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pavel-kravchenko

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1. ▌
   Cheminformatics Drug Discovery · pavel-kravchenko

   Parse SMILES/SDF with RDKit, build ChEMBL QSAR models, dock ligands with AutoDock Vina, predict ADMET/Lipinski properties. Use for compound screening, Tanimoto similarity, Rule of Five filtering.
   0 installs
2. ▌
   Foundations Linux Fundamentals · pavel-kravchenko

   Linux CLI basics: cp/mv/rm, grep/awk/find, pipes, chmod, gzip/tar, wget/scp/rsync, ps/kill. Use when writing a bash pipeline, inspecting FASTA/FASTQ/BAM/BED/VCF on a server, or filtering lines with grep/awk.
   0 installs
3. ▌
   Python Bio Python Introduction · pavel-kravchenko

   Foundational Python for biology - count nucleotides, compute GC content, use f-strings/loops/functions, and set up biopython/pandas/numpy via pip/venv/conda. Use when a beginner asks how to start with Python for bioinformatics, write a first DNA-parsing script, calculate GC content from a raw string, or install BioPython/scanpy/pysam in a virtualenv or conda environment.
   0 installs
4. ▌
   Python Bio Regular Expressions · pavel-kravchenko

   Match DNA/RNA/protein patterns with Python re — ORFs, restriction sites, IUPAC primers, PROSITE motifs, FASTA headers. Use when finding start/stop codons, tandem repeats, or parsing headers/BLAST output with regex.
   0 installs
5. ▌
   AI Science LLM Training Systems · pavel-kravchenko

   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.
   0 installs
6. ▌
   Bio Applied Lc Ms Preprocessing · pavel-kravchenko

   Preprocess raw LC-MS mzML with XCMS centWave peak picking, obiwarp RT alignment, gap filling, PQN/QC normalization, adduct grouping. Use when building an XCMS pipeline or preprocessing untargeted metabolomics runs.
   0 installs
7. ▌
   Bio Applied Microbial Diversity · pavel-kravchenko

   Compute alpha/beta diversity (Shannon, Simpson, Bray-Curtis, UniFrac) from a 16S/ASV feature table with scikit-bio; PCoA ordination, PERMANOVA/ANOSIM. Use for microbiome diversity or community composition questions.
   0 installs
8. ▌
   Bio Applied Molecular Evolution · pavel-kravchenko

   Test Hardy-Weinberg equilibrium, simulate Wright-Fisher drift/selection, and compute dN/dS, Tajima's D, and Fst with NumPy/SciPy. Use for neutral theory, molecular clock divergence time, selection scans, or effective population size (Ne) questions.
   0 installs
9. ▌
   Bio Applied Population Genetics · pavel-kravchenko

   Test Hardy-Weinberg equilibrium, simulate Wright-Fisher drift/selection, and compute dN/dS, Tajima's D, Fst, LD with NumPy/SciPy. Use for allele-frequency, selection, or population-structure questions.
   0 installs
10. ▌
    Bio Applied Regulatory Analysis · pavel-kravchenko

    Scan DNA for promoter/regulatory elements: TATA box regex search, CpG island detection via GC%/observed-over-expected sliding windows, and PFM to PWM (log-odds) construction/scanning for TFBS. Use when locating a TSS, calling CpG islands, building a position weight matrix from aligned binding sites, or scanning a promoter with a JASPAR/TRANSFAC-style motif.
    0 installs
11. ▌
    Bio Applied Scrna Preprocessing · pavel-kravchenko

    Build AnnData from 10x MEX, compute scanpy QC (pct_counts_mt, n_genes_by_counts), MAD-filter cells, normalize/log1p, select HVGs. Use for scRNA-seq preprocessing, doublet/dying-cell filtering, or AnnData QC before clustering.
    0 installs
12. ▌
    Bio Applied Taxonomic Profiling · pavel-kravchenko

    Classify shotgun metagenome reads to species level with Kraken2, remove host reads with Bowtie2, and re-estimate abundance with Bracken. Use when doing metagenomics taxonomic profiling, Kraken2/Bracken, or host decontamination workflows.
    0 installs
13. ▌
    Bio Applied Trajectory Analysis · pavel-kravchenko

