STA/BST 226
Statistical Methods for Bioinformatics

Projects

You are strongly encouraged to work in a team (ideally 3 people per team) for you project. Before selecting teams and topics, it will be useful to get to know each other. Please fill in your experience (e.g. molecular biologist, statistician, or even something with more detail). Under "interests" you can also list some of the topics (from the course or other aspects of bioinformatics) that you are excited about.

Name	Experience	Interests
Li-Kuan Chen	biomedical engineering student ( bioinformatics )	Use workflow system to analyze microarray data with existing bioinformatics algorithms. The application would be on some kind of genome biology (One I am thinking is transription factor binding site prediction.)
Kevin Cheng
Wes Cline	Molecular toxicology, chemistry, etc.	All of this is over my head. Interested in working with a group that could help me learn, on a practical level, how to do/apply programming? to real problems.
Daniele Filiault	Third year grad student in Plant Biology. My research focuses on quantitative genetics/natural genetic variation/molecular evolution. Some statistics and R experience.	I'm game for working with Siobhan on problems in data analysis for tiling microarrays (see her entry below). We would love to have a statistician to work with us!
Yolanda Hagar	Third year grad student in Biostatistics	I am not sure what I am interested in yet. I have done a lot of programming in R and feel comfortable with most mathematical issues, however I don't have much bio experience so it would be nice to group together with someone in that area.
Jung Hyun	Second year grad student in Biostatistics	I would like to group with someone whose backgound is in Bio Science since my previous experience was mostly related to pure statistics.
Ci-Ren Jiang
Yun Jiang	1st year grad student in Biostatistics	I usually use R, matlab, and SAS to do data analysis. This is the first time for me to handle a project related to biology, DNA, microarrays, etc. I am interested in Li-Kuan, Marisano's projects, please email me at ykjiang@ucdavis.edu if either of you need a teammate. Thanks.
Do Yup Lee
Dan Li
Gabrielle Miller-Messner	2nd year grad student in Population Biology, background in molecular biology and population genetics	I'm interested in doing something with SNP genotyping data , or with patterns of polymorphism in Ciona(the sea squirt, 2 species have been sequenced). Kristin, Kristian, and Siobhan, I'm interested in your projects. Is there an email list I missed out on? gmessner@ucdavis.edu
Janel Owens
Russell Reagan	Molecular Biology background, some sequence analysis experience, can write short Perl scripts, UNIX text parsing techniques, limited microarray analysis experience	Interested in how proteins acquire new functions. Also interested in learning about Network Analysis.
Joe Russell
K. Stevens	Computer Science / Population Genetics	Project will be genome scale and probably involve graphical models, bayesian inference, genotyping microarray data, and population genetics.
Kristin Tennessen	biostats/comp sci/plant bio	My project will be comparing arabadopsis DNA and RNA microarrays
Greg Wall	Second year Biostatistics graduate student, with a background in Computer Science	I would like to work on a project where I could get some exposure to the biology and underlying concepts of genomics and population genetics.
Dan Wang	I am majored in Environmental Engineering, but I did some work in Biochemistry, Molecular technology, and analyzing phylogeny using ARB. My current project is about statistics	Interested in working with a group that composes of people with different background, so that we can understand the questions and solutions more deeply I have two possible projects in mind, using the data generated in my lab: 1) analyze population diversity from the RFLP pattern 2) building phynogenetic tree for 16s rRNA from wastewater treatment system My email address is vdwang@ucdavis.edu If you are interested in these projects, please contact me.
Ian Wang
Marisano James	I have good programming skills and some knowledge of biology. My undergraduate major was Bioinformatics and Computational Biology. I interned at MPI for Marine Microbiology (Bremen, Germany). I wrote a Chaos Game Representation algorithm while I was there.	The split between prokaryotes and eukaryotes, managing complexity, the onset of sex, organization. Phylogeny.
Siobhan Braybrook	4th year Plant Biology grad student. I know a bunch about biology, and pretty much nothing about programing or stats- although I am a fast learner.	I work on tiling microarrays, and there is currently no real consensus on how to analyze the data. The basic stats they apply now is pretty much a joke. Anyone interested in messing around? I have some data.....Just throwing it out there.
Charlyn Suarez	I am currently working towards a MS in statistics, I have a BS in genetics, and I am comfortable programming in R and perl. I have some experience working with sequencing and microarray data.	I am interested in population genetics and working with microarray data.

Topics

The following are some examples of project topics. You can choose one of these if you need an idea. Or they might give you an idea of the flavor of things you could do. You should by no means feel limited by this list.

1. Implement or improve/extend a current implementation of an algorithm for a problem in bioinformatics (e.g. the HOPACH R package needs some efficiency improvements, a C program called phast needs to be implemented in R). Apply this algorithm to some data from a subject area you are interested in (and draw some conclusions).
   
2. Read a chapter from one of our texts that we did not cover in class (e.g. RNA: BAS 9-10, Multiple Alignment: BAS 6, Phylogeny: BAS 7-8, Other -omics: BCBS 5-6). Supplement this with a literature search for current publications on the topic. Compare several methods through simulations and on real data.
3. Develop a computer program to optimize a problem that comes up in the laboratory (e.g. which offspring to use in a breeding program to develop transgenic mice based on SNP genotyping array data).
   
4. Apply a bioinformatic technique to a new problem or new species (e.g. work with class auditor Alisha Holloway (Population Biology) to study accelerated evolution in fruit flies using a method developed by Katie Pollard to identify the fastest evolving regions of the human genome).
   
5. Study the functions and expression patterns of genes identified by Katie Pollard and UCSF graduate student David Williamson as having regulatory regions that are different between chimp and human.
   
6. Develop a classification method to predict new genome sequences with a particular funciton (e.g. new RNA genes, new regulatory sequences). This project could focus on the ENCODE regions of the human genome (1% of the genome that is now very well annotated).
   
7. Start with a scientific problem and see if you can formulate it as a graphical model (e.g. HMM of some kind). Derive and implement (in code) the algorithms for estimating model parameters and evaluating the likelihood of an observed data set. If it makes sense, you could also figure out how to identify the most likely path through the graphical model (like the Verterbi path in an HMM).