Bioinformatics Lab UofL

Software and Downloads

Below is a sampling of some of the ongoing bioinformatics research projects at the University of Louisville available as either downloads or web servers.

BIOINFORMATICS SOTWARE
categoryCompare

CategoryCompare: High-throughput data meta-analysis using gene annotations

CATEGORYCOMPARE is a methodology for cross-platform and cross-sample comparison of high-throughput data at the annotation level (such as GO ontologies; KEGG pathways; and gene sets (GSEA)). This approach allows for the comparison of datasets from heterogeneous platforms. CategoryCompare provides a powerful visualization utilizing Cytoscape that allows for users to quickly view the shared features between annotations. CategoryCompare is available as an R bioconductor package. A web version of categoryCompare is currently under construction which employs cytoscape.js.
Flight RM, Harrison BJ, Mohammad F, Bunge MB, Moon LDF, Petruska JC, Rouchka EC: categoryCompare, an analytical tool based on feature annotations. Frontiers in Genetics 2014, 5:98. doi: 10.3389/fgene.2014.00098

Available as R bioconductor package

absolute ID convert

AbsIDConvert: Absolute gene ID conversion tool

With the availability of gene and protein centric databases (NCBI, Ensembl, UCSC, and others), as well as the wide variety of available platforms for measuring gene expression (Affymetrix, Agilent, custom arrays, and RNA-Seq), biological researchers need reliable methods for converting various identifiers from one type to another. AbsIDConvert is based on the unique idea that genomic identifiers can be converted to genomic intervals, and therefore conversion between identifiers requires simply finding overlapping intervals.
Mohammad F, Flight RM, Harrison BJ, Petruska JC, Rouchka EC: AbsIDconvert: An absolute approach for converting genetic identifiers at different granularities. BMC Bioinformatics 2012, 13:229. doi:10.1186/1471-2105-13-229.

Available as web interface and virtual machine

MPrime

Multiple Primer Design

MPrime is an interface which allows the effiicient high-throughput detection of multiple primers or oligonucleotides for genic regions in either the human, mouse, rat, zebrafish, or fruit fly genomes. In order to choose the regions of interest for primer or oligo design, you must choose the organism you are interested in, as well as the genic regions of interest. Genic regions can be identified by the gene name, GenBank or RefSeq accession, or by a keyword. Additionally, MPrime1.3 will now allow you to enter in fasta formatted sequences. Before primers are designed, you will be sent to a page that will allow you to select the genic regions you wish to use.
Rouchka EC, Khalyfa A, Cooper NGF. (2005) MPrime: efficient large scale multiple primer and oligonucleotide design for cutomized gene arrays. BMC Bioinformatics, 6:175. (doi:10.1186/1471-2105-6-175).

Available as a web interface

zebrafish repeats

Exact tandem repeats in the zebrafish genome

This database contains a total of 116,915 exact tandem repeats with a base length of at least three and a copy number of at least ten have been detected in the Zv8 assembly of the zebrafish genome. This web interface can be used to browse for repeats and primers for amplifying these repeats within a certain genomic region. In addition, the repeats can be downloaded as tracks for either the UCSC Genome browser (December 2008 build) or FishMap Zv8 browser.
Rouchka, EC. (2010) Database of exact tandem repeats in the Zebrafish genome. BMC Genomics 11:347. doi:10.1186/1471-2164-11-347

Available as a web interface and genome browser tracks

rMotifGen

rMotifGen: Random Motif Generator for Genomic Sequences

rMotifGen is a solution with the sole purpose of generating a number of random DNA or amino acid sequences containing short sequence motifs. Each motif consensus can be either user-defined, or randomly generated. Insertions and mutations within these motifs are created according to user-defined parameters. The resulting sequences can be helpful in mutational simulations and in testing the limits of motif detection algorithms.
Rouchka EC, Hardin CT (2007). rMotifGen: random motif generator for DNA and protein sequences. BMC Bioinformatics, 8:292. (doi:10.1186/1471-2105-8-292).

Available as a web interface and source code

RBF-TSS

RBF-TSS: Identification of transcription start sites using radial basis functions

RBF-TSS is a novel identification method for identifying transcription start sites that improves upon published TSS detection models. RBF-TSS incorporates a metric feature based on oligonucleotide positional frequencies, taking into account the nature of promoters. A radial basis function network for identifying transcription start sites is created using non-overlapping chunks (windows) of size 50 and 500 on the human genome.
Mahdi RN, Rouchka EC. (2009) RBF-TSS: Identification of transcription start site in human using radial basis functions network and oligonucleotide positional freqeuncies. PLoS One, 4(3):e4878. (10.1371/journal.pone.0004878)

Available as source code

motif PSO

DNA Motif Detection Using Particle Swarm Optimization and Expectation-Maximization

The Motif Swarm Algorithm aids in motif discovery, the process of discovering a meaningful pattern of nucleotides or amino acids that is shared by two or more molecules, is an important part of the study of gene function. In this work, we developed a hybrid motif discovery approach based upon a combination of Particle Swarm Optimization (PSO) and the Expectation-Maximization (EM) algorithm. In the proposed algorithm, we use PSO to generate a seed for the EM algorithm.
Hardin CT, Rouchka EC (2005). DNA Motif Detection Using Particle Swarm Optimization and Expectation-Maximization. Proc IEEE Swarm Intell Symp., 2005:181-184. (PMCID: 137489, PMID: 20436786)

Available as source code

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