    Order scRNA-seq cells with diffusion pseudotime (scanpy sc.tl.dpt), PAGA graphs, and RNA velocity (scVelo) on spliced/unspliced counts. Use for pseudotime, root cell selection, or RNA velocity streamline plots.
    0 installs
14. ▌
    Bio Core Computational Genetics · pavel-kravchenko

    Translate DNA per-frame, score codon usage bias (RSCU/CAI), simulate restriction digests/ORFs, and test three-point-cross mapping and Hardy-Weinberg equilibrium. Use for CAI, virtual digests, crossover mapping, or HWE tests.
    0 installs
15. ▌
    Bio Core Nucleic Acid Structure · pavel-kravchenko

    Compute DNA helix geometry (A/B/Z-DNA), nearest-neighbor duplex free energy (SantaLucia), and RNA dot-bracket structure/Nussinov folding with Biopython. Use when analyzing helix groove geometry, oligo Tm/stability, or RNA stem-loop/hairpin structure.
    0 installs
16. ▌
    Foundations Character Encodings · pavel-kravchenko

    Fix UTF-8/Latin-1/CP1251 decode errors, strip BOM, repair mojibake, normalize CRLF endings, remove hidden Unicode in FASTA/GFF text. Use when hitting UnicodeDecodeError or garbled text from Windows/Excel exports.
    2 installs
17. ▌
    Foundations Git Version Control · pavel-kravchenko

    Version-control bioinformatics scripts with git init/add/commit/branch/merge/stash/tag and .gitignore for FASTQ/BAM/VCF. Use when setting up a repo, undoing a commit, or resolving a merge conflict.
    0 installs
18. ▌
    Bio Applied Cell Type Annotation · pavel-kravchenko

    Annotate scRNA-seq Leiden/Louvain clusters into cell types via canonical marker scoring, SingleR reference correlation, and CellTypist logistic-regression classification on an AnnData/SingleCellExperiment object. Use when doing cell type annotation, labeling clusters, scoring marker genes on a UMAP, running SingleR or CellTypist, or resolving ambiguous/NA-labeled clusters in PBMC or other scRNA-seq data.
    0 installs
19. ▌
    Bio Applied Cite Seq Integration · pavel-kravchenko

    Normalize CITE-seq ADT counts (CLR/DSB) and build WNN graphs joining RNA+protein or RNA+ATAC with muon/Seurat FindMultiModalNeighbors. Use for CITE-seq, 10x Multiome, or paired RNA+ADT/ATAC single-cell integration.
    0 installs
20. ▌
    Bio Applied Copy Number Analysis · pavel-kravchenko

    Call CNVs from binned read-depth: GC-bias normalization, circular binary segmentation (CBS), log2-ratio-to-CN-state calling, tumor-purity correction. Use for CNV/copy-number segmentation, log2 ratio analysis, or gain/deletion/amplification calls.
    0 installs
21. ▌
    Bio Applied Differential Binding · pavel-kravchenko

    Find ChIP-seq/ATAC-seq peaks that gain or lose signal between conditions using DiffBind (dba.count/dba.normalize/dba.analyze with DESeq2 or edgeR) on a consensus peak set, then annotate hits to genes/promoters with ChIPseeker annotatePeak. Use when comparing TF binding or histone marks across conditions, building volcano/MA plots from dba.report() output, or annotating differential peaks to nearest TSS/gene.
    0 installs
22. ▌
    Bio Applied Snp Calling Pipeline · pavel-kravchenko

    SNP calling pipeline: Trimmomatic trim, BWA-MEM2/HISAT2 align, samtools mpileup + bcftools call, ANNOVAR annotate (dbSNP, RefGene, 1000G, ClinVar). Use for FASTQ-to-VCF pipelines or ANNOVAR variant annotation.
    0 installs
23. ▌
    Bio Applied Variant Surveillance · pavel-kravchenko

    Assign SARS-CoV-2 Pango lineages with Pangolin/Nextclade and deconvolve wastewater into lineage fractions with Freyja (variants/demix). Use when doing variant surveillance, wastewater epidemiology, lineage tracking, or VOC/VOI classification.
    0 installs
24. ▌
    Bio Applied Functional Annotation · pavel-kravchenko

