Bio

Cory Strope is a Postdoctoral research fellow working in statistical genetics at North Carolina State University advised by Jeffrey L. Thorne. Cory received his PhD in the field of Bioinformatics from the University of Nebraska, coordinating his research between Computer and Biological Sciences working with Stephen D. Scott and Etsuko N. Moriyama (dissertation). Cory led the design and development of the biological sequence simulation software, indel-Seq-Gen, and remains the lead developer and project manager of indel-Seq-Gen, supervising undergraduate and PhD students in further developments and improvements to the software. Cory is currently developing end-point conditioned sequence evolution data augmentation schemes for use with dependent-sites molecular evolution models. Cory is a member of the Society of Molecular Biology and Evolution (SMBE).

Research

My current research is focused on constraint mechanisms on either DNA or amino acid sequences, with future intentions of better understanding the interplay of constraints between genes (codon-level) and product sequence (protein). As a first step towards this goal, I am using orthologous sequences mined from whole genome data of prokaryotic organisms for an exploratory analysis aimed at discovering novel insertion and deletion acceptance sites in gene terminal regions.

The primary mechanism of modeling sequence evolution has been to model mutational events based on statistical methods of sequence mutation, which averages the effects of mutational mechanisms based on event occurrences derived from hundreds of thousands sequences and assume complete independence between sequence sites. Mutational events using these models are applied independently and homogeneously along simulated sequences. However, genomic sequences and their products range from unconstrained sequences (e.g., non-coding DNA or duplicated proteins) with little to no dependence between sites to highly constrained sequences (e.g., transcriptional elements or hemoglobin proteins) with many interacting sites. Only a fraction of such sequences will fit the "average" sequence mould as specified by current statistical models. I have developed indel-Seq-Gen (iSG) to address this gap, a biological sequence simulation method that incorporates a novel model of sequence constraints effects on mutational processes, mimicking functionally important sequence regions. iSG is still being actively developed to (i) model additional sequence constraints as more mutational mechanisms are discovered, (ii) generate sequences using dependent sites models, and (iii) infer the evolutionary path of mutations of a set of related sequences for both independent and dependent sites models.

Taken together, my research will expand the knowledge base of mutational mechanisms on functionally constrained sequences and help to pinpoint objective function improvements for bioinformatic methods that will benefit the bioinformatics and evolutionary biology community.