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Home Projects

A few of our current research projects.

Characterization and Analysis of Codon Usage Bias


Genomic sequencing projects are an abundant source of information for biological studies ranging from the molecular to the ecological in scale; however, much of the information present may yet be hidden from casual analysis. One such information domain, trends in codon usage, can provide a wealth of information about an organism's genes and their expression. Degeneracy in the genetic code allows more than one triplet codon to code for the same amino acid, and usage of these codons is often biased such that one or more of these synonymous codons is preferred. Detection of this bias is an important tool in the analysis of genomic data, particularly as a predictor of gene expressivity. Methods for identifying codon usage bias in genomic data that rely solely on genomic sequence data are susceptible to being confounded by the presence of several factors simultaneously influencing codon selection. We have developed novel techniques for removing the effects of one of the more common confounding factors, GC(AT)-content, and of visualizing the search-space for codon usage bias through the use of a solution landscape.

See all of our research publications on molecular evolution.


Identification of Biomarkers of Toxicity and Downstream Outcomes


Metabolomics is the exhaustive characterization of metabolite concentrations in biofluids and tissues.  The use of NMR and chromatography-linked mass spectrometry to assay metabolic profiles of tissue homogenates and biofluids has been increasingly recognized as a powerful tool for biological discovery.  In recent years metabolomics techniques have been applied to a wide variety of diagnostic, preclinical, systems biology, and ecological studies.  Working with Dr. Nick Reo's NMR spectroscopy lab at Wright State University, we are developing standards-based tools and web services for the pre-processing, normalization/standardization, exploratory and comparative analysis, and visualization of NMR spectra from biofluids.

See all of our research publications on metabolomics


Forensic DNA research



PCR-based amplification of STR loci has become the method of choice for the purpose of human identification in forensic investigations.  With these loci, length polymorphisms associated with differences in the number of tandem repeats of four-nucleotide (tetranucleotide) core sequences are detected after polymerase chain reaction (PCR) amplification.  A set of thirteen STR loci are typically genotyped with commercially available kits and length polymorphisms are identified with machines such as the Applied Biosystems 310 or 3100 capillary electrophoresis systems.  In the analysis and interpretation of DNA evidence using STRs, a surprising number of technical, statistical, and computational issues emerge.  Together with Forensic Bioinformatics Services, Inc., we investigate algorithmic, empirical, and statistical approaches to address many of these problems.  The end goal of our research is to ensure that DNA evidence is treated with due scientific objectivity in the courtroom.

See all of our publications in forensic DNA.

Download slides from Dr. Raymer's OCCBIO tutorial on Forensic DNA analysis (Powerpoint .pptx, 2.4 MB).


Protein Structure


Understanding protein structure and the forces that drive protein folding is one of the most fundamental and challenging problems in biochemistry.  We are pursuing a number of projects that explore the determinants of protein structure and improve computational structure prediction methods.  Our current areas of investigation include:

  • Development of a novel technique for the identification of remote homologs,
  • Characterization of secondary structure variability for protein sequences, and
  • Hybrid experimental/computational methods for high-confidence prediction of protein tertiary and quaternary structure.

The latter project involves improving the reliability of protein structure prediction algorithms by including experimental information in the model selection process.  In collaboration with Dr. Jerry Alter's lab, (Department of Biochemistry and Molecular Biology, Wright State University) we have developed the computational support for MRAN - Modification Reactivity Analysis (see figure above).  Based upon the reaction rate of proteolysis or residue modification reactions, solvent accessibility and other physiochemical properties of specific residues can be estimated.  This information can then be used to drive the process of selecting and refining conformational models for further exploration.

See our publications in protein structure.



SCALE-UP in the Computer Science Core

Scale-up Headlines

Over the past decades, pedagogical research shows that actively learning students obtain higher levels of achievement than students learning passively [Johnson, 1991; Felder, 1998; Springer].  Modern STEM classrooms have been responding to the observation that traditional passive lectures are often the least educational aspect of university.  The growing volume and accessibility of digital content including reading material, free on-line lecture content, youtube videos, TED talks, and so forth from world-class thinkers and educators is making the traditional passive lecture increasingly obsolete.  Universities must respond to these changes in order to serve their mission.  One solution to these problems are Active/Cooperative (ACL) strategies such as the Student-Centered Active Learning Environment for Undergraduate Programs (SCALE-UP) Project [Beichner et al. 1999; Beichner et al. 2007;].  In the SCALE-UP classroom, “lecture” time is spent primarily on hands-on activities, questions and discussion of work completed/viewed prior to the lecture period.   In this project, we will introduce new SCALE-UP classroom and develop SCALE-UP alternatives to our entire current introductory core in computing.   Secondly, we will design, develop, or adopt the tools, abstractions, materials, and learning experiences to enable computing students to thrive in the SCALE-UP approach. Prior SCALE-UP research deals principally with barriers in the physical sciences.  This project will extend this to work to identify and overcome barriers in computing education. Over the course of the proposed work, courses will be developed for initial effectiveness, improved based upon assessed effectiveness, and then packaged into modules for dissemination.   Finally, we will evaluate the effectiveness of the revised delivery of the core content using techniques such as observational rubrics, surveys, peer assessment, and formative assessment forms.  This evaluation will give us the information that we need to improve our courses, materials, and faculty as well as the information necessary to publish our results and help others adopt similar successful techniques.