    Profile MetaCyc pathways/genes from metagenomes with HUMAnN3, test differential abundance via MaAsLin2, detect AMR genes with AMRFinderPlus. Use for metagenomic functional annotation, pathway abundance, or AMR profiling.
    0 installs
25. ▌
    Bio Applied Lncrna Classification · pavel-kravchenko

    Classify StringTie/gffcompare transcripts into lncRNA subtypes by class code/length/TPM, score coding potential with CPC2/CPAT, detect circRNAs via CIRI2 BSJ reads. Use for lncRNA annotation or circRNA calls.
    0 installs
26. ▌
    Bio Applied Viral Genome Assembly · pavel-kravchenko

    Assemble viral genomes from ARTIC amplicon FASTQ with minimap2/iVar/LoFreq; call consensus, detect quasispecies variants. Use when doing SARS-CoV-2/HIV/Influenza assembly, ARTIC pipelines, or minority variant calling.
    0 installs
27. ▌
    Python Bio SQL For Bioinformatics · pavel-kravchenko

    Query genomic data with SQLite (sqlite3, pandas.read_sql_query): SELECT/WHERE/GROUP BY/HAVING, INNER/LEFT JOIN, subqueries, parameterized inserts. Use when writing SQL over gene/variant tables or building a SQLite database.
    0 installs
28. ▌
    Bio Applied Cancer Transcriptomics · pavel-kravchenko

    Classify tumor RNA-seq into subtypes (melanoma Tirosh/Harbst on TCGA-SKCM): log1p/z-score, PCA/t-SNE, hierarchical clustering, random forest, Kaplan-Meier survival. Use when subtyping cBioPortal expression data.
    0 installs
29. ▌
    AI Science Alphafold Protein Design · pavel-kravchenko

    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.
    0 installs
30. ▌
    Bio Applied Screen Qc Normalization · pavel-kravchenko

    Compute Gini index and replicate LFC correlation on CRISPR sgRNA count matrices; apply DESeq2-style median-ratio normalization before MAGeCK/CRISPRcleanR. Use when QC'ing a CRISPR screen count table or flagging copy-number-biased dropout.
    0 installs
31. ▌
    Bio Applied Spatial Transcriptomics · pavel-kravchenko

    Analyze Visium/Xenium/MERFISH spatial transcriptomics with Squidpy/Scanpy: QC, spatial neighbor graphs, Moran's I spatially variable genes, tissue-image plots. Use for spatial autocorrelation or SVG detection.
    0 installs
32. ▌
    Bio Applied Dimensionality Reduction · pavel-kravchenko

    Compute PCA/UMAP embeddings and Leiden clusters for scRNA-seq with scanpy/Seurat; tune n_pcs/n_neighbors/resolution, find markers via rank_genes_groups. Use for UMAP plots, clustering single-cell data, or picking PCs/resolution.
    0 installs
33. ▌
    Bio Applied Gene Regulatory Networks · pavel-kravchenko

    Infer TF-target regulatory networks via correlation, ARACNE mutual information, and GENIE3 random-forest importance; find feed-forward loops; validate against TRRUST. Use when building a GRN or asked about GENIE3, ARACNE, or regulons.
    0 installs
34. ▌
    Bio Applied Mageck Gene Essentiality · pavel-kravchenko

    Run MAGeCK count/test on pooled CRISPR sgRNA screens, scoring gene essentiality via RRA, FDR, and log2 fold-change. Use when analyzing CRISPR screen FASTQ/count data, calling essential or drug-resistance genes, or benchmarking vs DepMap.
    0 installs
35. ▌
    Bio Core Multiple Sequence Alignment · pavel-kravchenko

    Align FASTA sequences via MAFFT/MUSCLE/Clustal Omega, parse with Biopython AlignIO, build UPGMA guide trees, score sum-of-pairs/consensus/conservation. Use for MSA, MSA tool choice, consensus/logo, or guide-tree building.
    0 installs
36. ▌
    Bio Core Pairwise Sequence Alignment · pavel-kravchenko

    Align two protein/DNA sequences with Biopython's PairwiseAligner (global Needleman-Wunsch, local Smith-Waterman), BLOSUM/PAM substitution matrices, and affine gap penalties; compute percent identity/similarity and E-values. Use when doing pairwise sequence alignment, ortholog comparison, dot plots, or choosing BLOSUM62 vs PAM250.
    0 installs
37. ▌
    AI Science Epigenomic Sequence Models · pavel-kravchenko

