The University of Minnesota Pathway Prediction System: multi-level prediction and visualization.

The University of Minnesota Pathway Prediction System (UM-PPS, http://umbbd.msi.umn.

The University of Minnesota Biocatalysis/Biodegradation Database: improving public access.

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.msi.umn.

Improving infrastructure for pathway prediction.

The UM-BBD Pathway Prediction System (UM-PPS, http://umbbd.msi.umn.

The University of Minnesota pathway prediction system: predicting metabolic logic.

The University of Minnesota pathway prediction system (UM-PPS, http://umbbd.msi.umn.

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.

Meta-prediction of protein subcellular localization with reduced voting.

Meta-prediction seeks to harness the combined strengths of multiple predicting programs with the hope of achieving predicting performance surpassing that of all existing predictors in a defined problem domain. We investigated meta-prediction for the four-compartment eukaryotic subcellular localization problem. We compiled an unbiased subcellular localization dataset of 1693 nuclear, cytoplasmic, mitochondrial and extracellular animal proteins from Swiss-Prot 50.

Genome-wide reverse genetics framework to identify novel functions of the vertebrate secretome.

Background: Understanding the functional role(s) of the more than 20,000 proteins of the vertebrate genome is a major next step in the post-genome era. The approximately 4,000 co-translationally translocated (CTT) proteins - representing the vertebrate secretome - are important for such vertebrate-critical processes as organogenesis. However, the role(s) for most of these genes is currently unknown.

The University of Minnesota Biocatalysis/Biodegradation Database: the first decade.

As the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.

Evaluating eukaryotic secreted protein prediction.

Background: Improvements in protein sequence annotation and an increase in the number of annotated protein databases has fueled development of an increasing number of software tools to predict secreted proteins. Six software programs capable of high throughput and employing a wide range of prediction methods, SignalP 3.0, SignalP 2.

AMOD: a morpholino oligonucleotide selection tool.

AMOD is a web-based program that aids in the functional evaluation of nucleotide sequences through sequence characterization and antisense morpholino oligonucleotide (target site) selection. Submitted sequences are analyzed by translation initiation site prediction algorithms and sequence-to-sequence comparisons; results are used to characterize sequence features required for morpholino design. Within a defined subsequence, base composition and homodimerization values are computed for all putative morpholino oligonucleotides.

Encoding microbial metabolic logic: predicting biodegradation.

Prediction of microbial metabolism is important for annotating genome sequences and for understanding the fate of chemicals in the environment. A metabolic pathway prediction system (PPS) has been developed that is freely available on the world wide web (http://umbbd.ahc.

Comparison of computational methods for identifying translation initiation sites in EST data.

Background: Expressed Sequence Tag (EST) sequences are generally single-strand, single-pass sequences, only 200-600 nucleotides long, contain errors resulting in frame shifts, and represent different parts of their parent cDNA. If the cDNAs contain translation initiation sites, they may be suitable for functional genomics studies. We have compared five methods to predict translation initiation sites in EST data: first-ATG, ESTScan, Diogenes, Netstart, and ATGpr.

Identifying secretomes in people, pufferfish and pigs.

The proteins processed by the secretory pathway (secretome) are critical players in the development of multi-cellular eukaryotic organisms but have yet to be comprehensively studied at the genomic level. In this study, we use the Target P algorithm to predict human (13-20% of proteins found in individual datasets) and Fugu (14%) secretomes based on analysis of their nearly complete proteomes. We combine internal processing with prediction software to automate secreted protein identification and overcome one of the major challenges associated with EST data: identification of the minority of clones that encode N-terminally-complete proteins.

Microbial pathway prediction: a functional group approach.

We have developed a system to predict microbial catabolism, using the University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.

The University of Minnesota Biocatalysis/Biodegradation Database: post-genomic data mining.

The University of Minnesota Biocatalysis/Biodegradation Database (UM-BBD, http://umbbd.ahc.umn.