Claude Skills by Pavel-Kravchenko

Core Python for bioinformatics — types, bio-string manipulation (codons, reverse complement), functions, and file I/O for FASTA/GenBank

RNA-seq differential expression analysis and normalization workflows.

RNA-seq differential expression — DESeq2, edgeR, normalization strategies (RPKM/TPM/DESeq2 size factors), exploratory PCA, volcano plots, GSEA, STAR/Salmon/featureCounts pipelines

Single-cell RNA-seq analysis from count matrix to annotated cell types and trajectories.

Pattern matching algorithms — naive, KMP (failure function), Rabin-Karp (rolling hash), and DFA-based matching for sequence search

Bio.PDB parsing, distance/RMSD/TM-score, DSSP, Ramachandran, PWM/PROSITE, GO enrichment, KEGG REST API.

Viral genome assembly, intra-host variant calling, phylodynamics, and real-time surveillance.

Vision-language model inference patterns for scientific documents.