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Claude Skills by Pavel-Kravchenko
github.com/Pavel-Kravchenko213 skills0 installs219 views
- Bio Applied BiochemistryBiochemistry fundamentals for computational biologists — Beer-Lambert law, spectrophotometric assays, Michaelis-Menten kinetics, linearization methods, and inhibition modelsVotes: 0GitHub stars: 4
- Bio Applied Cancer TranscriptomicsCancer transcriptomics — melanoma subtype classification (Tirosh/Harbst), preprocessing pipeline, PCA/t-SNE, hierarchical clustering, random forest, and Kaplan-Meier survival analysisVotes: 0GitHub stars: 4
- Bio Applied Capstone ProjectIntegrative bioinformatics pipeline — sequence QC, BLAST identification, MSA, phylogenetics, structure analysis, GO enrichment, and publication figuresVotes: 0GitHub stars: 4
- Bio Applied Cell Type AnnotationscRNA-seq cell type annotation — manual marker scoring, SingleR reference-based, and CellTypist automated classificationVotes: 0GitHub stars: 4
- Bio Applied Chipseq PipelineChIP-seq pipeline — QC, alignment, deduplication, peak calling with MACS2, and signal normalization with deepToolsVotes: 0GitHub stars: 4
- Bio Applied Cite Seq IntegrationCITE-seq and Multiome integration — ADT normalization (CLR/DSB), WNN graph construction, and paired RNA+ATAC analysis with muonVotes: 0GitHub stars: 4
- Bio Applied Clinical GenomicsClinical genomics — ACMG/AMP variant classification, ClinVar queries, and clinical reporting workflowsVotes: 0GitHub stars: 4
- Bio Applied Copy Number AnalysisDNA copy number analysis — read depth normalization, CBS segmentation, CN state calling, and genome-wide visualizationVotes: 0GitHub stars: 4
- Bio Applied Data HarmonizationMulti-omics data harmonization — normalization strategies, missing data imputation, batch correction, and integration approaches (MOFA2, DIABLO)Votes: 0GitHub stars: 4
- Bio Applied Deep Learning For BiologyPyTorch deep learning for biological sequences — when to use DL vs classical ML, CNN architecture for motif detection, one-hot encoding, and the standard training loopVotes: 0GitHub stars: 4
- Bio Applied Differential BindingDifferential binding analysis for ChIP-seq: DiffBind workflow, consensus peaks, normalization, and MA/volcano plots. Use when comparing ChIP-seq signal between conditions.Votes: 0GitHub stars: 4
- Bio Applied Dimensionality ReductionscRNA-seq dimensionality reduction and clustering: PCA, k-NN graph, UMAP, Leiden. Parameter selection guide, implementation patterns, and pitfalls.Votes: 0GitHub stars: 4
- Bio Applied Dmr AnalysisDifferentially Methylated Regions (DMRs)Votes: 0GitHub stars: 4
- Bio Applied DockingMolecular docking: ligand preparation, receptor setup, AutoDock Vina workflow, scoring functions, and binding pose analysis. Use when predicting protein-ligand interactions.Votes: 0GitHub stars: 4
- Bio Applied Enzyme KineticsEnzyme kinetics computational patterns — fitting Michaelis-Menten with scipy, bootstrap confidence intervals, inhibition type determination, allosteric cooperativity, and multi-substrate kineticsVotes: 0GitHub stars: 4
- Bio Applied Epigenetic ClocksEpigenetic Clocks and Aging Analysis with MatplotlibVotes: 0GitHub stars: 4
- Bio Applied Functional AnnotationFunctional Annotation of Metagenomes with NumPyVotes: 0GitHub stars: 4
- Bio Applied Gene Regulatory NetworksGRN inference methods: correlation, mutual information (ARACNE), and random forest (GENIE3). Decision table for method selection, evaluation patterns, and key pitfalls.Votes: 0GitHub stars: 4
- Bio Applied Genetic Engineering In SilicoIn silico restriction digestion, compatible end detection, primer design (Tm models), and gel simulationVotes: 0GitHub stars: 4
- Bio Applied Genome AssemblyGenome assembly algorithms (OLC and de Bruijn graph), k-mer selection, assembler comparison table, and SPAdes/Flye/hifiasm usage.Votes: 0GitHub stars: 4
- Bio Applied GwasGenome-Wide Association Studies (GWAS) with NumPyVotes: 0GitHub stars: 4
- Bio Applied Hla TypingHLA Typing and Antigen PresentationVotes: 0GitHub stars: 4
- Bio Applied Immune RepertoireImmune repertoire sequencing — TRUST4/MiXCR workflows, diversity metrics, clonal tracking, Morisita-Horn overlap, VDJdb lookup, CDR3 Hamming clustering.Votes: 0GitHub stars: 4
- Bio Applied Isoform AnalysisIsoform analysis with long reads — Minimap2 splice alignment, bambu isoform discovery, DRIMSeq differential isoform usage.Votes: 0GitHub stars: 4
- Bio Applied Lc Ms PreprocessingLC-MS metabolomics data preprocessing: peak picking, retention time alignment, gap filling, and adduct detection. Use when processing raw mass spectrometry data for metabolomics studies.Votes: 0GitHub stars: 4
- Bio Applied Lncrna ClassificationLong Non-Coding RNA: Discovery and ClassificationVotes: 0GitHub stars: 4
