Claude Skills by Pavel-Kravchenko

Tries, Aho-Corasick multi-pattern matching, suffix arrays with LCP, and suffix trees for genome indexing

AlphaFold2/3 architecture, confidence metrics (pLDDT/PAE), structure fetching, and protein design ranking workflows

Score matching, noise schedules, DDIM sampling, and DDRM inverse problems for diffusion generative models

Enformer architecture for regulatory prediction from DNA, in-silico mutagenesis (ISM), and variant prioritization

Borzoi vs Epiformer model selection for RNA-seq coverage vs chromatin accessibility prediction

ESM2 Embeddings and ESMFold with NumPy

Geneformer and scGPT for Single-Cell Modeling

Genomic Foundation Models: Nucleotide Transformers, HyenaDNA, and Evo with NumPy

LLM fine-tuning with HuggingFace Transformers — LoRA math, QLoRA 4-bit NF4 quantization, chat templates, SFTTrainer workflow.

Module T5-01B: LLM Training Systems (Tracking, Epochs, and Ablations) with Pandas

Splicing Models: SpliceAI and AlphaGenome with NumPy

From DNA Variants to Protein Structure: AlphaFold2, AlphaFold3, RoseTTAFold with NumPy

Module T5-02: Vision RAG with NumPy

Zero-Shot Mutation Effect Prediction with NumPy

Multi-pattern string matching in O(n + m + z) via a trie augmented with KMP-style failure links.

Self-balancing BST (Adelson-Velsky & Landis, 1962) guaranteeing O(log n) operations via rotation-based rebalancing.

Foundational algorithms — Euclidean GCD, Newton's method for cube root — with complexity analysis and clean implementations.

Graph Traversals: BFS and DFS with Matplotlib

BST operations, complexity, and a clean implementation with parent pointers supporting all standard operations.

Comparison-based sorting algorithms — bubble, merge, shell, quicksort — with complexity tables and implementation patterns.

Big O notation, complexity classes, space vs time trade-offs, and complexity analysis rules.

DFA-based exact pattern matching: O(m|Σ|) build via prefix function, O(n) search with no backtracking.

Dijkstra's Algorithm: Shortest Paths in Weighted Graphs

Dynamic arrays: amortized O(1) append via doubling, O(n) insert/delete, and Python list internals.

Graph representations — adjacency matrix, adjacency list, edge list — with complexity tables, implementation patterns, and biological network use cases.

Hash tables (chaining vs open addressing) and Bloom filters: complexity, trade-offs, and implementation patterns.

Top-down DP with memoization — cache recursive subproblems for exponential-to-linear speedup, @lru_cache shortcut

KMP string matching — O(n+m) pattern search using failure function prefix table

Knapsack DP variants — 0/1, unbounded, subset sum with traceback and space optimization

Linear and binary search — implementations, variants (first/last occurrence), and when to use each

Counting sort, radix sort, bucket sort — O(n) non-comparison sorts that bypass the Omega(n log n) lower bound

Singly linked list — full implementation with head/tail pointers, insert/delete/search/reverse, complexity table

Minimum spanning trees — Kruskal's (Union-Find, O(E log E)) and Prim's (heap, O((V+E) log V)), MST clustering

Naive O(nm) brute-force string matching — sliding window baseline, when it's acceptable, motivation for KMP/Rabin-Karp

Rabin-Karp hash-based string matching — rolling hash for O(n+m) average, excels at multi-pattern search

Red-black tree — self-balancing BST with O(log n) operations, 5 invariants, insert fix-up with rotations and recoloring

Needleman-Wunsch global and Smith-Waterman local sequence alignment — DP table fill, traceback, scoring matrices

Stack (LIFO) and Queue (FIFO) — array and linked-list implementations, O(1) operations, common applications

Suffix arrays — space-efficient sorted suffix index, O(n log n) construction, O(m log n) pattern search

Suffix trees — compressed trie of all suffixes, O(m) pattern search, O(n) construction via Ukkonen's algorithm

Bottom-up DP with tabulation — edit distance, LCS, space optimization with rolling arrays

Topological sort — DFS and Kahn's BFS algorithms for DAG ordering, cycle detection, critical path analysis

Prefix tree for O(m) string insert/search and O(p+k) prefix queries; ideal for autocomplete and dictionary membership.

AlphaFold/ESMFold structure prediction and confidence interpretation.

ATAC-seq quality control and accessibility analysis.

Advanced NGS: genome assembly algorithms (OLC, de Bruijn graph), k-mer theory, assembler selection table, and SPAdes/Flye/hifiasm CLI usage.

Metagenomic assembly with MEGAHIT, contig binning with MetaBAT2, and MAG quality assessment with CheckM. Includes binning signals, multi-sample strategy, and MIMAG quality tiers.

Long-Read Assembly Structural Variants with NumPy

Bayesian statistics with PyMC: prior specification, MCMC sampling, posterior analysis, and hierarchical models for biological data. Use when applying Bayesian inference to experiments.

Quick reference for bioinformatics file formats — FASTA, FASTQ, SAM/BAM/CRAM, VCF, BED, GFF/GTF, BigWig, PDB, Newick — specs, coordinate systems, and parsing patterns.