--- /dev/null
+
+
+# Research Objectives
+
+## Uncovering genetic causes of diseases using a multidisciplinary bioinformatics-driven approach
+
+
+
+My research focuses on designing and using bioinformatics techniques
+to identify causes and mechanisms underlying human diseases such as
+Systemic Lupus Erythematosus, Glioblastoma Multiforme, and
+Arteriovenous Malformations followed be designing appropriate
+diagnostics and treatment methods. Once identified, I work with
+collaborators to verify the bioinformatics-discovered mechanisms
+utilizing *in silico*, *in vitro*, and *in vivo* techniques, and
+develop therapeutic and diagnostic techniques to identify and treat
+the underlying human disorder. Cell-culture-based methods are utilized
+as the first step in designing multi-target treatments, followed by
+appropriate animal models..
+
+# Unique Qualifications
+
+## Straddling Biology, Computer Science, and Statistics
+
+In addition to being a cellular and molecular biologist, I have
+extensive experience in algorithm design, computer programming, and
+statistics. The combination of these areas enables me to handle
+biological problems which involve large numbers of samples and data
+and require statistical analysis which can address confounders which
+are often present in non-laboratory settings. It also gives me a
+unique perspective which enables me to design novel methods to analyze
+and interpret large amounts of data.
+
+## Multidisciplinary approach
+
+I have published in multiple disciplines, including membrane
+biophysics, bioinformatics, genetics, and cellular biology. My
+experiences in these fields and my experiences while transitioning
+fields has allowed me to apply unique insights garnered from my
+previous work to new topics leading to novel approaches and
+breakthrough discoveries.
+
+# Previous Research Projects
+
+
+
+## Genetic Basis of System Lupus Erythematosus (SLE)
+
+I developed novel bioinformatic methods which increase
+
+
+likelihood of identifying reproducible genetic associations using
+prior knowledge from publicly available databases and expert
+information \cite{Armstrong2008:function2gene}. Using these methods, I
+was able to identify genes previously unassociated with SLE in a
+trio-based study \cite{Jacob2007:ar_lupus}. These genes were then
+replicated in a larger case-control study which was funded by the NIH
+on the basis of the original findings
+\cite{Jacob2009:sle_irak1,Armstrong2009:sle_gi}. Among other findings,
+this larger study identified a missense allele in NCF2 (H389Q,
+rs17849502) which was associated with SLE. Collaborative work
+indicated that H389Q altered the binding energy of NCF2 with VAV1
+using docking simulations, and in vitro experiments confirmed that
+H389Q altered NADPH oxidase function \cite{Jacob2012:sle_ncf2}, thus
+identifying it as a causative SLE mutation.
+
+## Cancer Stem Cells in Glioblastoma
+
+Glioblastoma is a almost invariably fatal form of brain cancerwhich is
+diagnosed in \(\approx\) 9,000 people in the US annually. It is typified
+by high levels of chemotherapeutic-resistant recurrences, some of
+which is likely caused by cancer stem cells which are insensitive to
+many chemotherapeutic agents. In collaboration with Florence Hoffman
+at USC, I have classified glioblastoma-derived cancer stem cells and
+cancer cell lines into distinct classes using gene microarrays and
+various clustering approaches, which will enable the design of a
+class-specific treatment of this devastating disease.
+
+## Regulatory pathways underlying cranial arteriovenous malformations
+
+The mechanisms underlying the formation of arteriovenous
+malformations(AVMs) which
+occur in the brain are unknown. Using gene microarrays, qtPCR, and *in
+vitro* experiments on primary human endothelial cells cultured from
+resected AVMs, I indentified multiple gene regulation pathways, many
+of them novel, including the Id1/Thsb1 inhibitory pathway. Additional
+experiments indicated that the *in vitro* pathology of endothelial
+cells could be partially rescued using extracellular Thsb1
+\cite{Stapleton2011:thbs1}.
+
+# Future research directions
+
+## Identification of causal mutations in SLE
+
+While many regions and SNPs which are associated with SLE have been
+identified, few of those regions have identified causal alleles with
+known function. Furthermore, even for regions with identified causal
+alleles, no systematic searches have been performed to identify
+additional causal regions. Continuing my existing collaboration with
+Chaim O. Jacob, I will rectify this by
+
+1. Deep sequencing the associated regions in 500 lupus cases and 1000 controls
+
+2. Identifying which newly found variants are associated with SLE
+
+3. Selecting variants with a high likelihood of producing functional variants
+
+4. Verifying biological relevance of variants by *in vitro* study
+
+5. Verifying functional relevance in human subjects
+
+## Developing analysis tools for massive amounts of sequencing data
+
+The ability to cheaply and rapidly sequence large numbers of samples
+has massively increased the amount of data processing required by
+researchers. Compounding this increase in data, most existing tools
+have not been designed to take full advantage of the current advances
+in computer architecture, which parallel solutions to problems which
+can be run on architectures with vastly differing computational
+abilities (such as GPUs).
