Summary
Archana Raja is a computational biologist with 11 years of experience applying genomics, gene prediction, and next-generation sequencing analysis to translational research. Based at Stanford School of Medicine, she designs and validates pipelines (including Snakemake) for CNV analysis, assembly validation of PacBio genomes, and visualization via genome browsers, bridging wet-lab goals and informatics implementation. Her toolkit spans Python, R/Bioconductor, Java, and practical QA/testing practices from earlier GenoViz/IGB work, enabling reproducible analyses and clear communication with biologists. Past roles at HHMI, Northwestern, and NC State highlight strengths in miRNA/mRNA-seq workflows, hybrid assembly strategies, and annotation of complex genomic features like segmental duplications. She combines hands-on pipeline engineering with an eye for visualization and user-facing tools, making large sequencing datasets actionable for investigators. Notably, her background includes both software QA for genome browsers and experimental primer design for draft genomes, reflecting a rare mix of software rigor and wet-lab awareness.
10 years of coding experience
2 years of employment as a software developer
MS, Bioinformatics, MS, Bioinformatics at University of North Carolina at Charlotte
B.Tech, Bioinformatics, B.Tech, Bioinformatics at Shanmugha Arts, Science, Technology and Research Academy