Venkata Sanaboyana
Computational Structural Biologist, Bioinformatics Scientist, Data Scientist
Iowa City,IA
Summary
Meticulous computational biochemist accomplished in modeling biological systems, molecular simulations and analyzing complex information through software. Hands on experience in high-throughput analysis of AlphaFold2 predicted protein structures. Strives to stay updated with the latest innovations in the proteomics as well as genomics research. Proven ability to analyze complex datasets, with strong skills in research and programming methodologies.
Overview
9
9
years of professional experience
10
10
years of post-secondary education
Work History
Data Science Intern
InfoCepts
McLean, VA
08.2022 - Current
- Collaborate and work with Business Consulting competency on organization priorities
(including Data Science COE, Business Solutions for Pharma/Healthcare) - Work with our Advisory team to develop POV/POC and demonstrate thought leadership in
D&A space (including data science, healthcare, retail, media & other industry) - Skills: R, Python, Machine learning, Snowflake, SQL and Data modeling.
PhD Graduate Assistant
University of Iowa
Iowa City, IA
08.2018 - 08.2022
- Refinement of the neural network-based signal peptide prediction methods using structural information from the DeepMind’s AlphaFold2 proteome database
- High throughput predictions of signal peptides of hundreds of thousands of protein sequences on HPC clusters at the University of Iowa
- Building training and validation datasets
- Large scale analysis of the 560,000 protein structures predicted by AlphaFold2 Version2.
- Gathered, reviewed and summarized literature from scientific journals such as SciFinder and PubMed and produced graphs and other scientific calculations using MS Excel and R.
Masters Student
University of Iowa
Iowa City, IA
08.2016 - 08.2018
- Progress towards molecular simulations of plasmid segregation system in E. coli
- Computational design and implementation of coarse-grained models of protein filaments (long chain of protein monomers)
- Modeling of protein-protein interactions
- Molecular simulations of filament formation in E. coli: simulation system includes hundreds of thousands of coarse-grained protein models
- Data analysis using Python, Perl and Shell programming languages
Research Assistant
National Center for Biological Sciences, NCBS
Bangalore, India
05.2013 - 08.2016
- Exploring the effects of sparse restraints on protein structure prediction (Mandalaparthy, Sanaboyana, Rafalia, & Gosavi, 2018)
- Implementation of structure-based models (SBMs) or go models to study protein folding o Data analysis in Perl and MATLAB
- Characterized protein sequences using UV- Visible, CD, Fluorescence, and NMR spectroscopies.
- Gathered, arranged and corrected research data to create representative graphs and charts highlighting results for presentations.
Education
Ph.D - Biochemistry
University of Iowa
08.2018 - 07.2022
MS - Biochemistry
University of Iowa
Iowa City, IA 08.2016 - 07.2018
B.Tech - Biotechnology
Indian Institute of Technology (IIT)
Guwahati 07.2008 - 05.2012
Skills
Proteomics: molecular modeling, protein structure prediction
Additional Information
- Qualified for Council of Scientific and Industrial Research (CSIR) fellowship with an All India Rank (AIR) of 82.
- Qualified for GATE - Biotechnology with 98.8 Percentile / AIR of 352.
- Achieved merit cum means (MCM) fellowship for the entire undergraduate studies at IIT Guwahati. 2008
Publications
PUBLICATIONS
Mandalaparthy, V., Sanaboyana, V. R., Rafalia, H., & Gosavi, S. (2018). Exploring the effects of sparse restraints on protein structure prediction. Proteins-Structure Function and Bioinformatics, 86(2), 248-262. doi:10.1002/prot.25438
Sanaboyana. V. R., Elcock A.H. (2018). Progress towards molecular simulations of plasmid segregation system in E. coli [University of Iowa]. https://doi.org/10.17077/etd.a6nq41cg
Sanaboyana. V.R., Elcock. A. H. (2022). Improved identification of signal and transit peptides using proteome- wide predictions of protein structure with DeepMind’s Alphafold2. Journal of Molecular Biology, Manuscript under revision.
Sanaboyana. V.R., Elcock. A. H. (2022). Role of predicted protein contact maps in identifying signal peptides in bacteria. Journal of Molecular Biology, Manuscript under preparation.
References
REFERENCES
Dr. Adrian Elcock from University of Iowa.
adrian-elcock@uiowa.edu | 319 – 335 – 6643
Dr. Ernesto Fuentes from University of Iowa.
ernesto-fuentes@uiowa.edu | 319 – 353 – 4244
Dr. Michael Schnieders from University of Iowa.
michael-schnieders@uiowa.edu | 650 – 995 – 3526
Timeline
Data Science Intern
InfoCepts
08.2022 - Current
Ph.D - Biochemistry
University of Iowa
08.2018 - 07.2022
PhD Graduate Assistant
University of Iowa
08.2018 - 08.2022
MS - Biochemistry
University of Iowa
08.2016 - 07.2018
Masters Student
University of Iowa
08.2016 - 08.2018
Research Assistant
National Center for Biological Sciences, NCBS
05.2013 - 08.2016
B.Tech - Biotechnology
Indian Institute of Technology (IIT)
07.2008 - 05.2012
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