Bioinformatics Lead for Viral Immunology
Publicada el 2026-07-20
Descripción de la oferta
I am about to launch an entirely in-silico study on host–virus interactions and I’m still at the initial hypothesis-formulation stage. My goal is to move from a promising idea to publication-quality results that can support one or more scientific manuscripts. Here is what I need from you: • Shape a clear, testable hypothesis around host–virus interactions, grounded in current literature and biologically meaningful. • Mine and curate public transcriptomic datasets from GEO or ArrayExpress, standardise them, and build a harmonised expression matrix. R/Bioconductor or Python workflows are both fine, as long as the code is reproducible. • Perform differential expression analysis followed by a robust meta-analysis across studies to highlight consistent host signatures. • Translate the strongest signals into molecular-docking experiments that probe host and viral protein interactions; AutoDock Vina, PyMOL and similar tools are welcome if they suit your pipeline. • Deliver a concise results package that already looks and feels like manuscript figures and methods: cleaned data, scripts, statistical outputs, high-resolution plots, docking files and a short narrative of the findings. Acceptance will be based on: 1. A documented analysis pipeline that runs end-to-end on the provided datasets. 2. At least one prioritized hypothesis supported by statistically significant meta-analysis results (adjusted p-values, effect sizes, forest plots). 3. Docking scores and visualisations that clearly link back to the transcriptomic hits. 4. Figures and tables formatted for direct insertion into a journal submission. If you thrive on turning big public data into publishable biological insight, I’d love to see how you would approach this project and how soon we can move to drafting the manuscript.
Skills
Fuente original: freelancer