TableButler – a Windows based tool for processing large data tables generated with high-throughput methods

Background  

High-throughput "omics" based data analysis play emerging roles in life sciences and molecular diagnostics. This emphasizes the urgent need for user-friendly windows-based software interfaces that could process the diversity of large tab-delimited raw data files generated by these methods. Depending on the study, dozens to hundreds of these data tables are generated. Before the actual statistical or cluster analysis, these data tables have to be combined and merged to expression matrices (e.g., in case of gene expression analysis). Gene annotations as well as information concerning the samples analyzed may be appended, renewed or extended. Often additional data values shall be computed or certain features must be filtered out.     

Boolean networks using the chi-square test for inferring large-scale gene regulatory networks

Background  

Boolean network (BN) modeling is a commonly used method for constructing gene regulatory networks from time series microarray data. However, its major drawback is that its computation time is very high or often impractical to construct large-scale gene networks. We propose a variable selection method that are not only reduces BN computation times significantly but also obtains optimal network constructions by using chi-square statistics for testing the independence in contingency tables.     

A web services choreography scenario for interoperating bioinformatics applications

Background  

Very often genome-wide data analysis requires the interoperation of multiple databases and analytic tools. A large number of genome databases and bioinformatics applications are available through the web, but it is difficult to automate interoperation because: 1) the platforms on which the applications run are heterogeneous, 2) their web interface is not machine-friendly, 3) they use a non-standard format for data input and output, 4) they do not exploit standards to define application interface and message exchange, and 5) existing protocols for remote messaging are often not firewall-friendly. To overcome these issues, web services have emerged as a standard XML-based model for message exchange between heterogeneous applications. Web services engines have been developed to manage the configuration and execution of a web services workflow.     

Prediction of amphipathic in-plane membrane anchors in monotopic proteins using a SVM classifier

Background  

Membrane proteins are estimated to represent about 25% of open reading frames in fully sequenced genomes. However, the experimental study of proteins remains difficult. Considerable efforts have thus been made to develop prediction methods. Most of these were conceived to detect transmembrane helices in polytopic proteins. Alternatively, a membrane protein can be monotopic and anchored via an amphipathic helix inserted in a parallel way to the membrane interface, so-called in-plane membrane (IPM) anchors. This type of membrane anchor is still poorly understood and no suitable prediction method is currently available.     

High-throughput screening of cellulase F mutants from multiplexed plasmid sets using an automated plate assay on a functional proteomic robotic workcell

Background  

The field of plasmid-based functional proteomics requires the rapid assay of proteins expressed from plasmid libraries. Automation is essential since large sets of mutant open reading frames are being cloned for evaluation. To date no integrated automated platform is available to carry out the entire process including production of plasmid libraries, expression of cloned genes, and functional testing of expressed proteins.     

GeneKeyDB: A lightweight,gene-centric,relational database to support data mining environments

Background  

The analysis of biological data is greatly enhanced by existing or emerging databases. Most existing databases, with few exceptions are not designed to easily support large scale computational analysis, but rather offer exclusively a web interface to the resource. We have recognized the growing need for a database which can be used successfully as a backend to computational analysis tools and pipelines. Such database should be sufficiently versatile to allow easy system integration.     

Quilt Plots: A Simple Tool for the Visualisation of Large Epidemiological Data

Background

Graphical representation of data is one of the most easily comprehended forms of explanation. The current study describes a simple visualization tool which may allow greater understanding of medical and epidemiological data.

Method

We propose a simple tool for visualization of data, known as a “quilt plot”, that provides an alternative to presenting large volumes of data as frequency tables. Data from the Australian Needle and Syringe Program survey are used to illustrate “quilt plots”.

Conclusion

Visualization of large volumes of data using “quilt plots” enhances interpretation of medical and epidemiological data. Such intuitive presentations are particularly useful for the rapid assessment of problems in the data which cannot be readily identified by manual review. We recommend that, where possible, “quilt plots” be used along with traditional quantitative assessments of the data as an explanatory data analysis tool.     

Exploiting structural and topological information to improve prediction of RNA-protein binding sites

Background  

RNA-protein interactions are important for a wide range of biological processes. Current computational methods to predict interacting residues in RNA-protein interfaces predominately rely on sequence data. It is, however, known that interface residue propensity is closely correlated with structural properties. In this paper we systematically study information obtained from sequences and structures and compare their contributions in this prediction problem. Particularly, different geometrical and network topological properties of protein structures are evaluated to improve interface residue prediction accuracy.     

ORFer – retrieval of protein sequences and open reading frames from GenBank and storage into relational databases or text files

Background  

Functional genomics involves the parallel experimentation with large sets of proteins. This requires management of large sets of open reading frames as a prerequisite of the cloning and recombinant expression of these proteins.     

