All posts by bioinformatics

Alternative Isoform Use in Proliferating and Quiescent Cells

We are studying the difference between cells that are dividing and cells that have stopped dividing. We are interested in working with an undergraduate student with strong computer skills and an interest in bioinformatics to understand the changes in isoform expression upon cell cycle exit. The student will assist us with analysis of next generation sequencing data, identification of splicing variants and changes in isoform use, and text based analysis of sequence motifs surrounding differentially present 5’ UTRs, exons and 3’ UTRs.

Please contact Hilary Coller at hcoller@ucla.edu

 

Computational Integration of Genomic Data

Project start date: Summer 2015
Contact: Bogdan Pasaniuc, pasaniuc@ucla.edu
Recent advances in high throughput genomic technologies have allowed for the collection of massive OMICs data sets ranging from gene expression to genetic variation data. We seek a highly motivated and energetic student with strong expertise in programming to develop and implement new tools to extract meaningful information from large scale data. Experience in genetic, bioinformatics, statistics is not required.
Required expertise: Strong background in programming (C, C++, Java, Python)
Funding: Yes

Jawbone: sleep disruption in response to daylight savings time shift

Project start: Summer 2015
Project Contact: Chris Colwell, ccolwell@mednet.ucla.edu
Project Description: This project focuses on the analysis of large datasets obtained from activity bands.  Our partner Jawbone is making data available about sleep and activity cycle.  This data must be extracted and then analyzed.  The hypothesis is that the daylight savings time disrupts sleep and that this disruption is worse with age.  The first part of the project will take the form of an internship at Jawbone in San Francisco to extract the data.  The second part will be at UCLA where we will interpret the findings.

Identifying loci for regulation of RNA splicing in mice

Project Start Date: Winter 2015
Contact: Des Smith <DSmith@mednet.ucla.edu>
Project Description: We have obtained deep RNA sequencing data from a panel of inbred mouse strains. The genome of these strains is well characterized, allowing fine mapping of loci involved in regulating gene expression. The project is to identify loci involved in splice site selection. Required Experience: The more background in C, Perl and R, the better. Some knowledge of genetic mapping and splicing desirable.
Possibility of Funding : No

Fine mapping genes for drug action

Project Start Date: Winter 2015
Contact: Des Smith <DSmith@mednet.ucla.edu>
Project Description: Although a staggering array of drugs is available for disorders such as cancer and autoimmunity, much remains unknown about their genetic targets. The project repurposes the technology of radiation hybrid (RH) panels to identify genes for drug action. RH cells contain extra copies of randomly selected genes and offer the opportunity to pinpoint functional drug/gene interactions with high precision. The project involves analyzing the data from these RH mapping experiments to identify gene targets for drugs of medical relevance. Required Experience: The more background in C, Perl and R, the better. Some knowledge of genetic mapping and radiation hybrid mapping desirable.
Possibility of Funding : No

Analysis of Variant-specific Gene and Isoform Expression using RNA-seq Data

Project Start Date: Spring 2014 (as soon as possible)
Project Title: Analysis of Variant-specific Gene and Isoform Expression using RNA-seq Data
Project Contact: Paivi Pajukanta (ppajukanta@mednet.ucla.edu)

Project Description:
Current massive parallel sequencing technologies allow us to investigate human transcriptome for changes conferring the susceptibility to obesity and high serum cholesterol and triglyceride levels. We hypothesize that there are DNA sequence variants influencing allele-specific expression of near-by genes that in turn increases the risk of obesity, dyslipidemia, and cardiovascular disease. This project will develop and employ approaches elucidating these expression changes using human adipose RNA-seq data.

Required Experience: Experience with some programming language (C,
C++, Python, Java etc.), some background knowledge of high throughput
sequencing.

Possibility of Funding: Yes

Analysis of Large-Scale Epigenomic Data Sets

Project Start Date: Winter 2014
Project Title: Analysis of Large-Scale Epigenomic Data Sets
Project Contact: Jason Ernst jason.ernst@ucla.edu

Project Description:
Advances in sequencing technology has enabled unprecedented ability to experimentally map genome-wide epigenetic features such as histone modifications, DNA methylation, and regions of open chromatin in a large number of cell types and conditions. Potential projects include analysis and/or method development in the context of leveraging large-scale epigenomic datasets to address problems related to stem cell reprogramming, cancer progression, and neuropsychiatric diseases.

Required Experience: Experience with some programming language and knowledge of basic statistics and probability.

Possibility of Funding: Yes

Analysis of Single Nucleotide Variants in RNA-Seq Data

Project Start Date: Winter 2014
Project Title: Analysis of Single Nucleotide Variants in RNA-Seq Data
Project Contact: Xinshu (Grace) Xiao <gxxiao@ucla.edu>

Project Description:
Our lab handles a large amount of high-throughput sequencing data of different types from the ENCODE and other large projects. With these data, we routinely analyze gene expression, alternative splicing, expressed polymorphisms, RNA editing and protein-RNA interaction. This project will develop methods for analyzing RNA-Seq data and measuring expression of single nucleotide variants.

Required Experience: Experience with programming in Pyton, Perl, C, C++, or Java etc, some background knowledge of high throughput sequencing. Basic knowledge in biology will be a plus

Possibility of Funding : Yes

Population genetic simulations of natural selection in the human genome

Project Start Date: Winter/Spring 2014

Project title: Population genetic simulations of natural selection in the human genome

Project Contact: Kirk Lohmueller (klohmueller@ucla.edu)

Project Description: We are developing and applying mathematical models of how natural selection affects patterns of genetic variation across regions of the human genome. This particular project will involve performing population genetic simulations using existing software to 1) assess the accuracy of our theoretical predictions, and 2) help interpret signals seen in actual genetic variation data.

I am looking for a motivated and talented student to play a prominent role in this project.

Required Experience: Experience with running programs from the command line, shell scripting, using a cluster, writing programs/scripts in C/C++, Perl, or Python to parse large files, and using R. Some background on genetic variation is required. Interest in population genetics a major plus.

Possibility of funding: Yes, especially if working over the summer or for longer periods of time.

Integrative OMICs methods in neurodegenerative dementia

Project Start Date: Spring 2013
Project Title: Integrative OMICs methods in neurodegenerative dementia.
Project Contact: Giovanni Coppola <gcoppola@ucla.edu>

Project Description:

The long-term goal of our group is to advance our understanding of the genetic architecture of neuropsychiatric disorders. We have collected genetic, genomic (gene expression, methylation) imaging and phenotypic data in a large series of patients with neurodegenerative conditions, including Alzheimer’s Disease (AD) and Frontotemporal Dementia (FTD).

In collaboration with Dr. Horvath, biostatistician at UCLA, and Dr. Paul Thompson (Department of Neurology) we are developing network-based methods to integrate multiple layers of information, including genetic, genomic, epigenetic, and neuroimaging data.

Required Experience: Experience with some programming language (preferred: Python, Perl, R, Java etc.), some background knowledge of biology or genetics

Possibility of Funding : Yes