5 Paths, 122 Lessons
A comprehensive curriculum spanning Python programming, sequence analysis, tabular data manipulation, and clinical variant notation. Modules may be completed sequentially or referenced individually as needed.
Fundamental Python syntax, core data structures, and foundational conceptual principles required for computational biology.
Progress0%Python Exception Traceback·Interpreter standard error on unbound identifier Traceback (most recent call last): File "<cell>", line 3, in <module> print(len(seq)) NameError: name 'seq' is not definedNumerical computation, tabular data processing, and scientific visualization using NumPy, pandas, Matplotlib, and Seaborn.
Progress0%Gene Expression Count Matrix·Tab-separated expression data (counts.tsv) gene control_1 control_2 treated_1 treated_2 TP53 1204 1150 2310 2402 EGFR 3021 2988 1502 1477 MYC 150 143 900 945Sequence analysis, record manipulation, pairwise alignment, and standard biological file parsing with Biopython.
Progress0%FASTA Sequence Header and Record·Reference transcript sequence (sample.fasta) >NM_000546.6 TP53 transcript variant 1 (excerpt) ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCA GACCTATGGAAACTACTTCCTGAAAACAACGTTCTGTCCCCCTTGCCGTCCCAAGCAATGStandardized variant notation, HGVS nomenclature parsing, coordinate projection, and clinical VCF processing pipelines.
Progress0%Variant Call Format (VCF) Record·Genomic coordinates against GRCh38 (variants.vcf) #CHROM POS ID REF ALT QUAL FILTER INFO chr17 7676154 . G A 99.0 PASS DP=120;AF=0.51 chr17 43093220 rs80357906 C T 45.2 PASS DP=88;AF=0.49Comprehensive, end-to-end computational biology pipelines evaluated across complete execution workflows.
Progress0%ModulesClinical Variant Analytical Report·Structured pipeline output format records=10 malformed=4 filtered=1 kept=6 chr1:3 GCA G TP53 120 0.5100 deletion chr1:25 G GAAA BRCA1 88 0.4900 insertion summary: 6 variants in 3 genes, mean depth 81.8