Computational Biosciences Undergraduate Research Portal

This portal was designed to connect UCLA faculty and UCLA undergraduates around biosciences research projects that involve data analysis or modeling, using the computational approaches of Bioinformatics and Systems Biology.

UCLA students contribute substantively to the research programs of UCLA laboratories and UCLA laboratories play key roles in preparing aspiring leaders in the field.

FACULTY

PROJECTS : Please submit your new projects via this short form: Undergraduate Research Project Form (you may submit multiple projects, one for each submitted form).

STUDENTS

EXPLORE : Click on your field of interest below and explore exciting research opportunities. Check whether the required qualifications and coursework match with yours.

CONNECT: Once you have identified projects that interest you and are a suitable match, please contact the Faculty directly at the email listed.

Biomedical Imaging and Informatics
Computational Genetics and Genomics

Spatiotemporal RNA-Seq analysis of the thymic vasculature during distinct development stages

We have an exciting, newly funded project that focuses on the microenvironment of the thymus, the organ responsible for recruiting hematopoietic stem cells and driving their development towards the T-cell lineage. We are looking to identify unique subpopulations of endothelial cells and their dynamics during different developmental stages (embryonic, neonatal and adult postnatal) by using both single-cell and spatial RNA-Seq technologies (10X Genomics). We aim to understand the contribution of different types of endothelial cells to thymus growth and function.
Integration of single cell RNA-Seq and spatial transcriptomics will be instrumental to elucidate previously hidden vascular components of the thymic microenvironment, as well as their interaction with other thymic stromal cells, with the ultimate goal of improving T-cell immunity. We are looking for student(s) with bioinformatics and computational biology, who are familiar with R/Seurat, Cell/Space Ranger, and able to work with different types of deconvolution and mapping methods.

Contact Name: Gay Crooks
Contact Email: sdebarros@mednet.ucla.edu
Website: https://www.crooks-lab.com/
Requirements: Advanced (junior year): Bioinformatics minor, CaSB Imaging, CaSB Biological Dynamical Systems
Quarters: WinterSpringSummer
Hours Per Week: 12
Location: On campus/online
Programming Languages: Python, R
Updated: November 30, 2023

Computational Genetics and Genomics
Computational Neuroscience

Genetic architecture of neuropsychiatric traits

We use genomic data to study the genetic architecture of psychiatric disorders such as schizophrenia and bipolar disorder. Bioinformatic tools are used to decipher clinical features as well as genetic susceptibility, epigenetic features, and regulation of gene expression. Previous experiences in R, Python, shell scripting, RNA-seq or WGS analysis, handling big genomic datasets, and using UCLA Hoffman2 cluster are strongly desired. Student projects are tailored to the interest and skill set of the student.

Contact Name: Roel Ophoff
Contact Email: ophoff@g.ucla.edu
Website: https://bioscience.ucla.edu/people/roel-a-ophoff/
Requirements: LS40: statistics of biological systems, simulations-based OR STATS10: introduction to statistical reasoning (Basic, freshman year) - Math 33A/B: linear algebra, differential equations (Intermediate, sophomore year) - Bioinformatics minor, CaSB Neuroscience (Advanced, junior year))
Quarters: Any
Hours Per Week: 12
Location: on-campus and remote
Programming Languages: Python, R
Updated: November 7, 2023

Computational Cell and Systems Biology
Computational Genetics and Genomics

Bioinformatics Undergraduate Researcher

Cell type gene regulatory networks (GRNs) model gene regulation in individual cell types from single cell omics data to elucidate cell type-specific mechanisms that contribute to complex disease. Our lab has developed a single cell GRN inference method and is scaling it to thousands of single cell RNA-seq and spatial transcriptomics datasets in human and mouse tissues. We are seeking a highly driven undergraduate with a computational biology background to build and analyze these GRNs. This student will also help develop and implement a computational pipeline to predict key regulatory genes and disease mechanisms in the GRNs, as well as benchmark the performance of our GRNs with existing tissue-level networks.

Contact Name: Xia Yang
Contact Email: xyang123@g.ucla.edu
Website: https://yanglab.ibp.ucla.edu/
Requirements: Bioinformatics minor, CaSB Biological Data Sciences (Advanced: junior year)
Quarters: Any
Hours Per Week: 12
Location: On-campus
Updated: October 4, 2023

Biomedical Imaging and Informatics
Computational Neuroscience

We are looking for a data scientist to help complete a project using predictive models, machine learning/artificial intelligence looking at clinical outcomes for patients with traumatic spinal cord injury after staying in a rehabilitation facility. Analysis would involve studying quantifiable clinical data points to help predict if a spinal cord injury patient can improve (re-learn how to walk, use the restroom, take care of oneself) after performing a specific rehabilitation program.

Contact Name: Irene Say, MD / Sandra Holley, PhD / Daniel Lu, MD PhD
Contact Email: irene.say24@gmail.com
Website: N/A
Requirements: Basic (freshman year): LS30A, B: mathematics for life scientists OR Math 31A/B: differential and integral calculus..., LS40: statistics of biological systems, simulations-based OR STATS10: introduction to statistical reasoning, LS7A/B/C: life science core in cell and molecular biology, genetics, evolution and ecology, physiology and Human biology - Intermediate (sophomore year): CS32: stacks, queues, lists, algorithm analysis, trees, graphs, searching, sorting
Quarters: Any
Hours Per Week: 10
Location: Remote/online
Programming Languages: Python, R, Matlab
Updated: January 26, 2023

Biomedical Imaging and Informatics

Robust AI labeling for live cell phenotyping

We have recently developed an AI platform for translating label free images into immunofluorescence-like images. While this platform can potentially become a powerful tool for molecular-based live cell imaging, current AI predictions do not have the robustness for practical implementations. In this project, we aim to develop and implement domain adaptation algorithms to generalize our trained AI models. The student will mainly focus on obtaining training data (microscopy images) and characterize the performance of AI models developed by our CS collaborators.

Contact Name: Neil Lin
Contact Email: neillin@g.ucla.edu
Website: https://www.linlab.seas.ucla.edu
Requirements: Basic (freshman year): LS30A, B: mathematics for life scientists OR Math 31A/B: differential and integral calculus..., LS7A/B/C: life science core in cell and molecular biology, genetics, evolution and ecology, physiology and Human biology - Intermediate (sophomore year): Math 32A: calculus of several variables, Math 33A/B: linear algebra, differential equations - Advanced (junior year): Bioinformatics minor, CaSB Imaging
Quarters: Full Year
Hours Per Week: 10
Location: On-campus
Programming Languages: Python, Matlab
Updated: January 26, 2023

Questions?

Please contact the Undergraduate Programs Manager at qcboffice@lifesci.ucla.edu for general information.

Fields of Interests:

Spatiotemporal RNA-Seq analysis of the thymic vasculature during distinct development stages

Genetic architecture of neuropsychiatric traits

Bioinformatics Undergraduate Researcher

Robust AI labeling for live cell phenotyping

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