    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.
    0 installs
38. ▌
    Bio Applied Deep Learning For Biology · pavel-kravchenko

    Train PyTorch CNN/LSTM/Transformer/VAE on DNA/protein sequences: one-hot encoding, motif filters, saliency. Use when classifying sequences, predicting TF binding sites, denoising scRNA-seq, or choosing DL vs ML.
    0 installs
39. ▌
    Bio Applied Metabolite Identification · pavel-kravchenko

    Assign molecular formulas from accurate mass/adducts and match MS/MS spectra by cosine similarity to GNPS/MassBank/HMDB. Use for LC-MS peak annotation, MSI confidence scoring, or KEGG metabolite enrichment (MSEA).
    0 installs
40. ▌
    AI Science Diffusion Generative Models · pavel-kravchenko

    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.
    0 installs
41. ▌
    AI Science Variant To Structure Models · pavel-kravchenko

    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.
    0 installs
42. ▌
    Bio Applied Bayesian Statistics Python · pavel-kravchenko

    Fit Bayesian models with PyMC/Bambi/ArviZ: NUTS sampling, prior/posterior checks, HDI intervals, hierarchical GLMMs, LOO/WAIC comparison. Use when doing Bayesian inference, hierarchical modeling, or MCMC diagnostics.
    0 installs
43. ▌
    Foundations Biostatistics Fundamentals · pavel-kravchenko

    Run t-test/Mann-Whitney/ANOVA/chi-square tests, BH-FDR correction, and power analysis in SciPy, statsmodels, R. Use when comparing groups, interpreting p-values/CIs, correcting many gene-level tests, or sizing an experiment.
    0 installs
44. ▌
    Bio Applied Machine Learning For Biology · pavel-kravchenko

    Engineer k-mer/GC/CpG DNA features, train scikit-learn classifiers (LogisticRegression, RandomForest, SVC), evaluate with CV/ROC-AUC. Use for promoter/variant classifiers or model comparison on omics features.
    0 installs
45. ▌
    Bio Applied Genetic Engineering In Silico · pavel-kravchenko

    Simulate restriction digests, overhang compatibility, and primer Tm (Wallace/SantaLucia NN) in Python; plot agarose gel bands. Use when planning cloning, enzyme compatibility, or PCR primer design for a target Tm.
    0 installs
46. ▌
    Bio Applied Statistics For Bioinformatics · pavel-kravchenko

    Run t-test/Mann-Whitney/ANOVA with scipy.stats, apply Bonferroni/BH-FDR via statsmodels, compute Cohen's d and power. Use for comparing expression/counts between groups, correcting p-values, or genomics power analysis.
    0 installs
47. ▌
    Bio Applied Variant Calling And Snp Analysis · pavel-kravchenko

    Run GATK/bcftools BAM-to-VCF calling, parse VCF fields, decode genotypes (GT/AD/DP/GQ), hard-filter variants, test Hardy-Weinberg equilibrium. Use for SNP/indel calling, VCF/GVCF parsing, zygosity decoding, or HWE checks.
    0 installs
48. ▌
    Bio Applied Numerical Methods For Bioinformatics · pavel-kravchenko

    Interpolate missing time points (Newton/cubic spline), estimate derivatives, and compute AUC via trapezoidal/Simpson/curve_fit in SciPy. Use for missing qPCR points, PK dC/dt, dose-response/ROC AUC, or Michaelis-Menten/Hill fits.
    0 installs
49. ▌
    Foundations R Hypothesis Testing And Nonparametrics · pavel-kravchenko

    Run exact/nonparametric hypothesis tests in R: binom.test, sign test, wilcox.test/wilcox.exact (Wilcoxon signed-rank and Mann-Whitney U), kruskal.test with Dunn post-hoc, Hodges-Lehmann CIs, and binomial power/sample-size functions. Use when a user asks to test proportions, compare paired or independent samples that are non-normal or small-n, run Mann-Whitney/Wilcoxon/Kruskal-Wallis in R, or compute power/sample size for a binomial test.
    0 installs
50. ▌
    Foundations R Regression Correlation And Diagnostics · pavel-kravchenko

