Microarray-based identification of tomato microRNAs and time course analysis of their response to Cucumber mosaic virus infection.

A large number of plant microRNAs (miRNAs) are now documented in the miRBase, among which only 30 are for Solanum lycopersicum (tomato). Clearly, there is a far-reaching need to identify and profile the expression of miRNAs in this important crop under various physiological and pathological conditions. In this study, we used an in situ synthesized custom microarray of plant miRNAs to examine the expression and temporal presence of miRNAs in the leaves of tomato plants infected with Cucumber mosaic virus (CMV).

siRecords: a database of mammalian RNAi experiments and efficacies.

RNAi-based gene-silencing techniques offer a fast and cost-effective way of knocking down genes' functions in an easily regulated manner. Exciting progress has been made in recent years in the application of these techniques in basic biomedical research and therapeutic development. However, it remains a difficult task to design effective siRNA experiments with high efficacy and specificity.

siDRM: an effective and generally applicable online siRNA design tool.

Small interfering RNAs (siRNAs) have become an indispensable tool for the investigation of gene functions. Most existing siRNA design tools were trained on datasets assembled from confined origins, incompatible with the diverse siRNA laboratory practice to which these tools will ultimately be applied. We have performed an updated analysis using the disjunctive rule merging (DRM) approach on a large and diverse dataset compiled from siRecords, and implemented the resulting rule sets in siDRM, a new online siRNA design tool.

Meta-prediction of phosphorylation sites with weighted voting and restricted grid search parameter selection.

Meta-predictors make predictions by organizing and processing the predictions produced by several other predictors in a defined problem domain. A proficient meta-predictor not only offers better predicting performance than the individual predictors from which it is constructed, but it also relieves experimentally researchers from making difficult judgments when faced with conflicting results made by multiple prediction programs. As increasing numbers of predicting programs are being developed in a large number of fields of life sciences, there is an urgent need for effective meta-prediction strategies to be investigated.

A PATO-compliant zebrafish screening database (MODB): management of morpholino knockdown screen information.

Background: The zebrafish is a powerful model vertebrate amenable to high throughput in vivo genetic analyses. Examples include reverse genetic screens using morpholino knockdown, expression-based screening using enhancer trapping and forward genetic screening using transposon insertional mutagenesis. We have created a database to facilitate web-based distribution of data from such genetic studies.

PepCyber:P~PEP: a database of human protein protein interactions mediated by phosphoprotein-binding domains.

Phosphoprotein-binding domains (PPBDs) mediate many important cellular and molecular processes. Ten PPBDs have been known to exist in the human proteome, namely, 14-3-3, BRCT, C2, FHA, MH2, PBD, PTB, SH2, WD-40 and WW. PepCyber:P approximately PEP is a newly constructed database specialized in documenting human PPBD-containing proteins and PPBD-mediated interactions.

Integrated siRNA design based on surveying of features associated with high RNAi effectiveness.

Background: Short interfering RNAs have allowed the development of clean and easily regulated methods for disruption of gene expression. However, while these methods continue to grow in popularity, designing effective siRNA experiments can be challenging. The various existing siRNA design guidelines suffer from two problems: they differ considerably from each other, and they produce high levels of false-positive predictions when tested on data of independent origins.

SVRMHC prediction server for MHC-binding peptides.

Background: The binding between antigenic peptides (epitopes) and the MHC molecule is a key step in the cellular immune response. Accurate in silico prediction of epitope-MHC binding affinity can greatly expedite epitope screening by reducing costs and experimental effort.

Results: Recently, we demonstrated the appealing performance of SVRMHC, an SVR-based quantitative modeling method for peptide-MHC interactions, when applied to three mouse class I MHC molecules.

siRecords: an extensive database of mammalian siRNAs with efficacy ratings.

Unlabelled: Short interfering RNAs (siRNAs) have been gaining popularity as the gene knock-down tool of choice by many researchers because of the clean nature of their workings as well as the technical simplicity and cost efficiency in their applications. We have constructed siRecords, a database of siRNAs experimentally tested by researchers with consistent efficacy ratings. This database will help siRNA researchers develop more reliable siRNA design rules; in the mean time, siRecords will benefit experimental researchers directly by providing them with information about the siRNAs that have been experimentally tested against the genes of their interest.