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DU Bioinformatics Lab

Welcome to the DU Bioinformatics Laboratory!

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The laboratory is currently working hard.  Please contact us to discuss our findings!

Differentiating Codon Usage Patterns among Species Projects:

PROUD RECIPIENT OF THE DAVENPORT RESEARCH FACULTY GRANT FOR THE "CODON USAGE PATTERNS AMONG LACTOBACILLUS SPECIES" PROJECT IN 2015.

Lactobacilli organisms assist with digestion and fermentation.  Some species are used routinely in probiotics and have been shown to cause weight changes in humans and other animals.  There are over 125 Lactobacillus species, ranging in %(G+C) from 35 – 55%.  No other genera have this variation so investigators are examining ways to re-classify this large, diverse group of organisms.  Is there a way to classify these species according to their ability to cause weight changes?  Our lab is using genomic codon usage and protein modeling methods to approach this question.

Detecting Mechanisms behind Antibiotic Resistance ProjectS:

PROUD RECIPIENT OF THE DAVENPORT RESEARCH FACULTY GRANT FOR THE "COMPUTATIONAL APPROACHES TO UNCOVER MECHANISMS OF ANTIBIOTIC RESISTANCE IN BACTERIA" IN 2017.

Antibiotic resistant bacteria are a growing public health concern with thousands of people dying each year from resistant infections. The lab uses computational approaches to predict mechanisms behind antibiotic resistance. The lab started by looking at methicillin resistant S. aureus (MRSA) and has moved onto comparing antibiotic resistant Streptococcus and Pseudomonas species.

Identification of Hypothetical Proteins ProjectS:

PROUD RECIPIENT OF THE DAVENPORT RESEARCH FACULTY GRANT FOR the "EXAMINING HYPOTHETICAL PROTEINS IN STAPHYLOCOCCUS AUREUS" PROJECT IN 2016.

A hypothetical protein is one detected solely on its genetic sequence and has no predicted function.  Almost 20% of antibiotic resistant S. aureus genomes is comprised of hypothetical proteins.  This project uses in silco protein comparison, modeling, and docking methods to predict the function of these proteins. This project has now expanded to all bacterial species, including Pseudomonas and Streptococcus.

Predicting Cancer Promoting Mechanisms behind Bacterial Infections ProjectS:

Chronic bacterial infections have been shown to cause cancer with some of the details starting to be elucidated experimentally.  The lab uses computational approaches to predict the mechanisms bacterial infections use to enhance cancer growth and formation. The lab's current work examines how Streptococcus infections influence colorectal cancer development, with the potential to help thousands of patients worldwide.

Do you want to meet the faculty and student researchers responsible for making these projects happen?  Check out our Lab Personnel page!