    Fit/diagnose R lm() regression and compute Pearson/Spearman/Kendall correlation with Fisher z CIs. Use for lm() regression, residual diagnostics, correlation CIs, or t.test/shapiro.test checks.
    0 installs
51. ▌
    Rnaseq · pavel-kravchenko

    Run bulk RNA-seq DE with DESeq2/PyDESeq2: size-factor normalization, Wald test, apeglm LFC shrinkage, volcano/MA plots. Use for RNA-seq differential expression, TPM/FPKM/CPM, or STAR/Salmon/featureCounts to DESeq2 pipelines.
    0 installs
52. ▌
    Algo Tries · pavel-kravchenko

    Implement a trie (prefix tree) in Python for O(m) word insert/search, O(p) prefix checks, and O(p+k) prefix enumeration; build autocomplete, spell-checkers, and k-mer/gene-name lookup over DNA or dictionary strings. Use when asked for prefix tree, trie data structure, autocomplete implementation, dictionary/word membership, longest-prefix match, gene-name or k-mer prefix search, or radix/compressed trie.
    0 installs
53. ▌
    Algo Bfs Dfs · pavel-kravchenko

    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.
    0 installs
54. ▌
    Document RAG · pavel-kravchenko

    Retrieve PDF/image pages with ColPali late-interaction embeddings and answer questions via Qwen2-VL/LLaVA. Use when doing document RAG, PDF QA, or retrieval over scanned papers/reports.
    0 installs
55. ▌
    Metabolomics · pavel-kravchenko

    Parse LC-MS mzML with pyOpenMS, PQN/LOESS-normalize feature tables, match m/z to HMDB/GNPS by ppm, run COBRApy FBA. Use when doing metabolomics preprocessing, metabolite ID, feature QC, MSEA enrichment, or flux modeling.
    0 installs
56. ▌
    Algo Dijkstra · pavel-kravchenko

    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 confidence score product.
    0 installs
57. ▌
    Algo Knapsack · pavel-kravchenko

    Solve 0/1, unbounded, subset-sum, and bitmask set-cover knapsack DP in Python with traceback and O(capacity)-space optimization. Use when picking an optimal subset under a budget/capacity constraint — gene panel or assay selection under a sequencing budget, primer/reagent allocation, experiment portfolio selection, or any "maximize value subject to a cost limit" or "does a subset sum to X" problem.
    0 installs
58. ▌
    Algo Avl Trees · pavel-kravchenko

    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) degeneration of a BST on sorted/near-sorted input (e.g. genomic positions arriving in coordinate order).
    0 installs
59. ▌
    Immunogenomics · pavel-kravchenko

    Analyze scTCR/BCR-seq with scirpy on 10x VDJ contigs, type HLA with OptiType, and score neoantigens with NetMHCpan/pVACseq. Use when doing clonotype/repertoire analysis, HLA typing, or building neoantigen pipelines.
    0 installs
60. ▌
    Linux Git Bash · pavel-kravchenko

    Write set -euo pipefail bash pipelines, parse FASTA/FASTQ/VCF/GTF/BED with grep/awk/sed and BAM with samtools, and run git workflows. Use when writing/debugging shell scripts or fixing git/BOM/CRLF issues.
    0 installs
61. ▌
    Python Bio Oop · pavel-kravchenko

    Build Python classes with __getitem__/__contains__/__call__/__slots__ and mixins for sequence databases, sliceable sequences, motif scorers, low-memory variants. Use for custom bio classes or dunder/OOP/__slots__ code.
    0 installs
62. ▌
    Algo Rabin Karp · pavel-kravchenko

    Rabin-Karp rolling-hash search in Python for single/multi-pattern matching (DNA motifs, k-mers, plagiarism phrases). Use when finding pattern occurrences in text, explaining rolling hash, or comparing vs KMP/naive search.
    0 installs
63. ▌
    Algo Tabulation · pavel-kravchenko

    Bottom-up DP (tabulation) in Python: edit distance/Levenshtein, LCS, and LIS with rolling-array space optimization. Use when comparing DNA/protein sequences, scoring similarity, or filling a DP table without recursion.
    0 installs
64. ▌
    Dna Methylation · pavel-kravchenko

