Guidance for GSOC,2016 framework to analyse gene function in cancer datasets,git hub based revision control of chromosomes

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Nikhil Yadala

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Mar 4, 2016, 8:49:13 PM3/4/16
to Genome Informatics-Google Summer of Code Group
Hi all,

     I am Nikhil Yadala pursuing 2nd year of Btech in CSE at IIT Guwahati. I am very much interested in application of machine learning in computational biology. Currently I am working on a research project which includes profiling multiple genes, from a given base gene set using deep learning.

           I have gone through the project list floated for Gsoc,2016, and I found the following projects very interesting.
         
                 
1)statistical framework to analyze gene function in multivariate cancer datasets.
                  2)Github-based revision control of synthetic chromosomes

      I dont have enough experience in R, but I am well versed with python, c++. I have already  taken courses in machine learning , cell biology, and currently i am attending a course on mathematical statistics. I have been developing a python to c++ translator too. I would be glad if any one over there shall guide me to get enough knowledge to get going with the project.
                                                
thanks,
Nikhil Yadala,
Btech- CSE.
 

Robin Haw

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Mar 4, 2016, 9:11:43 PM3/4/16
to genome-in...@googlegroups.com, eri...@berkeley.edu, juri.r...@utoronto.ca
Dear Nikhil,
Thank you for expressing an interest in the Open Genome Informatics group. I have cc’d Juri Reimand and , who will be mentoring this project and will have a better understanding of the project requirements than I.
Good luck with your application.
Regards
Robin Haw


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Nikhil Yadala

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Mar 7, 2016, 2:48:52 PM3/7/16
to Genome Informatics-Google Summer of Code Group, eri...@berkeley.edu, juri.r...@utoronto.ca
HI juri reimand,
               I have thought of the entire details of the project implementation and now, i have decided to contribute to    
                      
"statistical framework to analyze gene function in multivariate cancer datasets. "
Could you please tell me, if have to know any other things prior, so that, time would be saved during the summer. I am very much interested to  start the project even before the official GSOC starts.
                           thank you ,
Nikhil Yadala,
Btech-CSE.


On Saturday, March 5, 2016 at 7:41:43 AM UTC+5:30, rhaw wrote:
Dear Nikhil,
Thank you for expressing an interest in the Open Genome Informatics group. I have cc’d Juri Reimand and , who will be mentoring this project and will have a better understanding of the project requirements than I.
Good luck with your application.
Regards
Robin Haw


On Mar 4, 2016, at 02:16, Nikhil Yadala <nikhil...@gmail.com> wrote:

Hi all,

     I am Nikhil Yadala pursuing 2nd year of Btech in CSE at IIT Guwahati. I am very much interested in application of machine learning in computational biology. Currently I am working on a research project which includes profiling multiple genes, from a given base gene set using deep learning.

           I have gone through the project list floated for Gsoc,2016, and I found the following projects very interesting.
         
                 
1)statistical framework to analyze gene function in multivariate cancer datasets.
                  2)Github-based revision control of synthetic chromosomes

      I dont have enough experience in R, but I am well versed with python, c++. I have already  taken courses in machine learning , cell biology, and currently i am attending a course on mathematical statistics. I have been developing a python to c++ translator too. I would be glad if any one over there shall guide me to get enough knowledge to get going with the project.
                                                
thanks,
Nikhil Yadala,
Btech- CSE.
 

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rhaw

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Mar 7, 2016, 9:25:11 PM3/7/16
to Genome Informatics-Google Summer of Code Group, eri...@berkeley.edu
Dear Nikhil,
You could drop Eric Yao, the lead developer (cc'd) if you have any further questions. 
Good luck with your application.
Thanks,
Robin Haw
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