CV

Caitlin Guccione

Bioinformatics Ph.D. Student

cguccion@ucsd.edu

Objective I am a Ph.D. graduate student with a projected summer 2024 graduation looking for a computational biology role in industry. My passion is harnessing the power of big data with my computer science and mathematics expertise to tackle complex biological challenges, particularly in the field of oncology.

Interests : Bioinformatics, Computional Biology, Oncology, Cancer Microbiome

Education

Ph.D. Bioinformatics & Systems Biology

University of California, San Diego
September 2020 - Present

M.S. Applied Mathematics

University of Rhode Island
September 2018 - August 2020

  • Final Project : Stochastic Models with Applications to Genetics, Cancer, AIDS & Biomedical Systems

B.S. Applied Mathematics & B.A. Computer Science

University of Rhode Island
September 2016 - May 2020

  • Minor : Biological Sciences
  • Honors : magna cum laude, University of Rhode Island Honors Program
  • Extracurriculars : NCAA DI Student-Athlete, School Record Holder

Micro MBA

Rady School of Management, University of California, San Diego May 2023 - September 2023

Technical Skills

Python ० Jupyter Lab ० Linux Command Line ० Github ० R ० RStudio ० Slurm Workload Manager ० Shell Scripting ० Anaconda ० Amazon Web Services ० Microsoft Office ० Adobe Illustrator ० Vim ० C++

Professional Expereince

  • Improved computational pipelines for the detection of cfmDNA (cell-free microbial DNA)
  • Used scikit-learn machine learning for the classification of microbial differences across cancer tissue
  • Ran BWA, Bowtie2, Minimap2, Samtools, and other common bioinformatic command line tools
  • Gathered and processed large genomic cohorts such as The Cancer Genome Atlas & genomes on NCBI
  • Written clean, well commented, reproducible code with Github Repositories and Conda environments
  • Processed over 100 terabytes of whole genome sequencing data using high performance computing
  • Microbial analysis of 16S and shotgun datasets including alpha and beta diversity metrics such as PCoA

Leadership & Mentorship

  • Project manager for the filtering, aggregation & analysis of over 150 cancer microbiome datasets (13)
  • Independently supervised Ph.D. Visiting Scholar and two undergraduate students
  • Project deliverables included drafted publication and three invited conference presentation
  • Graduate Bioinformatics Council: Community Event Chair + Outreach Committee Member
  • NCAA Division I Student-Athlete & Captain

Presentations

  • “Improving microbial detection in cancer tissue samples with computational host depletion using the pangenome”, Poster at American Association for Cancer Research Annual Meeting, April 2024
  • “Enhancing microbial insights in cancerous tissue: unveiling the hidden microbiome” Cancer Genomics Cloud, Seminar Series; July 2023
  • “Evolutionary modeling of microbiome community assembly in the context of human pre-cancer progression.” Talk at Math Modeling of Microbes Conference, Max Planck Institute;September 2022
  • “Community assembly dynamics of the microbiome in premalignant Barrett’s esophagus.” Structural & Functional Genomics Retreat, Moores Cancer Center; March 2022

Awards

  • Voted Best Presentation - UC San Diego Bioinformatics Program Conference, 2024
  • Winifred B. Keaney Award: Role model student-athlete - Univ. of Rhode Island, 2020
  • Biology Department Alpha Research Award - Univ. of Rhode Island, 2020
  • Winifred P. Kelley Award of Academic Excellence - Univ. of Rhode Island, 2017

Experience

Bioinformatics Graduate Reseracher

University of California, San Diego
September 2020 - September 2024 (predicted)

  • Designed computational host filtration pipeline to remove human reads for microbial analysis (10)
  • Applied math modeling to determine microbial evolution across esophageal cancer development (12)
  • Computationally extracted microbial reads from blood and determined microbial differences across liver disease (11) using differential abundance (6) and random forest machine learning (9)
  • Invited Talk: Cancer Microbiome

Undergraduate Reserach Assistant

University of Rhode Island
January 2018 - September 2020

Informatics Intern

Agios Pharmaceuticals
Summer 2019

  • Implemented a Laboratory Information Management System for reproducible research using R

Discrete Mathematics & Theoretical Computer Science Research Experience for Undergraduates

Rutgers Cancer Institute of New Jersey
Summer 2018

Data-Intensive Scientific Computing Research Experience for Undergraduates

University of Notre Dame
Summer 2018

Publications

[13] Guccione, C.#, Takaces, B.#, et al. Comparative Analysis of the Microbial Composition of Different Cancer Tumor Tissues [In preparation for June 2024 submission]

[12] Guccione, C., et al. Community assembly modeling of microbial evolution within Barrett’s esophagus and esophageal adenocarcinoma. [In preparation for ISME J March 2024 submission]

[11] Guccione, C.#, Dantas Machado, A.#, et al. Microbial DNA in tumor and blood differentiates primary and secondary hepatic malignancies [In preparation for Cell & Host Microbiome April 2024 submission]

10 Guccione, C.#, Patel, L.#, et al. Incomplete human reference genomes can drive false sex biases and expose patient-identifying human sequences in metagenomic data. [Submitted to Nature Microbiology]

9 Guccione, C.#, Sepich-Poore, G.#, McDonald, D.#, Evguenia, K.#, et al., Robustness of cancer microbiome signals over a broad range of methodological variation. Oncogene (2024).

8 Chapman, O. S., Luebeck, J., Sridhar, S., et al. Circular extrachromosomal DNA promotes tumor heterogeneity in high-risk medulloblastoma. Nature Genetics (2023).

7 Guccione, C., McDonald, D., et al.. You are what you excrete. Nature Microbiology (2023).

6 Rahman, G., Morton, J., Martino, C., Sepich-Poore, G., Allaband, C., Guccione, C., et al. BIRDMAn: A Bayesian differential abundance framework that enables robust inference of host-microbe associations. bioRxiv (2023). [Submitted to Nature Microbiology]

5 Ghosh, P., Campos, V., Vo, D., Guccione, C., et al. AI-assisted discovery of an ethnicity-influenced driver of cell transformation in esophageal & gastroesophageal junction adenocarcinomas. JCI Insight (2022).

4 Ma, S. D., Guccione, C., et al. Oral Microbiome Diversity Between Patients With Normal Versus Elevated Salivary Pepsin Levels & Its Implication in Gastroesophageal Reflux Disease. Foregut (2022).

3 Guccione, C.#, Sepich-Poore, G. D.#, et al. Cancer’s second genome: Microbial cancer diagnostics and redefining clonal evolution as a multispecies process. BioEssays (2022).

2 Guccione, C., Yadlapati, R., et al. Challenges in Determining the Role of Microbiome Evolution in Barrett’s Esophagus and Progression to Esophageal Adenocarcinoma. Microorganisms (2021).

1 Loh, J. W., Guccione, C., et al. All-FIT: Allele-frequency-based imputation of tumor purity from high-depth sequencing data. Bioinformatics (2020).

#Authors contributed equally, [ ] In preparation for submission