    Align WGBS/RRBS bisulfite reads with Bismark; call DMRs/DMPs with methylKit or BSmooth. Use when analyzing bisulfite sequencing, CpG beta values, .cov/cytosine_report files, or DNAm epigenetic age (Horvath/GrimAge).
    0 installs
65. ▌
    Network Biology · pavel-kravchenko

    Build PPI networks from STRING with NetworkX, find hub genes via centrality, detect Louvain modules, infer GRNs with GENIE3. Use for protein interaction networks, hub/bottleneck genes, network communities, GRN inference.
    0 installs
66. ▌
    Python Bio Sets · pavel-kravchenko

    Python set ops (union/intersection/difference) and collections.Counter for gene-list comparisons and k-mer/codon counting. Use when comparing gene lists, finding shared orthologs, computing k-mer Jaccard similarity, or tallying GC/codon usage.
    0 installs
67. ▌
    Python Core Bio · pavel-kravchenko

    Write pure-Python DNA/RNA sequence code (reverse complement, GC%, translation, ORF finding) and parse FASTA/FASTQ with generators. Use when writing sequence utilities without Biopython or parsing bio files from scratch.
    0 installs
68. ▌
    Rnaseq Analysis · pavel-kravchenko

    Run bulk RNA-seq differential expression from a gene x sample count matrix using DESeq2 (R), pydeseq2, or edgeR — normalization (median-of-ratios/TPM), Wald/LRT testing, BH-adjusted p-values, volcano/MA plots, and GSEA/ORA. Use when doing RNA-seq DE, comparing treatment vs control expression, building a FASTQ-to-DESeq2 pipeline, or asked about TPM/RPKM/FPKM, count matrices, log2FoldChange, padj, or STAR/Salmon/featureCounts/tximport.
    0 installs
69. ▌
    Bio Applied Gwas · pavel-kravchenko

    Run GWAS: SNP QC (MAF/HWE), PCA ancestry covariates, per-SNP logistic/linear regression, Manhattan/QQ plots, genomic inflation, LD clumping. Use when doing GWAS, SNP-array association, or stratification correction.
    0 installs
70. ▌
    Bio Core Domains · pavel-kravchenko

    Build/scan PWMs (PPM, log-odds, info content, logos) for DNA motifs, convert PROSITE patterns to regex, parse HMMER domtblout/Pfam hits. Use for TF binding scans, promoter motifs, PROSITE matches, or Pfam/InterPro domain mapping.
    0 installs
71. ▌
    Python Bio Lists · pavel-kravchenko

    Split CDS into codons, extract k-mers, sort sequences by GC%/length, and pack gene coordinates into tuples/namedtuples. Use when looping over genes/codons/SNPs/BED intervals, computing sliding-window GC%, or detecting gene overlaps in Python.
    0 installs
72. ▌
    Python Bio Numpy · pavel-kravchenko

    Vectorize bioinformatics math with NumPy — RPKM/CPM/TPM normalization, per-gene z-scores, broadcasting over genes x samples matrices, position weight matrices (PWM/PSSM) for motif scoring, and O(n) sliding-window GC content via cumsum. Use when normalizing count matrices, computing per-row/per-column statistics on expression data, building or scoring a PWM, calculating GC content over a genome window, or replacing slow Python for-loops over arrays with vectorized operations.
    0 installs
73. ▌
    Algo Aho Corasick · pavel-kravchenko

    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.
    0 installs
74. ▌
    Algo Dfa Matching · pavel-kravchenko

    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.
    0 installs
75. ▌
    Algo Linear Sorts · pavel-kravchenko

    Implement counting sort, radix sort, and bucket sort in Python for O(n) non-comparison sorting of integers, fixed-length strings, and DNA k-mers. Use when sorting integers with a small known range, sorting fixed-length keys/k-mers for de Bruijn graph construction or k-mer analysis, or explaining why non-comparison sorts beat the Omega(n log n) lower bound.
    0 installs
76. ▌
    Algo Linked Lists · pavel-kravchenko

