Gene delivery into mouse retinal ganglion cells by in utero electroporation

Background  

The neural retina is a highly structured tissue of the central nervous system that is formed by seven different cell types that are arranged in layers. Despite much effort, the genetic mechanisms that underlie retinal development are still poorly understood. In recent years, large-scale genomic analyses have identified candidate genes that may play a role in retinal neurogenesis, axon guidance and other key processes during the development of the visual system. Thus, new and rapid techniques are now required to carry out high-throughput analyses of all these candidate genes in mammals. Gene delivery techniques have been described to express exogenous proteins in the retina of newborn mice but these approaches do not efficiently introduce genes into the only retinal cell type that transmits visual information to the brain, the retinal ganglion cells (RGCs).     

Parallel biocomputing

Background  

With the advent of high throughput genomics and high-resolution imaging techniques, there is a growing necessity in biology and medicine for parallel computing, and with the low cost of computing, it is now cost-effective for even small labs or individuals to build their own personal computation cluster.     

Potentials 'R'Us web-server for protein energy estimations with coarse-grained knowledge-based potentials

Background  

Knowledge-based potentials have been widely used in the last 20 years for fold recognition, protein structure prediction from amino acid sequence, ligand binding, protein design, and many other purposes. However generally these are not readily accessible online.     

Knowledge-based matrix factorization temporally resolves the cellular responses to IL-6 stimulation

Background  

External stimulations of cells by hormones, cytokines or growth factors activate signal transduction pathways that subsequently induce a re-arrangement of cellular gene expression. The analysis of such changes is complicated, as they consist of multi-layered temporal responses. While classical analyses based on clustering or gene set enrichment only partly reveal this information, matrix factorization techniques are well suited for a detailed temporal analysis. In signal processing, factorization techniques incorporating data properties like spatial and temporal correlation structure have shown to be robust and computationally efficient. However, such correlation-based methods have so far not be applied in bioinformatics, because large scale biological data rarely imply a natural order that allows the definition of a delayed correlation function.     

A statistical framework for differential network analysis from microarray data

Background  

It has been long well known that genes do not act alone; rather groups of genes act in consort during a biological process. Consequently, the expression levels of genes are dependent on each other. Experimental techniques to detect such interacting pairs of genes have been in place for quite some time. With the advent of microarray technology, newer computational techniques to detect such interaction or association between gene expressions are being proposed which lead to an association network. While most microarray analyses look for genes that are differentially expressed, it is of potentially greater significance to identify how entire association network structures change between two or more biological settings, say normal versus diseased cell types.     

Detecting purely epistatic multi-locus interactions by an omnibus permutation test on ensembles of two-locus analyses

Background  

Purely epistatic multi-locus interactions cannot generally be detected via single-locus analysis in case-control studies of complex diseases. Recently, many two-locus and multi-locus analysis techniques have been shown to be promising for the epistasis detection. However, exhaustive multi-locus analysis requires prohibitively large computational efforts when problems involve large-scale or genome-wide data. Furthermore, there is no explicit proof that a combination of multiple two-locus analyses can lead to the correct identification of multi-locus interactions.     

Hormonal induction of spawning in 4 species of frogs by coinjection with a gonadotropin-releasing hormone agonist and a dopamine antagonist

Background  

It is well known that many anurans do not reproduce easily in captivity. Some methods are based on administration of mammalian hormones such as human chorionic gonadotropin, which are not effective in many frogs. There is a need for simple, cost-effective alternative techniques to induce spawning.     

CoSMoS: Conserved Sequence Motif Search in the proteome

Background  

With the ever-increasing number of gene sequences in the public databases, generating and analyzing multiple sequence alignments becomes increasingly time consuming. Nevertheless it is a task performed on a regular basis by researchers in many labs.     

