Bioinformatics scientist/PhD candidate

Goal

I am looking for internship opportunities that will allow me to apply my bioinformatics skills while making new discoveries in the areas of NGS and multi-omics analysis or data driven science. I am also looking to develop my coding skills in a more collaborative environment.

Summary

I study alternative splicing in the C. elegans genome by writing algorithms in Python on a Linux system to parse through genomic data. Using a simple stochastic model of the noisy background of alternative splicing, the not-so-simple nature of alternative splice site selection is revealed. I am working on refining the process of describing these instances of biologically regulated splicing against the noisy background. I also have extensive experience as a teaching assistant, which has helped me develop strong communication and organizational skills.

Education

• University of California, Davis. In-progress PhD, advanced to candidacy, Integrative Genetics and Genomics. September 2019-present
• University of California, Davis. MS, Integrative Genetics and Genomics. Filed March 2024
• California State University, Long Beach. BSc, Microbiology. September 2014-May 2019

Skills

• Proficiency in Python and Unix
• Basic understanding of Snakemake, RNA-seq analysis, and other bioinformatic methods like BLAST

Research experience

University of California, Davis: September 2019-present
Advisor: Dr. Ian Korf
Thesis: Modeling the stochastic nature of alternative splicing

High-throughput RNA-seq data reveals the presence of millions of low-abundance, seemingly useless splice isoforms. We believe that mRNA splicing is largely a stochastic process, with the ‘correct’ isoforms simply being more likely to occur. To test this hypothesis, I have generated all possible combinations (APC) of splice isoforms from a given gene sequence using the C. elegans genome. Isoforms are then scored using probabilistic models. A position weight matrix scores the donor and acceptor sites, and a Markov model and length model scores the exons and introns. We believe poor predictions made by the APC model indicate interference of the stochastic process by other biological processes. I am currently examining gff files generated by the APC algorithm.

Project repo: https://github.com/icacedo/splicing

California State University, Long Beach: June 2017-May 2019
Advisor: Dr. Jesse Dillon
Project title: Total coliforms collected during wet vs. dry weather and from protected vs. non-protected beaches do not show differences in the incidence of antibiotic resistand coliforms

Fecal coliform levels increase in local beach water after heavy rainfall, increasing the risk of illness for beach goers. Additionally, environmental antibiotic resistance is also of concern in these coliforms. I tested the incidence of multiple antibiotic resistant coliforms from southern California beaches by performing growth experiments on agar with antibiotic disks. Zones of inhibition were measured and used to determine the incidence of multiple antibiotic resistance, which was quite low and not significantly different depending on site. However, over 50% of isolates were shown to be ampicillin resistant. The project lead was Rebecca Hernandez, a Master’s student.

Project paper:
Hernandez, R., Acedo, I., Dillon, J. G. 2020. Impact of wave action and rainfall on incidence and antibiotic resistance of total coliforms in Southern California beaches. J. Water Health. 18(5) DOI:10.2166/wh.2020.100

Relevant teaching assistantship experience

• Introduction to genomics and bioinformatics Spring 2022, Spring 2021
• Introduction to biology, Fall 2023, Fall 2021
• Structure and function of macromolecules, Spring 2023

Relevant coursework completed at UCD

• Graduate group core classes, Fall 2019-Spring 2020
  • Genetic analysis, Genomics, Quantitative and population genetics
• Applied multivariate modeling Fall 2020
• Microbial biology Fall 2020
• Scientific professionalism and integrity, Fall 2020
• Machine learning genomics, Fall 2021

Honors and awards:

CSULB BUILD Research Scholar: June 2017-May 2019

NIH funded research training program for upper division students seeking a PhD level education. Curriculum included how to present research professionally and conduct research ethically, as well as completing a research project.

CSULB BUILD Research Associate: June 2016-May 2017

NIH funded research program for lower division students exploring laboratory research.