+
+To resolve this, I am in the process of actively developing new open
+source tools which are capable of running on massively parallel
+architectures using both multiple computers (openMPI) and multiple
+GPUs on the same computer (Nvidia's CUDA) to
+
+1. Develop an open source massively parallel imputation method which
+ can combine existing GWAS results with new deep sequencing
+ and genetic profiling results.
+
+2. Extend same tools to call SNPs both incrementally and in parallel.
+
+I am currently working on extending samtools (an Open Source SNP
+calling suite) to support running on multiple computers.
+
+## Gut microbiota alteration in SLE
+
+Many autoimmune disorders are known to be affected by gut microbiota.
+Preliminary evidence suggests that mice which develop SLE have
+differences in gut microbiota from mice which do not develop SLE,
+which suggests that SLE severity may also be affected by differences
+in human gut microbiota. I am currently developing novel methods to
+
+1. Determine which gut microbiota differ between mice with and
+ without SLE and using 16S sequencing
+
+2. Determine which gut microbiota differ between humans with and
+ without SLE using 16S sequencing, given #1.
+
+## Continuous, incremental analysis
+
+Just as science requires continuous testing of hypotheses,
+bioinformatics is slowly moving towards continuous incremental
+analysis of data. Most current tools use iterative analysis, where
+analyses must be completely re-run with each new piece of data that is
+obtained. When the amount of data remains small relative to the
+overall computing power available, this is a feasible approach.
+However, as the amount of data increases, it stops being feasible to
+completely reanalyze data as new data is obtained, and incremental
+analysis approaches are necessary. I will be working to extend
+existing analysis pipelines to handle the incremental analysis of
+data.
+
+# Research Funding
+
+## Funding Opportunities
+
+I anticipate obtaining funding from the following sources to pursue
+the research goals outlined previously:
+
+1. National Institute of Health
+
+ 1. [Research Project Grant (RO1)](http://grants.nih.gov/grants/guide/pa-files/PA-13-302.html) (NHGRI, NIAID, BISTI)
+
+ 2. [NLM Career Development Award in Biomedical Informatics (K01)](http://grants.nih.gov/grants/guide/pa-files/PAR-13-284.html)
+
+ 3. [Continued Development and Maintenance of Software (R01)](http://grants.nih.gov/grants/guide/pa-files/PAR-11-028.html) (extending existing biofinformatics software)
+
+2. Alliance for Lupus Research
+
+ 1. [Target Identification in Lupus](http://www.lupusresearch.org/news-and-events/press-releases/til.html)
+
+3. Institution specific funding
+
+## Track Record of Funding
+
+The projects that I am proposing have a strong track record of being
+funded by both the NIH and the Alliance for Lupus Research.
+
+# Wider impact of research agenda
+
+
+My research will identify genetic variants and pathways underlying SLE
+and other important human diseases, leading to better methodologies
+for both the diagnosis and treatment of those diseases, and resulting
+in significant decreases is patient morbidity and mortality.
+Secondarily, the tools that I develop to effect this work will enable
+researchers in other fields to more rapidly and cheaply identify
+relevant factors for economically and environmentally important
+phenotypes, such as pathogen-resistance in crops or
+disease-susceptibility in thylocenes. Furthermore, as all of my tools
+will be released under Open Source licenses, external researchers will
+be able to build upon and improve my tools without being forced to
+reinvent them.
+
+
+\newpage
+
+\printbibliography
+<div id="footnotes">
+<h2 class="footnotes">Footnotes: </h2>
+<div id="text-footnotes">
+
+<div class="footdef"><sup><a id="fn.1" name="fn.1" class="footnum" href="#fnr.1">1</a></sup> <p>Only 4% of patients survive to 5 years after diagnosis</p></div>
+
+<div class="footdef"><sup><a id="fn.2" name="fn.2" class="footnum" href="#fnr.2">2</a></sup> <p>Direct artery to vein connection without an
+intervening capilary bed; leads to high pressure arterial flow in
+venous tissue and can lead to hemmorrhage and death.</p></div>
+
+<div class="footdef"><sup><a id="fn.3" name="fn.3" class="footnum" href="#fnr.3">3</a></sup> <p>and extending existing open source tools where they
+exist</p></div>
+
+
+</div>
+</div>
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projects / don.git / blobdiff