Large scale sex typing of ostriches using DNA extracted from feathers

Background  

Ostrich (Struthio camelus) breeds have been gaining increasing significance around the world. The large-scale sex determination of chicks is an important task in the development of these breeds. To date, two PCR-based methods have been established for ostrich sex typing, neither of them intended for large-scale analyses. Here, we report on a protocol adapted to carry out large-scale gender scoring using DNA obtained from chick feathers.     

Opportunities and challenges for digital morphology

Abstract  

Advances in digital data acquisition, analysis, and storage have revolutionized the work in many biological disciplines such as genomics, molecular phylogenetics, and structural biology, but have not yet found satisfactory acceptance in morphology. Improvements in non-invasive imaging and three-dimensional visualization techniques, however, permit high-throughput analyses also of whole biological specimens, including museum material. These developments pave the way towards a digital era in morphology. Using sea urchins (Echinodermata: Echinoidea), we provide examples illustrating the power of these techniques. However, remote visualization, the creation of a specialized database, and the implementation of standardized, world-wide accepted data deposition practices prior to publication are essential to cope with the foreseeable exponential increase in digital morphological data.     

<Emphasis Type="Italic">SplitTester</Emphasis> : software to identify domains responsible for functional divergence in protein family

Background  

Many protein families have undergone functional divergence after gene duplications such that current subgroups of the family carry out overlapping but distinct biological roles. For the protein families with known functional subtypes (a functional split), we developed the software, SplitTester, to identify potential regions that are responsible for the observed distinct functional subtypes within the same protein family.     

Dendroscope: An interactive viewer for large phylogenetic trees

Background  

Research in evolution requires software for visualizing and editing phylogenetic trees, for increasingly very large datasets, such as arise in expression analysis or metagenomics, for example. It would be desirable to have a program that provides these services in an effcient and user-friendly way, and that can be easily installed and run on all major operating systems. Although a large number of tree visualization tools are freely available, some as a part of more comprehensive analysis packages, all have drawbacks in one or more domains. They either lack some of the standard tree visualization techniques or basic graphics and editing features, or they are restricted to small trees containing only tens of thousands of taxa. Moreover, many programs are diffcult to install or are not available for all common operating systems.     

PathMAPA: a tool for displaying gene expression and performing statistical tests on metabolic pathways at multiple levels for <Emphasis Type="Italic">Arabidopsis</Emphasis>

Background  

To date, many genomic and pathway-related tools and databases have been developed to analyze microarray data. In published web-based applications to date, however, complex pathways have been displayed with static image files that may not be up-to-date or are time-consuming to rebuild. In addition, gene expression analyses focus on individual probes and genes with little or no consideration of pathways. These approaches reveal little information about pathways that are key to a full understanding of the building blocks of biological systems. Therefore, there is a need to provide useful tools that can generate pathways without manually building images and allow gene expression data to be integrated and analyzed at pathway levels for such experimental organisms as Arabidopsis.     

Evaluation of normalization methods for cDNA microarray data by <Emphasis Type="Italic">k</Emphasis>-NN classification

Background  

Non-biological factors give rise to unwanted variations in cDNA microarray data. There are many normalization methods designed to remove such variations. However, to date there have been few published systematic evaluations of these techniques for removing variations arising from dye biases in the context of downstream, higher-order analytical tasks such as classification.     

Automating dChip: toward reproducible sharing of microarray data analysis

Background  

During the past decade, many software packages have been developed for analysis and visualization of various types of microarrays. We have developed and maintained the widely used dChip as a microarray analysis software package accessible to both biologist and data analysts. However, challenges arise when dChip users want to analyze large number of arrays automatically and share data analysis procedures and parameters. Improvement is also needed when the dChip user support team tries to identify the causes of reported analysis errors or bugs from users.     

UniFrac – An online tool for comparing microbial community diversity in a phylogenetic context

Background  

Moving beyond pairwise significance tests to compare many microbial communities simultaneously is critical for understanding large-scale trends in microbial ecology and community assembly. Techniques that allow microbial communities to be compared in a phylogenetic context are rapidly gaining acceptance, but the widespread application of these techniques has been hindered by the difficulty of performing the analyses.