- Bio Applied Machine Learning For BiologyMachine learning for bioinformatics — feature engineering for sequences, promoter classification, train/test splits, logistic regression, random forest, and bio-specific pitfallsVotes: 0GitHub stars: 4
- Bio Applied Mageck Gene EssentialityCRISPR Screen Analysis with MAGeCK with MAGeCKVotes: 0GitHub stars: 4
- Bio Applied Metabolic FluxFlux balance analysis and metabolic modeling with COBRApy. Use when predicting metabolic fluxes, simulating gene knockouts, or analyzing stoichiometric models.Votes: 0GitHub stars: 4
- Bio Applied Metabolite IdentificationMetabolite identification from MS/MS spectra: spectral matching, molecular formula prediction, and database searching (HMDB, KEGG). Use when annotating unknown metabolites.Votes: 0GitHub stars: 4
- Bio Applied Microbial DiversityMicrobial diversity analysis: alpha/beta diversity metrics, OTU/ASV methods, taxonomy assignment, and community comparison. Use when analyzing 16S amplicon or microbiome data.Votes: 0GitHub stars: 4
- Bio Applied Mirna Seq PipelinemiRNA-seq pipeline: adapter trimming, alignment to miRBase, quantification, DE analysis, and target prediction. Use when processing small RNA sequencing data.Votes: 0GitHub stars: 4
- Bio Applied MixomicsmixOmics PLS-DA and DIABLO for supervised multi-omics integration and feature selection. Use when classifying samples or selecting biomarkers from multi-omics data.Votes: 0GitHub stars: 4
- Bio Applied Mofa2MOFA2 unsupervised multi-omics factor analysis: variance decomposition, factor interpretation, and shared/view-specific signal separation. Use when integrating multiple omics layers.Votes: 0GitHub stars: 4
- Bio Applied Molecular EvolutionPopulation genetics and molecular evolution — Hardy-Weinberg, Wright-Fisher drift, selection models, dN/dS, Tajima's D, Fst, and the neutral theoryVotes: 0GitHub stars: 4
- Bio Applied Molecular GnnGraph Neural Networks for Molecular Property Prediction with RDKitVotes: 0GitHub stars: 4
- Bio Applied Molecular ModelingMolecular Modeling with NumPyVotes: 0GitHub stars: 4
- Bio Applied Network ModulesCommunity detection in biological networks — Louvain/Leiden algorithms, modularity Q, WGCNA co-expression modules, and Cytoscape exportVotes: 0GitHub stars: 4
- Bio Applied Ngs FundamentalsNGS platform comparison, FASTQ format, Phred quality scores, and QC metrics. Reference for sequencing technology selection and read quality assessment.Votes: 0GitHub stars: 4
- Bio Applied Numerical Methods For Bioinformatics- Implement Lagrange and Newton interpolation polynomials and explain the Runge phenomenon - Apply cubic spline interpolation to reconstruct missing time points in biological time series - Compute numVotes: 0GitHub stars: 4
- Bio Applied Ont ProcessingONT Data Processing with NumPyVotes: 0GitHub stars: 4
- Bio Applied PhylodynamicsViral phylodynamics — molecular clocks, root-to-tip regression, time-scaled phylogenies, Bayesian skyline plots, and phylogeography tool selectionVotes: 0GitHub stars: 4
- Bio Applied Population GeneticsPopulation genetics — Hardy-Weinberg equilibrium, Wright-Fisher drift simulation, selection models, molecular clock, dN/dS, Tajima's D, Fst, and linkage disequilibriumVotes: 0GitHub stars: 4
- Bio Applied Ppi NetworksPPI network construction and analysis with NetworkX and STRING DB: centrality metrics, hub/bottleneck classification, scale-free properties, and community detection.Votes: 0GitHub stars: 4
- Bio Applied PromoterCore promoter elements: TATA box, CpG islands, PWM construction, and TFBS scanning. Companion reference card to bio-applied-regulatory-analysis.Votes: 0GitHub stars: 4
- Bio Applied ProteomicsProteomics data analysis — peptide identification, quantification, PTM analysis, and protein inference workflowsVotes: 0GitHub stars: 4
- Bio Applied Qiime2 16s16S rRNA amplicon analysis with QIIME2: DADA2 denoising, taxonomy assignment, alpha/beta diversity, and differential abundance. Use when analyzing 16S microbiome data.Votes: 0GitHub stars: 4
- Bio Applied Qsar ModelingQSAR modeling: molecular descriptors, fingerprints, random forest/SVM models, applicability domain, and model validation. Use when building structure-activity relationship models.Votes: 0GitHub stars: 4
- Bio Applied Rdkit BasicsRDKit fundamentals: SMILES parsing, molecular properties, substructure search, fingerprints, and chemical similarity. Use when performing cheminformatics operations in Python.Votes: 0GitHub stars: 4
- Bio Applied Regulatory AnalysisPromoter and regulatory sequence analysis: TATA box detection, CpG island scanning, PWM/PFM construction, and TFBS scanning. Reference for computational promoter analysis.Votes: 0GitHub stars: 4