Pavel-Kravchenko/Bioinformatics
Plugin Claude Code
213 bioinformatics skills for Claude Code — sequence analysis, NGS pipelines, single-cell, metagenomics, structural biology, cheminformatics, algorithms, and AI for science.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Build tries, Aho-Corasick, and suffix arrays with Kasai LCP to index DNA/text and match many patterns in one pass. Use for genome motif scanning, k-mer indexing, longest-repeat search, or BWA/FM-index groundwork.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Interpret AlphaFold2/AF3 pLDDT/PAE scores, fetch AlphaFold DB models by UniProt ID, and rank RFdiffusion/ProteinMPNN designs. Use when asked about pLDDT, PAE, AF2 vs AF3, AlphaFold DB fetch, or design triage.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Code DDPM/DDIM diffusion samplers, linear/cosine noise schedules, and DDRM inverse-problem solving (denoising, inpainting, super-resolution) in NumPy/PyTorch. Use for forward/reverse diffusion, score matching, or DDIM sampling.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Predict CAGE/DNase/ATAC/ChIP-seq tracks from raw DNA with Enformer/Borzoi, run in-silico mutagenesis (ISM), and score noncoding variant effects. Use when predicting enhancer/promoter activity from sequence, running ISM, scoring a noncoding SNP, or prioritizing GWAS/eQTL variants.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Choose Borzoi (RNA-seq coverage, 32bp) vs Epiformer (sequence+PhyloP, chromatin accessibility) vs AlphaGenome for epigenomic prediction. Use when picking a model for RNA-seq, ATAC/DNase, or variant-effect scoring.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Generate ESM2 protein embeddings (fair-esm/transformers) and predict structure with ESMFold. Use when embedding sequences, scoring mutations zero-shot, annotating protein function, or doing fast MSA-free structure prediction.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Tokenize scRNA-seq via Geneformer gene-rank or scGPT expression-bin encoding; annotate cell types, simulate in-silico knockouts. Use for foundation-model cell annotation, Geneformer/scGPT tokenization, or perturbation prediction.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Embed DNA with genomic foundation models (Nucleotide Transformer, HyenaDNA, Evo) via HuggingFace transformers; k-mer tokenize, probe promoter motifs. Use for DNA LLMs, genomic embeddings, or NT/HyenaDNA/Evo choice.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Fine-tune LLMs (Mistral/Llama/Qwen) with LoRA/QLoRA via HuggingFace PEFT, bitsandbytes NF4, and trl SFTTrainer. Use when doing LoRA/QLoRA fine-tuning, PEFT, instruction tuning, or SFTTrainer on limited GPU memory.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Track LLM fine-tuning runs with pandas/dataclasses + W&B/MLflow/TensorBoard: log per-epoch loss, run one-factor ablations (LoRA rank, LR), build a run registry. Use for hyperparameter ablations or picking an early-stop epoch.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Score splicing variant effects with SpliceAI/Pangolin delta scores (DSAG/DSAL/DSDG/DSDL) and AlphaGenome. Use when scoring a VCF for splice disruption, interpreting DS thresholds, or ranking cryptic splice-site variants.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Triage variant scores for structural follow-up; pick AlphaFold2 vs AlphaFold3 vs RoseTTAFold2 and gate results on pLDDT/PAE. Use for monomer/complex/ligand model choice or ranking variants by structural confidence.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
ColPali-style Vision RAG: embed rendered PDF pages, retrieve via ColBERT MaxSim, feed top-k pages to Qwen2-VL, no OCR. Use for PDF/document QA over figures and tables, multimodal retrieval, or Recall@k/MRR eval.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Score protein point mutations zero-shot with ESM-1v/ESM-2 masked-LM log-odds, ensembled, benchmarked on ProteinGym DMS. Use when predicting mutation effects, ranking missense variants, scoring VUS fitness with no labels.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Build an Aho-Corasick automaton (trie + BFS failure links) to find every pattern occurrence in one O(n+m+z) text pass. Use for restriction-site/primer/motif search or replacing per-pattern KMP/regex loops over many fixed patterns.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Implement a self-balancing AVL binary search tree in Python with rotation-based rebalancing (LL/RR/LR/RL) guaranteeing O(log n) insert/delete/search. Use when a user asks to build/implement an AVL tree, keep a sorted index balanced under insert/delete, explain balance factor or tree rotations, or avoid O(n)…
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Compute GCD/LCM via Euclid's algorithm, find roots with Newton's method, and count k-mers using dict/Counter vs O(n^2) list-scan. Use for GCD/LCM math, root-finding, k-mer counting, or Big-O complexity questions.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
BFS (queue) and DFS (stack/recursion) traversal in pure Python for shortest unweighted path, k-hop neighborhood, connected components, cycle detection on PPI/regulatory networks. Use for shortest path or cycle detection.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Implement/debug a binary search tree in Python: insert, search, delete (3 cases), successor/predecessor, inorder/level-order traversal. Use for BST coding, O(log n) vs O(n) degenerate cases, or choosing AVL/Red-Black.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Implement bubble/merge/shell/quicksort in Python; compare Big-O time/space/stability. Use when asked to sort an array, code a sort from scratch, explain quicksort complexity, or fix O(n^2) worst case on sorted input.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Derive Big O time/space complexity of loops and recursion via recurrence relations; simplify expressions, compare growth at scale. Use when asked the complexity of code, hunting O(n^2) loops, or worst-case cost.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Build a DFA transition table via the KMP prefix function, then scan text in O(n) with zero backtracking. Use when repeatedly searching one fixed pattern (motif, restriction site, primer) against many sequences or texts.
Pavel-Kravchenko/Bioinformatics
Skill Claude CodeCodex
Compute single-source shortest paths in a non-negative-weight graph with Dijkstra's algorithm (binary-heap priority queue, O((V+E) log V)); reconstruct paths and find network diameter. Use when finding shortest/cheapest/most-reliable path, routing, weighted PPI/interaction-network distance, or ranking paths by…