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A step closer to treating cancer - PHD SOP for Computational Data Enabled Science and Engineering


kk242 1 / 1 1  
Nov 28, 2016   #1
For many years now, Scientists have struggled to help medical practitioners treat their patients according to their symptoms and provided customized healthcare on a personal basis. However, how personal can medicine get? In 2003, researchers obtained a complete human genome from which the sequence and map of all genes in the human body can be used as a reference. With this development we are a step closer to treating cancer and other diseases.

Most cancer treatments engage in trial and error basis of treatment which puts so much of pain, and risk on the patient. I worked on a similar problem in my role as a research assistant in a project funded by the NIH ******* Clinical Translational Research Center. It was on the use of metabonomics for the early detection of ovarian cancer. We worked on the development of various multi-class modelling techniques like support vector machines, random forests, k nearest neighbours and partial least squares using RNA-seq data from XYZInstitute that helped estimate accurate sensitivity, specificity, and positive predictive values of the tumour and develop predictive models for cancer.

I have worked on DNA methylation, RNA expression, clinical patient data based on the Pancreatic Adenocarcinoma dataset through the cancer genome atlas (TCGA). The study which was a two-step analysis included a pilot analysis that used supervised statistical analysis to identify gene features or RNA transcripts which are differentially expressed between covariates of particular interest yielding statistical significance. A follow up analysis was performed, which yielded us significant genes and proved to be an important integration analysis of multiple cancer and tissue types, an important area for bioinformatics.

In cancer, every tumour its own unique genetic makeup. In cancer, every tumour its own unique genetic makeup. Genomic data is important to comprehensively treat a patient. Genome sequences can be put in cloud systems like Hadoop clusters unlike traditional Relational databases where there is a restriction on the input format. I like to work on data to make it timely, fresh and of high quality to be available at the right format and at the right place like a good course of treatment and not just focus on optimizing traditionally managed data.

In my graduate studies, under the Bioinformatics and Biostatistics program, I took Data Mining subjects that dealt with supervised and unsupervised methods of learning that helped shape my interest in Data Science. I worked on a dataset that analyzed the malignant and benign prostate tissues that provided insight into a gene expression signature for prostate cancer. The goal was to conduct several prediction algorithms including principal component regression, elastic nets, partial least squares on the samples containing gene expression profiling by array to accurately predict prostate cancer. It was based on variables like factors that included disease state, and genotype/phenotype variation.

I currently work on building probabilistic graphic models by constructing metabolic models of genes. It involves understanding the metabolic pathways and testing hypothesis using high throughput data from human reconstruction models. Here the metabolic network models are used to investigate genes significant to Alzheimer's disease. A generic constraint based model of cancer metabolism is used to help predict important genes. We incorporate Bayesian statistics for belief propagation and test for statistical significance.

These day, large amounts of data is being generated from devices that track a person's health. I plan to research extensively using big data in these forms and use them to solve significant risk factors. I like to help predict the possible outcomes in an experiment/course of treatment of a disease and thus help contribute in increasing the survival statistics of a patient. I hope to work towards improving healthcare analyzing practices by recognizing the weakness and leverage the strengths of various algorithm approaches. I think the Computational and Data-Enabled Science and Engineering program will help me in pursuing this goal of mine.

It interests me to learn and excel in a place that has a huge intertwining of cultures and knowledge. I believe that it helps me discover my place in research of curing diseases. I am deeply influenced by the work of Professor ABC at the Department of Biostatistics and I plan to work under her for tackling big data problems in bioscience by employing mathematical modeling.
ryan31 65 / 96 15  
Nov 28, 2016   #2
hai kk
I have some suggestions for you
hope it helps

With this development, << do not forget utilize comma we are a step closer ...

I think you should give a line in here >>> A follow- up analysis was performed,

... pathways and testing the hypothesis using high- throughput data from ...A generic constraint- based on model of cancer metabolism is ...

thanks
Holt  Educational Consultant - / 14,797 4780  
Nov 29, 2016   #3
Krithika, your SOP borders on becoming a lecture and research paper all in one. Your opening statement is nothing but a lecture that the reviewer has to endure rather than having the reviewer informed about your passion, skills, abilities, and desire to study this particular course for your PhD. While there are portions of your essay that apply to a proper PhD SOP, most of it just presents research material to the reviewer. That is not the kind of information you should present here. Let me break it down for you.

In the first paragraph, talk about yourself, how your interest in computer data enable science and engineering developed, and why you would like to pursue this line of study. Don't make this your autobiography. Just compress all of the information into a single 10 sentence paragraph at the most. It need not be overly long nor descriptive.

As with any higher academic application essay, you are required to summarize both your college education and your masters degree field of study in the second paragraph.Specifically mention your thesis work by title, responsibilities, and outcome of the research. Do not enumerate the classes that you took in college and the masters course as proof of your ability to perform well in the PhD course of your choice. Your thesis paper and subsequent course of actions while developing the paper will be more than capable of doing that for you.

Now, you have actually presented some work on your part that relates to this interest of yours. So I suggest that you improve that presentation in order to show the logical progression to PhD studies on your professional part. Make sure that you highlight the reason why you feel that the current knowledge that you have is no longer sufficient for the future work you want to accomplish.

Finally, make sure that you have indicated enough of your academic interests to prove that you have an actual dissertation project in mind that will cover the proper scope of discipline within the PhD course. This means you have to present a summary of your dissertation proposal for consideration. Mention specific professors from the university or classes that will help you advance in your research. This will show that you are not only familiar with the demands of a PhD course, but that you actually will complete the program because you will work towards gaining experience from notable people at the university. The interactive experience should make the reviewer believe that you are beyond excited to start working on the program at their university.

I believe that by better focusing the content of your paper, and revising majority of the content, your work will have a better chance of being considered for a slot as a PhD student. Good luck with your application.
OP kk242 1 / 1 1  
Nov 29, 2016   #4
@Holt,
Thank you so much. That was very helpful and clear as crystal. I am working on it to improve it along the lines you mentioned. Thanks for taking the time to read it.


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