Computational Biology & Bioinformatics Research Lab
★ Advanced Research Lab · Grades 10–12
Do real cancer genomics research.
A premium, fully online research lab where high schoolers analyze real public cancer-genomics data — and leave with a portfolio that looks like a college student's.
🕖 One live 2-hour session / week · 8 weeks · 16 live hours + 1–2 hrs/week independent work
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Real research data — used responsibly. Students work with public, de-identified biomedical datasets from the NCI Genomic Data Commons (including TCGA). This is an educational research experience, not a clinical or diagnostic tool — a core skill is interpreting genomic results honestly and cautiously.
What makes it premium
College-level research — fully online, no wet lab.
This isn't a survey course. Students learn the actual workflow of a computational biologist: ask a research question, analyze real cancer-genomics data, visualize it, and defend an honest interpretation.
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Real cancer-genomics data
Mutation profiles and gene-expression data from the NCI GDC / TCGA — the same public datasets used in published cancer research.
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A guided research pipeline
From data → cleaning → analysis → visualization → interpretation, in Colab — with prepared files and helper code so the focus stays on the science.
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A real research portfolio
A research poster, a GitHub notebook, and a methods/results/conclusion abstract — the artifacts admissions and mentors take seriously.
NCI Genomic Data CommonsTCGA cancer cohortsNCBI / BLASTPython · Colabpandas · matplotlibVCF / FASTA / FASTQ
The 8-week curriculum
Genomic data science, end to end.
Eight weekly live sessions — 2 hours each (16 live hours total), plus 1–2 hours of independent work per week — building from genomics foundations to a complete, guided research capstone. All data and Colab notebooks provided.
Week 1 · Foundations
Genomics & Bioinformatics Bootcamp
DNA, genes, mutations, sequencing, cancer genomics — and how computational biologists ask research questions.
Week 2 · Tools
Command Line & Biological Databases
Colab, Bash basics, NCBI/BLAST, and sequence formats (FASTA / FASTQ).
Week 3 · Sequences
Alignment & Evolutionary Signals
Pairwise alignment, interpreting BLAST, comparing mutations, and phylogenetic thinking.
Week 4 · Variants
Variant Calling Concepts & VCF
FASTQ/SAM/BAM/VCF overview, quality scores, and variant filtering using prepared files.
Week 5 · Cancer Genomics
Working with TCGA / GDC
Clinical variables, mutation profiles, gene expression, and cancer-cohort comparison.
Week 6 · Visualization
Differential Expression & Plots
Expression matrices, PCA, heatmaps, volcano plots, and biomarker interpretation.
Week 7 · Capstone
Build Your Research Pipeline
A guided notebook: dataset → cleaning → analysis → visualization → interpretation.
Week 8 · Showcase
Research Poster + GitHub Portfolio
Final presentation, a GitHub notebook, and a research abstract (methods / results / conclusion).
What makes it real research
Real data demands real rigor.
Anyone can make a colorful plot. The skill that makes this college-level — and that mentors and admissions respect — is interpreting genomic data honestly, with its limits in full view.
Correlation isn't causeA gene linked to a tumor isn't proof it drives it. Students learn to state findings carefully.
Statistics & multiple testingTest thousands of genes and some "hits" appear by chance — so we correct and stay skeptical.
Reproducible workDocumented, shareable notebooks on GitHub — so the analysis can be checked and rerun.
Is your student ready?
Prerequisites
This is a rigorous program, so a little preparation matters. No wet-lab or prior bioinformatics experience is required — we teach the tools.
- Grades 10–12 Motivated 9th graders considered by application.
- Basic Python comfort Variables, loops, and functions (or an equivalent coding foundation). Everything runs in Google Colab.
- High-school biology Completed or currently taking Biology; comfort with DNA, genes, and cells.
- Curiosity & commitment ~8 weeks of live sessions plus independent capstone work.
Not quite there yet?
If your student needs support with coding foundations, we can recommend a short preparation path — such as our AI Agent Builder Lab — before the cohort begins.
What they leave with
A portfolio that opens doors.
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A research posterA presentable poster of an original genomic-data analysis.
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A GitHub portfolioA documented, reproducible analysis notebook to share with anyone.
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A path to mentorshipA research abstract — and a direct on-ramp to our 1:1 Research Program.
Apply for a seat
A premium research experience.
Tuition
$2,999 / student
8 weeks · live online · small cohort · application required
- 16 hours of live instruction — 8 weekly 2-hour sessions
- Plus 1–2 hours/week of guided independent work
- Real cancer-genomics data (NCI GDC / TCGA) & all Colab notebooks
- A guided capstone research pipeline
- Research poster + GitHub portfolio + research abstract
- Honest-interpretation & research-rigor coaching
- Priority on-ramp to the 1:1 Research Program
Seats are limited and admitted by application to keep cohorts small.
Questions parents ask
Good to know
Does my child need coding or bioinformatics experience?+
Basic Python comfort helps (variables, loops, functions) — and if your student doesn't have it, our AI Agent Builder Lab builds it first. No prior bioinformatics or wet-lab experience is needed; we teach the tools, and everything runs in Google Colab with prepared files and helper code.
Is this really college-level, or just a demo?+
It's the real workflow of a computational biologist, scaled for high schoolers: real public cancer-genomics data, a guided analysis pipeline, and an honest research interpretation. Students leave with a poster, a GitHub notebook, and an abstract — the same artifacts used in undergraduate research.
What data do students use — is it safe?+
Public, de-identified datasets from the NCI Genomic Data Commons, including TCGA cancer cohorts — the same sources used in published research. No private or patient-identifiable data is ever used, and the program is educational, not clinical or diagnostic.
How is it different from the AI in Medicine Lab?+
The Medicine Lab is a 4-week introduction to medical AI. This is a deeper, 8-week research lab focused on genomics and bioinformatics, culminating in an original research capstone — built for students aiming at competitive STEM and pre-med pathways.
What does the capstone lead to?+
A presentable research poster, a GitHub portfolio, and a research abstract — and a priority on-ramp into our 1:1 Research Program, where strong students can extend the project toward publication.
Turn curiosity about cancer into real research.
A premium, college-level genomics research experience — fully online, with a portfolio your student will actually use. Cohorts are small and admitted by application.