Miller, Justin B

Miller, Justin B.: Department of Internal Medicine, Division of Biomedical Informatics, Pathology, College of Medicine


Ebbert Computational Lab

Miller Computational Lab

Research Overview:

Drs. Mark Ebbert and Justin Miller are both working on various projects that would benefit from the supercomputer resources. All data stored on the supercomputer would be completely de-identified (IRB approval not required) or downloaded from publicly available datasets (IRB approval not required).

Dr. Ebbert's research interests focus on identifying structural genomic variants unique to people with Alzheimer's disease. Additionally, Dr. Ebbert is developing novel algorithms to interpret data generated from long-read sequencing/imaging technologies such as the Oxford Nanopore Technologies (ONT) PromethION sequencer and the Bionano Saphyr genome imager. No patient information or identifiable data will be stored on the supercomputer. Drs. Ebbert and Miller are not involved in the deidentification of the data and do not have access to any protected health information that could be used to identify any of the samples.

Dr. Miller's research interests focus on the identification of Alzheimer's disease subtypes with different long-term health trajectories. Additionally, Dr. Miller specializes in algorithmic design and development with an emphasis in machine learning. Dr. Miller is currently assessing functional interactions between proteins by developing a novel algorithm to detect evolutionarily-conserved regions within two or more proteins. Dr. Miller has previously developed several phylogenomic algorithms to assess species relatedness, and he plans to continue that work by integrating phylogenic biases that he previously published (e.g., codon pairing, ramp sequences and codon aversion) into a single phylogenomic metric. Data used for those analyses would originate from publicly available repositories (e.g., RefSeq, NCBI, GenBank).    


Software:

We will use various open-source software packages that Drs. Miller and Ebbert have published (e.g., ExtRamp, JustOrthologs, The Protein Interactions Calculator [PIC], Kmer-SSR, The Polygenic Risk Score Knowledge Base, Ramps Online, CAM, codon pairing) to analyze the genomic data. Additionally, we plan to use various genomic analysis tools (e.g., GATK, SAMtools, bcftools, vcftools, blast) to analyze the genomic data. We will continue to develop novel software packages to integrate data generated from the Bionano Saphyr machine and the ONT PromethION sequencer to facilitate data integration between these recently-developed sequencing machines. Most applications will be written in Python, bash, C++, or Perl.


Experience:

Both Drs. Mark Ebbert and Justin Miller have degrees in Bioinformatics with Minors in Computer Science and have been working with large computing clusters for a combined experience of approximately 20 years, including completely managing small clusters. Most recently, Dr. Ebbert managed a shared compute cluster at the Mayo Clinic, and Dr. Miller directed a team of undergraduate and graduate students on a supercomputer at Brigham Young University.


Principle Investigators:

Mark Ebbert, Ph.D. (Ebbert Computational Lab)

Justin Miller, Ph.D. (Miller Computational Lab)


Graduate students:

Bernardo Aguzzoli Heberle (graduate student), Added 03/15/2021

Erik D Huckvale (graduate student), Added 06/10/2021

Caleb Kennedy, Added on MCC cluster, 09/12/2022 

Abygail R Cacurak, Added on MCC cluster, 09/12/2022 

Anish V Penmecha, Added on MCC cluster, 09/12/2022 

Emily M Quarles, Added on MCC cluster, 09/12/2022 

Kate Horger, Added on MCC cluster, 09/12/2022 

Caylin Hickey, Cloud Engineer, Added on MCC cluster, 09/12/2022 

Tiffany N Clark, Added on MCC cluster, 11/10/2022 

Ketsile Ipeleng Dikobe, Added on MCC cluster, 12/16/2022 

Ellen Whitworth Heaberlin, Added on MCC cluster, 01/25/2023 

Coleman Reed, Added on MCC cluster, 02/03/2023 

Leah Moylan, Added on MCC cluster, 02/03/2023

Luke E Olsen, Added on MCC cluster, 02/28/2023 

Hady W Sabra, COM Office of Biomedical Education, Added on MCC cluster, 04/28/2023 

Shen Zhang, Added on MCC cluster, 05/23/2023 

Blake K Byer, Added on MCC cluster, 09/25/2023 

Jason Sun, Added on MCC cluster, 09/25/2023 

Anna Ho, Added on MCC cluster, 09/25/2023 

Hannah Allen, Added on MCC cluster, 10/23/2023 

Harshith Tummala, Added on MCC cluster, 10/23/2023 



Research Associate:

Madeline L Page, Sanders-Brown Ctr. on Aging, (Programmer Systems) Added 07/20/2021


Undergraduate:

Matthew Hodgman (future hire)


Grants:



Publications:


Center for Computational Sciences