Predicting functional upstream open reading frames in Saccharomyces cerevisiae

Background  

Some upstream open reading frames (uORFs) regulate gene expression (i.e., they are functional) and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not yet fully understood. In order to get a complete view of how uORFs are involved in gene regulation, it is expected that a large number of experimentally verified functional uORFs are needed. Unfortunately, wet-experiments to verify that uORFs are functional are expensive.     

Indirect two-sided relative ranking: a robust similarity measure for gene expression data

Background  

There is a large amount of gene expression data that exists in the public domain. This data has been generated under a variety of experimental conditions. Unfortunately, these experimental variations have generally prevented researchers from accurately comparing and combining this wealth of data, which still hides many novel insights.     

Generating samples for association studies based on HapMap data

Background  

With the completion of the HapMap project, a variety of computational algorithms and tools have been proposed for haplotype inference, tag SNP selection and genome-wide association studies. Simulated data are commonly used in evaluating these new developed approaches. In addition to simulations based on population models, empirical data generated by perturbing real data, has also been used because it may inherit specific properties from real data. However, there is no tool that is publicly available to generate large scale simulated variation data by taking into account knowledge from the HapMap project.     

The bovine QTL viewer: a web accessible database of bovine Quantitative Trait Loci

Background  

Many important agricultural traits such as weight gain, milk fat content and intramuscular fat (marbling) in cattle are quantitative traits. Most of the information on these traits has not previously been integrated into a genomic context. Without such integration application of these data to agricultural enterprises will remain slow and inefficient. Our goal was to populate a genomic database with data mined from the bovine quantitative trait literature and to make these data available in a genomic context to researchers via a user friendly query interface.     

FORG3D: Force-directed 3D graph editor for visualization of integrated genome scale data

Background  

Genomics research produces vast amounts of experimental data that needs to be integrated in order to understand, model, and interpret the underlying biological phenomena. Interpreting these large and complex data sets is challenging and different visualization methods are needed to help produce knowledge from the data.     

Evaluation of microarray data normalization procedures using spike-in experiments

Background  

Recently, a large number of methods for the analysis of microarray data have been proposed but there are few comparisons of their relative performances. By using so-called spike-in experiments, it is possible to characterize the analyzed data and thereby enable comparisons of different analysis methods.     

Systems analysis of endothelial cell plasma membrane proteome of rat lung microvasculature

Background  

Endothelial cells line all blood vessels to form the blood-tissue interface which is critical for maintaining organ homeostasis and facilitates molecular exchange. We recently used tissue subcellular fractionation combined with several multi-dimensional mass spectrometry-based techniques to enhance identification of lipid-embedded proteins for large-scale proteomic mapping of luminal endothelial cell plasma membranes isolated directly from rat lungs in vivo. The biological processes and functions of the proteins expressed at this important blood-tissue interface remain unexplored at a large scale.     

Amplifier spurious input current components in electrode-electrolyte interface impedance measurements

Background  

In Impedance Microbiology, the time during which the measuring equipment is connected to the bipolar cells is rather long, usually between 6 to 24 hrs for microorganisms with duplication times in the order of less than one hour and concentrations ranging from 10¹ to 10⁷ [CFU/ml]. Under these conditions, the electrode-electrolyte interface impedance may show a slow drift of about 2%/hr. By and large, growth curves superimposed on such drift do not stabilize, are less reproducible, and keep on distorting all over the measurement of the temporal reactive or resistive records due to interface changes, in turn originated in bacterial activity. This problem has been found when growth curves were obtained by means of impedance analyzers or with impedance bridges using different types of operational amplifiers.     

PCA2GO: a new multivariate statistics based method to identify highly expressed GO-Terms

Background  

Several tools have been developed to explore and search Gene Ontology (GO) databases allowing efficient GO enrichment analysis and GO tree visualization. Nevertheless, identification of highly specific GO-terms in complex data sets is relatively complicated and the display of GO term assignments and GO enrichment analysis by simple tables or pie charts is not optimal. Valuable information such as the hierarchical position of a single GO term within the GO tree (topological ordering), or enrichment within a complex set of biological experiments is not displayed. Pie charts based on GO tree levels are, themselves, one-dimensional graphs, which cannot properly or efficiently represent the hierarchical specificity for the biological system being studied.     

ProfNet,a method to derive profile-profile alignment scoring functions that improves the alignments of distantly related proteins

Background  

Profile-profile methods have been used for some years now to detect and align homologous proteins. The best such methods use information from the background distribution of amino acids and substitution tables either when constructing the profiles or in the scoring. This makes the methods dependent on the quality and choice of substitution table as well as the construction of the profiles.