Suma Ravulapalli

Assisted principal investigators in conducting research at USAMRIID. Supported data analysis and modeling efforts in biosafety labs. Organized bioinformatics resources to enhance research efficiency.

Utilized R, Python, and Perl programming languages to develop efficient solutions.

Leveraged Python modules, including NumPy, Matplotlib, and SciPy, to conduct comprehensive scientific data analysis.

Utilized R packages including ggplot, dplyr, tidyr, shiny, plotly, and DESeq for comprehensive data wrangling and analysis.

Conducted in-depth data analysis and modeling through the application of statistical methods, including linear regression, cluster analysis, ANOVA, and t-tests.

Led the creation of a comprehensive pipeline for nanostring data analysis from conception to execution. Oversaw the development of R and Python scripts to effectively manage and structure data from high throughput experiments.

Designed and implemented a comprehensive data repository in MS Access to enhance data accessibility from assays and Nanostring experiments.

Compiled technical specification reports to document analytical findings from studies.

Delivered bioinformatic support for conferences, ensuring accurate statistical analysis and visual data representation for presentations.

Assisted in maintaining high-performance Supermicro X10QBL-4CT computer with Linux (Ubuntu OS). Supported installation of 32 TB of internal storage. Collaborated with PIs and lab technicians to convert data into a human-readable format using scripts. Utilized BCL2Fasta tool for data processing.

Collaborated with Nanopore tech support to implement software enhancements for Minion MK1C, ensuring optimal performance.

Achieved efficient data processing by developing a pipeline in R Shiny for epigenetic NGS datasets. Improved data accessibility by connecting to AccessDB for seamless export of epigenetic data files. Enhanced data visualization and wrangling capabilities through the Shiny application, resulting in improved analytical insights.

Spearheaded collaboration with ITMI bioinformatics team to develop a comprehensive pipeline for next-generation sequencing data analysis.

Managed development of two distinct pipelines, Agua and Bcbio NextGen, while directing integration of Perl and Python scripts.

Managed virtual environments using Docker, AWS EC2, and S3 instances, alongside GitHub for version control.

Spearheaded miRNA data analysis from preterm birth studies, utilizing Partek's PCA and cluster analysis tools to identify key differentially expressed genes.

Designed and implemented a MySQL database to streamline inventory management for vendor samples.

Enhanced analytical capabilities by leveraging Galaxy, Agilent SureCall, BaseSpace, and IonTorrent Workbench, validating results against in-house pipelines (Agua, BCBio NextGen).

Identified critical genetic variations associated with congenital heart defects (CHD) through collaborative research with the Department of Genetics and Inherited Diseases at Taiba University. Delivered insights into the role of non-synonymous SNPs (nsSNPs) in genes related to CHD, highlighting their potential to alter protein function and drug responses. Retrieved and screened nsSNPs from the dbSNP database using bioinformatics tools like SIFT and PolyPhen, pinpointing those with harmful implications. Conducted further analysis on protein stability and mutation occurrences of nsSNPs utilizing I-Mutant and PANTHER, contributing to a deeper understanding of genetic influences on CHD.

• Achieved successful integration of DNA/RNA-based regulatory elements, including promoters, 5' UTRs, and 3' UTRs, into targeted genomic locations.
• Identified genes with significant expression patterns through effective use of bioinformatics tools and methods.
• Leveraged bioinformatics software such as Vector NTI, Genomatix, and Genevestigator for precise promoter identification and transcription factor analysis.
• Established expertise in bioinformatics databases including Ensembl, Transcript, JASPAR, TFSearch, TRED, SCPD, and DBGET.
• Contributed to successful design and upload of 40,000 promoters and regulatory elements from various species into MOD database. Enhanced application functionality through innovative product design.
• Developed user manuals and guides for bioinformatics applications created by software department, improving user experience.
• Supported evaluation and acquisition of bioinformatics tools, leading to effective implementation. Conducted informative webinars to demonstrate capabilities of in-house and external bioinformatics applications.

1. Microarray Data Analysis
Ø 80Chip Microarray Data Analysis:
Conducted key functional genomics research in collaboration with CPDR basic science research
team in identifying genes specific to prostate cancer and their oncogenic pathways. Extensively
studied genes like in ERG, PSA, TMPRSS-ERG fusions, TMEPAI, NKX, c-MYC, SCD-1etc.
Work was based on microarray experiment that involved samples from 40 prostate cancer
patients. The samples were chosen based on the progression of cancer. Analyzed the data
obtained from microarray using following tools and applications:
• Normalization of microarray data: RMA express and R -statistical analysis software,
Chipinspector (Genomatix suit).
• Identification of biomarkers and highly expressed genes: R-statistical analysis software,
MS Excel 2007.
• Analysis of top 500 genes specific to prostate cancer: Used various statistical tests like pvalues,
Cumulative index, Correlation coefficient and graphically represented them in the
form of box plots, Heatmaps, bar graphs etc.
• Pathway analysis: Study the pathways associated between the highly expressed genes
using bibiliosphere (Genomatix), TMV (MultiExperiment viewer to generate heatmaps).
• SNP analysis of genes associated with chromosome 8q24 in relation to prostate cancer.
• Gained expertise in meta-analysis and concordance analysis, where several publications
and scientific documents were evaluated to identify the findings and interpret the results.
The supplemental data from similar experiments were used to perform meta-analysis.
Supported scientist and computational biologist in developing the bioinformatics
applications. Several user manuals and publications of different bioinformatics tools were
evaluated and presented to interpret the algorithm behind the applications.
• Attended the AACR and AUA conferences to present the analytical finding found from
microarray experiments.
2. Analysis of ERG siRna treated Vcap cells
TMPRSS2-ERG fusion in known inhibit cell growth in mice. A microarray experiment
was done where cells were treated with ERG siRNA to knock down the expression of
ERG. The genes that were expressed in absence of ERG were further studied to identify
their role in prostate cancer. Evaluated the gene promoters in ERG siRNA-treated cells
and investigation of gene expression signatures of human prostate tumors. Also, studied
the pathways associated with the expressed genes upon ERG knock down.
Publication: TMPRSS2-ERG fusion, a common genomic alteration in prostate cancer
activates C-MYC and abrogates prostate epithelial differentiation
3. Analysis of genes expressed in Curcumin treated Lncap cells:
Experiment involved treatment of LnCap cells with curcumin. Analyzed and identified
the top 50 up and down regulated genes upon treatment of prostate cancer cells with
curcumin.
Oracle base central repository:
Worked with software development team to build an oracle based repository system for
storage and retrieval of raw and analyzed microarray data. Coordinated with the scientists
and the database development team to discuss the format of the raw microarray data (e.g.:
cel files) and the analyzed microarray data (graphs and statistical test results). Played a
major role in collecting and organizing the data from various teams. Developed a
requirements document and submitted it to the software development team.