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Software Engineer Quality Assurance

Location:
Blacklick, OH, 43004
Salary:
60000
Posted:
July 10, 2013

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Resume:

Resume

Saraswathi Sundararajan, PhD

Cell: 1-515-***-****

Email: ab0224@r.postjobfree.com

Citizenship: Singapore;

Permanent Resident of USA (Green Card holder)

Current status:

Postdoctoral Research Associate, since Aug. 2011 to present. The Research Institute at

Nationwide Children’s Hospital,

Battelle Center for Mathematical Medicine, Columbus, OH 43205, USA

Education

1. PhD: Iowa State University, Bioinformatics and Computational Biology. Thesis: Protein

Secondary Structure Prediction using Neural Networks and Particle Swarm Optimization

2. M. Sc.: Nanyang Technological University, Singapore, Bioinformatics,

Thesis: Cancer Classification of Microarray data, using Machine Learning techniques

3. M.S.: Old Dominion University, Norfolk, VA, USA Computer Science

4. E-Commerce Engineering and Java Certification, UC Santa Cruz, USA.

5. BA (Mathematics and Economics), University of Delhi, India

6. CCNA certified and completed courses in CCNP and other Windows administration courses.

7. Additional courses in finance and management (ACCA, Singapore), Biology and Statistics

at Masters level.

Current Research: using machine learning in computational biology

Methods: Genetic Algorithms for feature selection; Neural networks and Particle Swarm

Optimization for classification using MATLAB, WEKA and other bioinformatics tools.

• Collaborator: Dr. Peter Houghton: Developing methodologies for molecular

therapy response classification of childhood cancers in collaboration with Prof. Peter

Houghton. Machine learning and advanced statistical algorithms are used to identify molecular

biomarkers that predict efficacy within the context of PPTP childhood cancer pop ulations. An

Integer-Coded Genetic Algorithm (ICGA) is used for feature selection, data reduction and

identification of biomarkers. A Neural Network based Extreme Learning Machine (ELM)

algorithm in combination with Particle Swarm Optimization (PSO) is used to classify and

differentiate between different classes of data. We are interested in discovering possible

mechanisms of resistance or sensitivity that could in turn be targets of a synergistic therapy or

candidate genes for molecular perturbation studies. We have de monstrated that a relatively small

gene-expression signature derived from in vitro sensitivity data (using Genetic Algorithm and

neural network) is able to accurately predict the overall in vivo response at a of 80-85%.

• Collaborator : Dr. William Smoyer and Dr. Richard Ransom : (one R01 grant

application) Paired blood samples (Rna_seq data) from patients with Nephrotic Syndro me are

used for IPA analysis, classification and prediction of steroid resistant vs. steroid sensitive

patients. Although the samples were very few, we were able to reduce the microarray data set

using Genetic algorithms and clustering (collaborative study) to reduce the features and perform

machine learning analysis using neural network. Various statistical analysis were also performed

on the data.

• Three projects in collaboration with Dr. Chotani Maqsood: (one R01 grant

application)

The first project relates to the examination of signature microRNAs and proteins in

o

human vascular smooth muscle cells utilizing chip/PCR analyses and 2D-proteomics

(fluorescence difference gel electrophoresis), respectively. This approach will potentially lead to

identification of physiologically relevant "vasculo-protective" players (or markers), conferring

"stress-tolerance" to cells during cooling or vascular injury. Our preliminary studies using our

machine learning and feature selection techniques have illustrated that there are marked

differences in data relating to male and female mice cells which was a new discovery (our

contribution) in this research. We are in the process of identifying bio-markers related to

this study. We are using IPA analysis to study the genes selected using our methods.

The second project relates to Role of the Ras-related small GTPase Rap1A in the

o

cardiovasculature Rap1 acts as a molecular switch, coupling extracellular stimulation to

intracellular signaling through the second messenger cyclic AMP. The key objective of this

project is to examine the role of this protein in cell attachment and cell survival in

vascular smooth muscle cells, and in cardiac myocyte function. We are processing the

miRNA data for this study and are working on identifying markers using our algorithms as

described above.

The third project relates to the investigation of the alpha-2A and 2C adrenergic

o

receptors. Several bioinformatics tools were used to analyze these proteins for predicting

secondary structure, disordered regions, binding regions and relative solvent accessibility.

I-Tasser was used to build protein models and nor mal mode analysis was used to for dynamic

analysis.

• Collaborative study with Dr. Octavio Ramilo and Dr. Maria Mejas: Microarray data on

Children’s infectious diseases were provided for several diseases such as flu, RSV, RV and

controls. We have processed these data using Neural networks and GA algorithms to identify

genes which might be responsible for these children’s diseases and have performed IPA

analysis for these genes. This study was done last year in 2012.

• Collaboration with Dr. Lucchesi and Dr. Vidu Garg and Dr. Loren Wold. Discussion

of projects are going on.

• Collaboration with Dr. Bakaletz on modeling of biofilm. On going talks.

• Collaboration with Dr. Petril of OSU and Dr. Bartlett of BCMM, NCH on

ADHD studies : On going talks.

• Collaboration with the perinatal group and Dr. Sarah Kleims : on-going talks.

Continuing Research from my PhD Studies

• Protein secondary structure prediction, Solvent Accessibility, Phosphorylation etc.

• Investigating use of protein physical and chemical properties in secondary structure

prediction (using data from AAindex database)

• Investigating use of Position Specific Residue Preferences (PSRP) of amino acids in

structure prediction

Professional Experience 2007 – 1995 (2006 to 2011, Bioinformatics MS and PhD)

• Visiting Researcher: Bioinforamtics Research Center: Machine Learning research,

School of Computer Engineering, Nanyang Technological University, Singapore. (July 2006 to

July 2007).

• Bioinformatics Research Center: Amrita University: I worked on Machine learning

(SVM) techniques, and parallel processing using grid computing and MPI for

bioinformatics applications. (Jan 2005– June. 2006)

• Business Consultant: at Amritha Viswa Vidya Peetham, Coimbatore, India: Project

Lead for development of financial modules and Enterprise Resource Planning Software

developed for Konkan Railway System. Later joined as Visiting Researcher at the Center for

Networking and Excellence, Amrita University, Coimbatore, India. (Jan 2004– Dec. 2004)

• Software Engineer and Technical writer, ValueLabs, Hyderabad, India : Test

development and quality assurance for mobile portal applications. for mobile portal

applications such as interactive TV and multimedia messaging. (June 2002 Web page and web

page application development – Dec. 2003)

• Software Engineer/Consultant, Techsoft Consultants, India and CA, USA 2001 – 2007

(Freelance Consultant, doing work undertaken as contract. Developed and administered

website for a major shipping company, Air7Seas. Developed test tracking application for a

multimedia software vendor, Margi Systems. Computer security consultant for VPN

Dynamics. Familiar with web technology, Microsoft Office packa ges, E-commerce engineering

and database concepts, Scripting and MySQL. Working knowledge of Unix and expert

knowledge in Windows environment. Knowledge of the following computer languages: Ada, C,

C++, Visual BASIC, Java, MATLAB, HTML, Perl and Python, which were used at various times

for software development and research activities. (Jan 2001 to June 2007)

• Visiting Researcher and Tutor: School of Computer Engineering, Nanyang

Technological University and National University of Singapore - Developed Finite Element

analysis modeling software package in C++. The ultimate objective of the software was to

simulate material behavior under extreme conditions. I implemented code migration of a

geometrical Finite Element Analysis package from ADA to C. Tutoring Business and

Accounting students in Information Technology (Jan. 1995 –2000 Dec.)

References available on request



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