitous tool for the study of human disease, and nowhere is this more true than in cancer. With hundreds of studies and thousands of expression profiles representing the majority of human cancers completed and in public databases, the challenge has been effectively accessing and using this wealth of data.     

On the phylogenetic position of Myzostomida: can 77 genes get it wrong?

Background  

Phylogenomic analyses recently became popular to address questions about deep metazoan phylogeny. Ribosomal proteins (RP) dominate many of these analyses or are, in some cases, the only genes included. Despite initial hopes, phylogenomic analyses including tens to hundreds of genes still fail to robustly place many bilaterian taxa.     

SAQC: SNP Array Quality Control

Background  

Genome-wide single-nucleotide polymorphism (SNP) arrays containing hundreds of thousands of SNPs from the human genome have proven useful for studying important human genome questions. Data quality of SNP arrays plays a key role in the accuracy and precision of downstream data analyses. However, good indices for assessing data quality of SNP arrays have not yet been developed.     

Duplicate gene evolution and expression in the wake of vertebrate allopolyploidization

Background  

The mechanism by which duplicate genes originate – whether by duplication of a whole genome or of a genomic segment – influences their genetic fates. To study events that trigger duplicate gene persistence after whole genome duplication in vertebrates, we have analyzed molecular evolution and expression of hundreds of persistent duplicate gene pairs in allopolyploid clawed frogs (Xenopus and Silurana). We collected comparative data that allowed us to tease apart the molecular events that occurred soon after duplication from those that occurred later on. We also quantified expression profile divergence of hundreds of paralogs during development and in different tissues.     

The curvHDR method for gating flow cytometry samples

Background  

High-throughput flow cytometry experiments produce hundreds of large multivariate samples of cellular characteristics. These samples require specialized processing to obtain clinically meaningful measurements. A major component of this processing is a form of cell subsetting known as gating. Manual gating is time-consuming and subjective. Good automatic and semi-automatic gating algorithms are very beneficial to high-throughput flow cytometry.     

MASQOT: a method for cDNA microarray spot quality control

Background  

cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more.     

QTLminer: identifying genes regulating quantitative traits

Background  

Quantitative trait locus (QTL) mapping identifies genomic regions that likely contain genes regulating a quantitative trait. However, QTL regions may encompass tens to hundreds of genes. To find the most promising candidate genes that regulate the trait, the biologist typically collects information from multiple resources about the genes in the QTL interval. This process is very laborious and time consuming.     

Speeding disease gene discovery by sequence based candidate prioritization

Background  

Regions of interest identified through genetic linkage studies regularly exceed 30 centimorgans in size and can contain hundreds of genes. Traditionally this number is reduced by matching functional annotation to knowledge of the disease or phenotype in question. However, here we show that disease genes share patterns of sequence-based features that can provide a good basis for automatic prioritization of candidates by machine learning.     

Semi-automatic identification of punching areas for tissue microarray building: the tubular breast cancer pilot study

Background  

Tissue MicroArray technology aims to perform immunohistochemical staining on hundreds of different tissue samples simultaneously. It allows faster analysis, considerably reducing costs incurred in staining. A time consuming phase of the methodology is the selection of tissue areas within paraffin blocks: no utilities have been developed for the identification of areas to be punched from the donor block and assembled in the recipient block.     

A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis

Background  

Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query sequence based on the statistical genotype models learned from the known sequences. Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment.     

Cross-study analysis of genomic data defines the ciliate multigenic epiplasmin family: strategies for functional analysis in Paramecium tetraurelia

Background  

The sub-membranous skeleton of the ciliate Paramecium, the epiplasm, is composed of hundreds of epiplasmic scales centered on basal bodies, and presents a complex set of proteins, epiplasmins, which belong to a multigenic family. The repeated duplications observed in the P. tetraurelia genome present an interesting model of the organization and evolution of a multigenic family within a single cell.     

Biclustering of gene expression data by non-smooth non-negative matrix factorization

Background  

The extended use of microarray technologies has enabled the generation and accumulation of gene expression datasets that contain expression levels of thousands of genes across tens or hundreds of different experimental conditions. One of the major challenges in the analysis of such datasets is to discover local structures composed by sets of genes that show coherent expression patterns across subsets of experimental conditions. These patterns may provide clues about the main biological processes associated to different physiological states.     

Oocyte production and sperm utilization patterns in semi-fertile strains of <Emphasis Type="Italic">Caenorhabditis elegans</Emphasis>

Background  

Caenorhabditis elegans hermaphrodites are capable of producing hundreds of progeny. However, genetic and environmental factors can keep many animals from attaining their full reproductive potential. In these situations, efficient use of any functional gametes becomes more important for reproductive success. To learn about this aspect of C. elegans reproductive biology, we examined oocyte production and sperm utilization patterns in a unique collection of semi-fertile sperm function mutants.     

Thin films of Type 1 collagen for cell by cell analysis of morphology and tenascin-C promoter activity

Background  

The use of highly reproducible and spatiallyhomogeneous thin film matrices permits automated microscopy and quantitative determination of the response of hundreds of cells in a population. Using thin films of extracellular matrix proteins, we have quantified, on a cell-by-cell basis, phenotypic parameters of cells on different extracellular matrices. We have quantitatively examined the relationship between fibroblast morphology and activation of the promoter for the extracellular matrix protein tenascin-C using a tenascin-C promoter-based GFP reporter construct.     

Evaluating diabetes and hypertension disease causality using mouse phenotypes

Background  

Genome-wide association studies (GWAS) have found hundreds of single nucleotide polymorphisms (SNPs) associated with common diseases. However, it is largely unknown what genes linked with the SNPs actually implicate disease causality. A definitive proof for disease causality can be demonstration of disease-like phenotypes through genetic perturbation of the genes or alleles, which is obviously a daunting task for complex diseases where only mammalian models can be used.     

Highly sensitive feature detection for high resolution LC/MS

Background  

Liquid chromatography coupled to mass spectrometry (LC/MS) is an important analytical technology for e.g. metabolomics experiments. Determining the boundaries, centres and intensities of the two-dimensional signals in the LC/MS raw data is called feature detection. For the subsequent analysis of complex samples such as plant extracts, which may contain hundreds of compounds, corresponding to thousands of features – a reliable feature detection is mandatory.