Genomics Cohort Training—2024-2025

Summer 2024

Students took a summer bridging course DSCC 162: Data Structures in Python with Andrea Cogliatti as preparation for their fall matriculation into the program.

Fall 2024

Students participated in 13 credits of coursework. During the first semester the students took the following courses:

  • DSCC 462: Computational Introduction to Statistics, Professor Anson Kahng
  • DSCC 461: Introduction to Databases, Professor Eustrat Zhupa
  • DSCC 440: Data Mining, Professor Monika Polak
  • IND 501: SMD Research Ethics, Professor Paul Kammermeier

A pre-program survey was done by Cathy Cerosaletti to assess the cohort’s understanding and experiences and competency with research, ethics, equity and inclusion, genomics and career development skills.

Students began to connect with mentors.

Winter 2025

A sequence of three extra-curricular, hands-on workshops aimed at building core competencies in genomic data analysis were offered by the Genomics Research Center (GRC) in conjunction with the Goergen Institute for Data Science GIDS-REM fellowship program and the Center for Integrated Research Computing (CIRC). These workshops covered nine core competencies were required for GIDS-REM fellows were open to any researchers in the University of Rochester and Medical Center communities.

An introductory session on Tuesday, January 9 from 10 a.m.-3:30 p.m. by Professor Brendan Mort and staff of CIRC at the Vista Collaboratory in Carlson Library was required for those who needed Blue Hive access or basic knowledge of Linux clusters, running Jobs and Slurm, Modules, Software, and Jupyter.

The workshops were two hours each and led by John Ashton and staff of GRC:

  • Tuesday, January 14: Experimental Design and GRC deliverables. This workshop introduces experimental design considerations in the generation of high throughput sequencing data including RNAseq, ChIP-seq (and related -seq technologies).
  • Wednesday, January 15: Bulk RNAseq. This workshop introduces quality control in bulk RNA sequencing experiments and best practices in RNA seq analysis.
  • Thursday, January 16: Single cell sequencing. This workshop introduces single cell RNAseq and ATACseq data generation and analysis.

Spring 2025

Students returned to studies with 12 credits of coursework to take:

  • DSCC 465: Introduction to Statistical Machine Learning, Professor Cantay Caliskan
  • BST 434: Genomic Data Analysis, Professor Matthew McCall
  • BIOL 453: Computational Biology, Professor Justin Fay

Mentor Meetings were used to start discussions about summer internship placements.

Summer 2025

Students engaged full-time in their lab’s research assignments. Professor Fay initiated the Summer Seminar series—a weekly venue to learn and engage in applied problems in genomics. The series included short presentations from students, trainees and faculty on current research problems with an emphasis on pragmatic solutions. Presentations were followed by a discussion to enhance practical understanding and assessment of genomics approaches, methods and computational analyses. The seminar series was run as part of the Goergen Institute for Data Science MS program in applied genomics and open to students and faculty interested in application of genomics and genome technologies to problems in biology.

The seminar series also included a professional development component for students in the GIDS-REM training program. For this component students learn and assess presentation strategies and research communication skills to enhance their career goals in either academics or industry.

Seminar schedule (TBA)

Fall 2025

Students enrolled in:

  • DSCC 483: Practicum Project, Professors Ajay Anand and Cantay Caliskan
  • DSCC 457: Applied Genomics, Professor Amanda Larracuente

Presentations of summer research given during Meliora Weekend and the Fall Graduate Research Symposium.

Conference Travel

The cohort is considering attending one of the following conferences:

Practicum Project

Fall presentations will be posted as they become available.

Genomics Cohort 2024-2025

Headshot of Lydia Levasque.

LYDIA LEVASQUE

HOMETOWN: Westborough, MA

UNDERGRAD DEGREE: BS Microbiology, minor in Computational Biology from University of Rochester, magna cum laude, May 2024

WHY ROCHESTER: The curriculum of the GIDS-REM program, a multitude of research opportunities, and my relationships with my advisors and mentors such as Dr. Justin Fay, Dr. Amanda Larracuente, Dr. Richard Barth, and Dr. Raven Osborn drew me back to Rochester.

SELECTED MENTORS:

  • Juilee Thakar: Bioinformatics; Systems biology; Dynamic Modeling Tools
  • Caitlin Dreisbach: Use of quantitative methods to make better clinical assessments during pregnancy

SUMMER INTERNSHIP: TBD

HOW THE PROGRAM TRANSFORMED ME:

After Semester 1: “The program so far has helped transform the way I approach solving problems. Now, I am much more likely to think about how I can leverage programming languages like Python and R in conjunction with data science techniques to work towards solutions.”