    Implement singly/doubly linked lists in Python (O(1) head/tail insert, delete, reverse) plus pointer problems like Floyd's cycle detection and merge-sorted-lists. Use for linked-list coding-interview questions.
    0 installs
77. ▌
    Algo Suffix Trees · pavel-kravchenko

    Build a suffix tree for O(m) pattern search, longest repeated substring, and longest common substring (LCS). Use when finding all motif occurrences in DNA/text, detecting tandem repeats, or comparing two sequences' shared region.
    0 installs
78. ▌
    Atac Seq Analysis · pavel-kravchenko

    Analyze ATAC-seq BAM/BED data with pysam and pybedtools — fragment-size QC, NFR fraction, Tn5 +4/-5 offset correction, and TF footprint scoring around motif sites. Use when doing ATAC-seq QC, computing nucleosome-free-region fraction, correcting Tn5 insertion bias, or scoring transcription-factor footprints from chromatin accessibility data.
    0 installs
79. ▌
    Bio Applied Mofa2 · pavel-kravchenko

    Run MOFA2 (mofapy2/muon) to fuse RNA-seq, proteomics, methylation into latent factors; decompose per-view R2, interpret weights. Use for multi-omics integration, MOFA/MOFA2 analysis, or latent factor discovery.
    0 installs
80. ▌
    Bio Core Pathways · pavel-kravchenko

    Run GO/KEGG pathway enrichment via ORA (hypergeometric test) or GSEA, with BH-FDR and KEGG REST API queries. Use for "GO enrichment", "GSEA", "ORA vs GSEA", or "pathway enrichment" requests.
    0 installs
81. ▌
    Python Bio Pandas · pavel-kravchenko

    Manipulate bio DataFrames with pandas — loc/iloc selection, boolean/query filtering, groupby agg vs transform, left-join annotation merges, CSV/TSV expression-matrix I/O, wide/long melt. Use when indexing/filtering a gene or sample table, merging expression data with an annotation or clinical table, computing group-wise statistics (per-condition mean/z-score), or reading a counts.csv/counts.tsv into a DataFrame.
    0 installs
82. ▌
    Python Bio Tuples · pavel-kravchenko

    Build immutable Python tuple/namedtuple records for gene coordinates and SNP tuples (chrom,pos,ref,alt). Use when storing fixed records, returning multiple values, using coords as dict keys, or fixing list-aliasing/mutable-default bugs.
    0 installs
83. ▌
    String Algorithms · pavel-kravchenko

    Implement naive search, KMP (prefix function), Rabin-Karp (rolling hash), and DFA-based pattern matching in pure Python for exact substring/motif search in DNA or text. Use when finding restriction sites, scanning FASTQ/genome strings for a fixed motif, matching multiple same-length k-mers in one pass, or asked to explain/implement KMP failure function, rolling hash, or a pattern-matching automaton.
    0 installs
84. ▌
    Algo Kmp Algorithm · pavel-kravchenko

    Find all overlapping exact occurrences of a pattern/motif/primer in a string or DNA sequence in O(n+m) time via KMP's prefix/failure-function. Use for exact substring search, motif/primer location, or a slow naive O(n*m) scan.
    0 installs
85. ▌
    Algo Stacks Queues · pavel-kravchenko

    Implement Stack (LIFO)/Queue (FIFO) in Python (array, linked-list, two-stack) with O(1) ops; validate balanced brackets/RNA dot-bracket notation. Use for stack/queue from scratch, backing BFS/DFS, or checking parens.
    0 installs
86. ▌
    Algo Suffix Arrays · pavel-kravchenko

    Build a suffix array (Manber-Myers O(n log n)) and LCP array (Kasai's O(n)) in Python; binary-search substrings, count k-mers, find longest repeated motifs. Use for text indexing, pattern search, or aligner (BWA-like) internals.
    0 installs
87. ▌
    Generative Imaging · pavel-kravchenko

    Restore images (denoising, inpainting, super-resolution) via DDRM SVD data-consistency projection with DDIM diffusion sampling in NumPy. Use for cryo-EM/MRI restoration or inverse problems y=Hx with a diffusion prior.
    0 installs
88. ▌
    Python Bio Classes · pavel-kravchenko

