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. We present siRecords, an extensive database of mammalian RNAi experiments with consistent efficacy ratings. This database serves two purposes. First, it provides a large and diverse dataset of siRNA experiments. This dataset faithfully represents the general, diverse RNAi experimental practice, and allows more reliable siRNA design tools to be developed with the overfitting problem well curbed. Second, the database helps experimental RNAi researchers directly by providing them with the efficacy and other information about the siRNAs experiments designed and conducted previously against the genes of their interest. The current release of siRecords contains the records of 17,192 RNAi experiments targeting 5086 genes.

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. We compiled four unbiased phosphorylation site datasets, each for one of the four major serine/threonine (S/T) protein kinase families-CDK, CK2, PKA and PKC. Using these datasets, we examined several meta-predicting strategies with 15 phosphorylation site predictors from six predicting programs: GPS, KinasePhos, NetPhosK, PPSP, PredPhospho and Scansite. Meta-predictors constructed with a generalized weighted voting meta-predicting strategy with parameters determined by restricted grid search possess the best performance, exceeding that of all individual predictors in predicting phosphorylation sites of all four kinase families. Our results demonstrate a useful decision-making tool for analysing the predictions of the various S/T phosphorylation site predictors. An implementation of these meta-predictors is available on the web at: http://MetaPred.umn.edu/MetaPredPS/.

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. Our motivation is to provide the research community with a rich information source emphasizing the reported, experimentally validated data for specific PPBD-PPEP interactions. This information is not only useful for designing, comparing and validating the relevant experiments, but it also serves as a knowledge-base for computationally constructing systems signaling pathways and networks. PepCyber:P approximately PEP is accessible through the URL, http://www.pepcyber.org/PPEP/. The current release of the database contains 7044 PPBD-mediated interactions involving 337 PPBD-containing proteins and 1123 substrate proteins.

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. siDRM also implements a few high-sensitivity rule sets and fast rule sets, links to siRecords, and uses several filters to check unwanted detrimental effects, including innate immune responses, cell toxic effects and off-target activities in selecting siRNAs. A performance comparison using an independent dataset indicated that siDRM outperforms 19 existing siRNA design tools in identifying effective siRNAs.

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. DESCRIPTION: The MOrpholino DataBase is a MySQL relational database with an online, PHP interface. Multiple quality control levels allow differential access to data in raw and finished formats. MODBv1 includes sequence information relating to almost 800 morpholinos and their targets and phenotypic data regarding the dose effect of each morpholino (mortality, toxicity and defects). To improve the searchability of this database, we have incorporated a fixed-vocabulary defect ontology that allows for the organization of morpholino affects based on anatomical structure affected and defect produced. This also allows comparison between species utilizing Phenotypic Attribute Trait Ontology (PATO) designated terminology. MODB is also cross-linked with ZFIN, allowing full searches between the two databases. MODB offers users the ability to retrieve morpholino data by sequence of morpholino or target, name of target, anatomical structure affected and defect produced. CONCLUSION: MODB data can be used for functional genomic analysis of morpholino design to maximize efficacy and minimize toxicity. MODB also serves as a template for future sequence-based functional genetic screen databases, and it is currently being used as a model for the creation of a mutagenic insertional transposon database.

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. RESULTS: Using a distinctly large set of siRNA efficacy data assembled from a vast diversity of origins (the siRecords data, containing records of 3,277 siRNA experiments targeting 1,518 genes, derived from 1,417 independent studies), we conducted extensive analyses of all known features that have been implicated in increasing RNAi effectiveness. A number of features having positive impacts on siRNA efficacy were identified. By performing quantitative analyses on cooperative effects among these features, then applying a disjunctive rule merging (DRM) algorithm, we developed a bundle of siRNA design rule sets with the false positive problem well curbed. A comparison with 15 online siRNA design tools indicated that some of the rule sets we developed surpassed all of these design tools commonly used in siRNA design practice in positive predictive values (PPVs). CONCLUSION: The availability of the large and diverse siRNA dataset from siRecords and the approach we describe in this report have allowed the development of highly effective and generally applicable siRNA design rule sets. Together with ever improving RNAi lab techniques, these design rule sets are expected to make siRNAs a more useful tool for molecular genetics, functional genomics, and drug discovery studies.

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. Subsequently, we have greatly extended the construction of SVRMHC models and have established such models for more than 40 class I and class II MHC molecules. Here we present the SVRMHC web server for predicting peptide-MHC binding affinities using these models. Benchmarked percentile scores are provided for all predictions. The larger number of SVRMHC models available allowed for an updated evaluation of the performance of the SVRMHC method compared to other well- known linear modeling methods. CONCLUSION: SVRMHC is an accurate and easy-to-use prediction server for epitope-MHC binding with significant coverage of MHC molecules. We believe it will prove to be a valuable resource for T cell epitope researchers.

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). Following computational sequence homology search and hairpin structure prediction, we identified three novel tomato miRNA precursor genes. Our results also show that, in accordance with the phenotype of the developing leaves, the tomato miRNAs are differentially expressed at different stages of plant development and that CMV infection can induce or suppress the expression of miRNAs as well as up-regulate some star miRNAs (miRNA*s) which are normally present at much lower levels. The results indicate that developmental anomalies elicited by virus infection may be caused by more complex biological processes.

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. Currently, more than 4100 carefully annotated siRNA sequences obtained from more than 1200 published siRNA studies are hosted in siRecords. This database will continue to expand as more experimentally tested siRNAs are published. AVAILABILITY: The siRecords database can be accessed at http://siRecords.umn.edu/siRecords/