FUTURE PLANS:

I would like to achieve my PhD in biology, specifically with a computational and analytical approach. I ultimately want to become a computational biologist, potentially one who uses her expertise in the industry or in academia. I'm curious about the applications of computational and data science to the field of microbiology, specifically to how we can better understand human microbiomes.

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Headshot of Mariah Nuzzo.

MARIAH NUZZO

HOMETOWN: Brookline, MA

UNDERGRAD DEGREE: BA Biology from Brown University, 2018; BS Nursing from MGH Institute of Health Professions, 2020

WHY ROCHESTER: The UR program is so unique in the emphasis it places on mentorship and student research. We are constantly encouraged to explore opportunities and get real project experience working directly with research and medical faculty at UR and the medical center.

SELECTED MENTORS:

  • John Ashton: Cancer biology, specifically leukemia stem cell (LSC) biology
  • Caitlin Dreisbach: Use of quantitative methods to make better clinical assessments during pregnancy

SUMMER INTERNSHIP: TBD

HOW THE PROGRAM TRANSFORMED ME:

After Semester 1:

“The program has provided me with resources and mentorship that surpassed my expectations. Our professors and advisors really push us to challenge ourselves, develop skills and seek out relevant experiences (both in genomics and data science). Coming from a non-data science background, I’m excited to see such significant improvements in my math skills and analytical abilities after one semester. I have also become involved in health care research through one of my classes!”

FUTURE PLANS:

I am planning to work as a bioinformatician in medical research. I am passionate about improving healthcare and patient experiences with medicine. I hope to use the skills I develop at UR to contribute to genomic research and developing our understanding of personalized medicine to treat complex medical conditions.

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Headshot of Brooke Pinales.

BROOK PINALES

HOMETOWN: Irondequoit, NY

UNDERGRAD DEGREE: BS Business Finance from SUNY Fredonia, 2018

WHY ROCHESTER: This program specifically is a good middle between math, one of my strengths, and science, something I’ve always wanted to do more with. Working in URMC’s Microbiology department as an administrative professional for the past two years exposed me to amazing work that is going on in that area and influenced my desires to get involved in research.

SELECTED MENTORS:

  • Nancy Chen: Population genetics with pedigrees; Contemporary evolution in natural populations; Evolutionary genetics; Conservation genomics; Avian genomics
  • Caitlin Dreisbach: Use of quantitative methods to make better clinical assessments during pregnancy

SUMMER INTERNSHIP: TBD

HOW THE PROGRAM TRANSFORMED ME:

After Semester 1: “This first semester has helped me to become more self-starting, value time management and focus much more on problem-solving. I've learned programming with R and SQL, when I was completely unfamiliar with both in August. Additionally, I've learned how to reach out to faculty in order to establish connections and ask for guidance.

FUTURE PLANS: I would love to stay at the University of Rochester, either in the Genomics Research Center or as a bioinformatician in a research lab. My main research interest is evolutionary genetics.

Linked In Profile (coming soon)
Headshot of Elijah Soh.

ELIJAH SOH

HOMETOWN: Teaneck, NJ

UNDERGRAD DEGREE: BA Medicine, Health and Society and minor in Data Science from Vanderbilt University, 2024

WHY ROCHESTER: I believe that the strong data science program here connected to the medical center provides an excellent foundation to learn and practice my skills. Having once been a pre-medical student, this field is very intriguing as it would connect my passion for health with my passion for data science.

SELECTED MENTORS:

  • Matt McCall: Statistical genomics; Systems biology; Bioinformatics
  • Dongmei Li: biostatistics; microarray data analysis; genomic data analysis especially in methylation and transcriptome data analysis; social media data analysis; public health

SUMMER INTERNSHIP: TBD

HOW THE PROGRAM TRANSFORMED ME:

After Semester 1:

“Through this program so far, I was able to start my studies as a MS Data Science student with a firm structure of what courses and what steps I should take to maximize my time here at the University of Rochester. Thus, as I was introduced to program faculty and learned foundational concepts this first semester, I look forward to learning about genomics data science in the future”

FUTURE PLANS:

Pursue a career in which I become a data scientist working at the intersection of sports and health. I believe that the use of data is extremely powerful in the field of sports science and sports medicine as analysis can translate to addressing various topics like performance optimization, injury prevention, recovery and more.

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Genomics Cohort Training

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