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Opportunity: Entry-level BIOINFORMATICS position--Genome Campus, Cambridge, (UK)
Submitted by Damian Counsell; posted on Monday, February 02, 2004 (1 comment)
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Email: shwetha82@gmail.com
SKILLS
Design: UML, Rational Rose
Computer Languages: C, C++, HTML, Java Script, SQL, Assembly Language, Perl
Web designing skills: Flash, Photoshop, Dreamweaver
Databases: Oracle 8.0, MS Access
Operating Systems: UNIX, Windows 98/NT/2000/XP
Software Packages: MS Office, Matlab 6.5, Maple
Statistical Software: SAS
EDUCATION
M.S. Computational Biology Expected: May 2006
New Jersey Institute of Technology, Newark, NJ
B.S. Computer Science and Math minor January 2005
George Mason University, Fairfax, VA
A Levels in Chemistry and Physics March 2000
Cambridge High School, Dubai, U.A.E
PROJECTS
Current Projects:
Using various techniques such as microarray-based expression profiling, to detect regulatory regions such as enhancers and suppressors in non-coding DNA.
Previous Projects:
Database: Extracted data from the National Center for Biotechnology Information (NCBI) website and used this data to build a database populating it with species information about the Avian infectious bronchitis virus (IBV). Used Oracle 8.0 as the platform for the database, and querying was done using SQL.
Alignment Software: Used ClustalW as a tool for aligning multiple sequences of ribonucleases. Thoroughly tested all the parameters of the software and observed the changes in alignments as the parameters were varied.
SQL Server: Worked on the development of the Call Management System that allowed the employees to report technical problems. Emails are dispatched to the respective people. If the employee is dissatisfied with the tech support provided, the problem could be escalated to a manager. Gained experience with ASP, VBScript, JavaScript and SQL Server.
Image processing: Attained proficiency with Matlab, including image generation, object recognition and picture alterations. Have written a program that recognizes music notes using image recognition. The music scanner scans in the notes, recognizes them and converts the images into the corresponding sounds.
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