    Build Python classes for Gene/DNA/RNA/Protein records with __eq__/__lt__/__hash__, @property validation, ABCs, and @classmethod parsers (from_fasta_string). Use when modeling genes/FASTA/GFF as objects or asked about Python OOP, inheritance, dataclasses.
    0 installs
89. ▌
    Python Bio Strings · pavel-kravchenko

    DNA/RNA as Python strings: reverse complement (maketrans/translate), GC content, codon split, motif find (find/re.finditer), FASTA header parsing. Use for reverse complement, transcription, motif counting without Biopython.
    0 installs
90. ▌
    Scrna Seq Analysis · pavel-kravchenko

    Process 10x/Smart-seq scRNA-seq count matrices in scanpy/AnnData end-to-end — QC filtering, normalization, HVG selection, PCA/UMAP, Leiden clustering, marker genes, CellTypist annotation, and scVelo trajectory. Use when analyzing single-cell RNA-seq data, working with .h5ad/AnnData objects or 10x matrix.mtx output, clustering cells, annotating cell types, or computing RNA velocity/pseudotime.
    0 installs
91. ▌
    Algo Dynamic Arrays · pavel-kravchenko

    Implement resizable arrays with ctypes-backed doubling/shrinking; prove append is amortized O(1). Use when asked why list.append is O(1), to build a DynamicArray class, or to compare list vs numpy append speed.
    0 installs
92. ▌
    Bio Applied Docking · pavel-kravchenko

    Dock ligands into a receptor with AutoDock Vina: build PDBQT files (Open Babel/RDKit), set the grid box, run vina, parse/rank poses by affinity and RMSD. Use for molecular docking, virtual screening, redocking a co-crystal ligand, or PDB/SMILES to PDBQT conversion.
    0 installs
93. ▌
    Biopython Databases · pavel-kravchenko

    Fetch sequences from NCBI Entrez/UniProt/PDB/Ensembl REST APIs via BioPython SeqIO; read/write FASTA/GenBank/FASTQ. Use when downloading by accession/gene name, batch-fetching records, or converting sequence file formats.
    0 installs
94. ▌
    Chipseq Epigenomics · pavel-kravchenko

    Align/call ChIP-seq peaks with Bowtie2+MACS3, run DiffBind binding and ChIPseeker annotation in R, visualize with deepTools. Use for TF/histone peak calling, narrow vs broad peaks, FRiP/NSC/RSC QC, or peak annotation.
    0 installs
95. ▌
    Python Advanced SQL · pavel-kravchenko

    Write Python decorators/context managers/dataclasses and query gene/variant tables with sqlite3/pandas SQL (JOIN, GROUP BY, HAVING). Use for retry/caching/validation wrappers or SQL against Ensembl/UCSC-style schemas.
    0 installs
96. ▌
    Algo Red Black Trees · pavel-kravchenko

    Implement a red-black self-balancing BST (insert, rotations, recoloring) for O(log n) search on sorted VCF variant positions. Use when building a balanced BST, verifying invariants, or comparing red-black vs AVL trees.
    0 installs
97. ▌
    Bio Applied Mixomics · pavel-kravchenko

    Run mixOmics PLS-DA/sPLS-DA/DIABLO to classify samples and pick stable biomarkers from paired RNA-seq/proteomics/methylation blocks. Use for supervised multi-omics classification or DIABLO biomarker discovery.
    0 installs
98. ▌
    Bio Applied Promoter · pavel-kravchenko

    Detect TATA box/Inr/DPE promoter elements, call CpG islands (O/E ratio), and build/score PWMs for TFBS scanning. Use when finding a TATA box, calling CpG islands, or scanning a sequence for transcription factor binding sites.
    0 installs
99. ▌
    Bio Applied Ribo Seq · pavel-kravchenko

    Ribo-seq: cutadapt/bowtie2 adapter+rRNA removal, plastid P-site calibration, 3-nt periodicity QC, RiboCode/ribotricer ORF calling, translation efficiency. Use when user has ribosome profiling or footprint data.
    0 installs
100. ▌
     Long Read Sequencing · pavel-kravchenko

     Basecall ONT POD5 with Dorado, align with Minimap2, assemble with Flye/Hifiasm, call SVs with Sniffles2. Use when basecalling nanopore reads, doing long-read assembly, SV calling, or ONT methylation/isoform analysis.
     0 installs