Research Projects by Subject

Note: Each research project will involve background reading for the interns provided by their mentors. Each research project will involve a final presentation by the interns.

Interns are expected to work collaboratively on the same project and/or data set. This may preclude rising seniors from submitting papers based on such projects to the Intel Science Talent Search competition.

Biomolecular Engineering

Code Research Project Descriptions
BME-01 Title: Investigating Cellular Sorting Function in Huntingtons's Disease Human RNAseq Data
Primary mentor: Gepoliano Chaves
Faculty advisor: Prof. Nader Pourmand
Location: UCSC Main Campus
Number of interns: 3

Project description: Huntington's Disease is a neurodegenerative disease caused by an expansion in the glutamine codon of the Huntington (HTT) gene. Depending on the biological model, this neuropathy shows molecular mechanisms that are similar to other disorders, such as diabetes and Alzheimer's Disease (AD). For example, in a study submitted for publication, the mentor's group demonstrated that a gene, known to be a marker for both diabetes and AD, has its expression regulated by mutant HTT. Research of genes involved in several diseases has the potential to improve the understanding of the underlying biological processes, raising the possibility that drugs being investigated as a therapeutic alternative for one disease, could target the same gene in a parallel pathology.  

Tasks: The SIP interns will assist the mentor in identification of single nucleotide polymorphisms (SNPs) in a human dataset from post-mortem HD patients collected from a paper previously published by a different group. The SIP interns will have the opportunity to see how genomic data is initially processed and analyzed, by installing software such as the Genome Analyses Tool Kit (GATK), and use a Unix interface. The aim of this step is to find evidence of dysregulation of signaling pathways that control the sorting function of the cell. The mentor's research group has identified protein sorting processes disruption to be a common feature between diabetes, HD and AD. The SIP interns will help understand whether and how the sorting process is being affected by mutant HTT in the mentioned dataset. The sorting function is the ability the cellular machinery has to transport its proteins to proper locations in order to establish the normal functioning of the cell. The end goal is to identify genetic variance (e.g. SNPs) associated with HD. The SIP interns will install tools for genome alignment, gene expression and SNPs calling.

Required skills for interns prior to acceptance: None
Skills intern(s) will acquire/hone: Computer programming; lab work
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: OFF ON ON ON ON ON ON ON ON ON


Code Research Project Descriptions
BME-02 Title: Precision Immunotherapy for Cancer Treatment
Primary mentor: Arjun Rao
Faculty advisor: Prof. David Haussler
Location: Other
Number of interns: 2

Project description: Cancer is a generic term used to describe a group of diseases characterized by uncontrolled cell growth in the body. It is one of the leading causes of human deaths (8.2 million casualties in 2012 — World Health Organization). The standard of care to treat cancers involves chemo- or radio-therapies. Both these methods are extremely effective in their cell-killing potential; however, they are also extremely toxic to healthy normal cells in the vicinity of the tumor. The immune system is geared to protect the body from infection. Tumors develop ways to inhibit the immune system and the body is unable to fight them off by itself. The mentor’s research involves looking for ways to boost the immune reaction to a tumor in an attempt to provide a non-toxic therapy for cancer. (All work will be computational; the primary mentor will remotely/virtually supervise the project.)

Tasks: The SIP interns will have to be very comfortable with working as an independent group on the project. The tasks conducted during the internship will include: (1) studying T-Cell targetable mutations and identify context in the mutations with respect to haplotypes; (2) implementing a python module to classify new events as being in accordance with a given context or not; and (3) integrating the module into the mentor's group's larger computational workflow.

Required skills for interns prior to acceptance: Computer programming; statistical data analysis
Skills intern(s) will acquire/hone: Computer programming; statistical data analysis
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: ON ON ON ON ON ON ON ON ON ON

Only out-of-area applicants will be considered for this virtually-mentored project.
Code Research Project Descriptions
BME-03 Title: Identifying Driver Genes of the Alternative Lengthening of Telomeres
Primary mentor: David Haan
Faculty advisor: Prof. Josh Stuart
Location: UCSC Main Campus
Number of interns: 2

Project description: Telomeres are located at the ends of chromosomes and regulate cell division. One hallmark of cancer cells is their ability to extend their telomeres and multiply indefinitely creating large tumors. Cancer cells extend their telomeres using two methods, an overexpression of the enzyme telomerase or a method called alternative lengthening of telomeres (ALT). In this project, the mentor and the SIP interns will computationally identify new driver genes of the alternative lengthening of telomeres which may become therapeutic opportunities to treat cancer.

Tasks: The SIP interns will download, wrangle, and analyze genomic data from the Cancer Genome Atlas, a collection of genomic data from about 20,000 tumors. The genomic data include, but is not limited to: DNA mutation, RNA expression, protein expression, telomere length, and methylation data. The interns can choose to work either in the programming language Python or R and will learn basic statistical analysis.  

URL: https://sysbiowiki.soe.ucsc.edu/
Required skills for interns prior to acceptance: Computer programming
Skills intern(s) will acquire/hone: Computer programming; statistical data analysis
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: ON ON ON ON ON ON REM ON ON ON


Code Research Project Descriptions
BME-04 Title: Contributing to a Single Cell RNASeq Pipeline
Primary mentor: Trevor Pesout
Faculty advisor: Prof. Benedict Paten
Location: UCSC Main Campus
Number of interns: 2

Project description: The mentor's research group is building a genomics pipeline for the analysis of Single Cell RNASeq data. The pipeline quantifies the abundance of genes and gene isoforms in the RNA found in single cells. The project is still in its infancy, so the precise pre-processing and post-processing of the data is to be determined. It will likely involve some modification and pruning of incoming sequence data (pre-processing), and some graphical representation of the output (post-processing).

Tasks: The SIP interns should have some experience with programming (light experience is fine). All the coding for this project will be in Python. The mentor has two goals for the SIP interns: (1) Find and classify Single Cell RNASeq data. This will involve reading papers and finding data sources. Classification will involve the documentation of the sequencing technologies used to to generate the data. (2) Verification of the pipeline. This will involve writing tests to see that correct output is produced from specific inputs. There may be more tasks that the interns can help with as the pipeline becomes more fleshed out, but for now these are the mentor's goals for the interns.

Required skills for interns prior to acceptance: Computer programming
Skills intern(s) will acquire/hone: Computer programming
Program Week Number: 1 2 3 4 5 6 7 8 9 10
Mentor's availability: ON ON OFF ON ON ON ON ON ON ON