Justine Sundrud · Salt Lake City · Pulst-Scoles Lab, University of Utah

Toward a Bioinformatics PhD in neurodegeneration

Draft — Justine to edit.

I'm Justine Sundrud — lab specialist in the Pulst-Scoles lab at the University of Utah, applying to Bioinformatics PhD programs for Fall 2027. I want to use computation to understand neurodegenerative disease. This site is my sounding board: read my story, react to my directions, tell me where I'm wrong.

React to my research directionsHow you can help

01

The story

Draft — Justine to edit.

I grew up in New Orleans — exploring the city, canoeing the canals, sharing adventures with my dad. In 2016 he was diagnosed with Parkinson's disease, and our relationship changed. I went from adventuring with him to trying to protect him, and feeling powerless against a disease I could barely understand.

That powerlessness sent me into the literature. I read everything I could find, mapping his symptoms to their biology, and a conviction took hold: if we could understand these diseases at the molecular level, families like mine might get answers that felt less like fate.

I work on that conviction every day now, in a lab that studies the disease family that includes my father's.

02

The work so far

Draft — Justine to edit.

My path runs in three chapters. Bench roots: undergraduate research at Loyola New Orleans — antimicrobial peptide synergy, a peer-reviewed publication, then running the lab after graduating. Patients and data: four years at the Maliheh Free Clinic in Salt Lake City, writing ~$1M/year in grants, running quality-improvement initiatives, and learning to pull answers out of EHR data — six co-authored papers on what uninsured patients actually experience. Neurodegeneration: since 2023, the Pulst-Scoles lab — sm-FISH, Western blots, iPSC neurons, and the transcriptomics of SCA4 and STAU1-driven disease.

I've seen both ends of translation: the bench where mechanisms are found, and the clinic where they matter.

03

Research directions

Three candidate frameworks, deliberately unfinished. This is the part I most want reactions to — each ends with the questions I'm wrestling with and a way to tell me what you think.

Direction A

Computational dissection of neurodegeneration

Use transcriptomics and machine learning on patient-derived models to find the pathways that actually drive neurodegenerative disease — and the ones we can drug.

Draft — Justine to edit.

Our SFN 2026 work profiled iPSC-derived neurons from SCA4 patients: disrupted synaptic programs, altered mitochondrial metabolism, DNA-damage response, p53-associated cell-death signaling. The data says SCA4 is both loss- and gain-of-function. I want to build on exactly this kind of evidence: large-scale omics on human-derived models, analyzed rigorously, to rank disease mechanisms by druggability.

What I'm wrestling with

  • — Is ZFHX3 loss-of-function or gain-of-function the better therapeutic handle in SCA4 — and what experiment settles it?
  • — Which single-cell or multi-omic layer would add the most signal to our iPSC neuron data for the cost?

How strong is this direction?

Direction B

RNA biology of neurodegeneration

STAU1, NEAT1, and paraspeckles: how RNA-binding proteins and stress responses tip neurons from coping into dying — in ALS, FTD, and the ataxias.

Draft — Justine to edit.

My wet-lab work lives here: visualizing RNA with sm-FISH, probing STAU1's link to p53 apoptotic signaling (our 2025 Cell Death & Disease paper). The open mechanistic territory — what paraspeckles are actually doing in disease — is enormous, and computational analysis of RNA-protein interaction data could crack it open.

What I'm wrestling with

  • — Are paraspeckles protective, pathological, or both depending on stage — and how would you design the time-course to tell?
  • — Does the STAU1–p53 axis generalize beyond SCA2/ALS models to sporadic disease?

How strong is this direction?

Direction C

Bench-to-clinic translation

Therapeutic development with patients in view: from the lab's antisense-oligonucleotide heritage to data-driven trials and diagnostics that reach people like the ones I served at the free clinic.

Draft — Justine to edit.

The Pulst-Scoles lab took ASO therapy for SCA2 from mouse models toward humans. I spent four years at a free clinic watching what happens when treatments don't reach people. A research program at this intersection — translational bioinformatics for neurodegenerative therapeutics — is where my whole path points.

What I'm wrestling with

  • — What should a bioinformatics PhD optimize for if the goal is therapeutics: methods development or disease biology depth?
  • — Which programs/labs actually do translation well, rather than just saying it?

How strong is this direction?

04

Influences

The papers, books, and people behind the thinking.

05

The road to December

Applications are due December 1, 2026, for a Fall 2027 start. This is the real plan.

  1. June 2026

    Sounding board live

    Site shared with lab colleagues and mentors; directions open for feedback.

  2. July 2026

    Program list drafted

    Target Bioinformatics PhD programs identified and ranked.

  3. August 2026

    Directions narrowed

    Feedback synthesized; one research direction promoted to the hero.

  4. September 2026

    Recommenders confirmed

    Three letters committed.

  5. October 2026

    Statement of purpose drafted

    Draft 1 complete and out for review.

  6. November 2026

    Applications assembled

    All materials final; mock interviews done.

  7. December 2026

    Applications submitted

    Most Bioinformatics PhD deadlines hit December 1.

06

How you can help

If you've defended a thesis, run a lab, or are walking this road too — these are my specific asks.

Or just leave a thought

Your thoughts