Discover Agent Skills for data science & ml. Browse 61 skills for Claude, ChatGPT & Codex.
Accesses the STRING database to analyze protein-protein interaction networks and perform functional enrichment for systems biology.
Optimizes Python data structures using defaultdict for efficient grouping, adjacency lists, and nested dictionary management.
Generates optimized race-day pacing and fueling strategies tailored to individual fitness levels and specific course topography.
Performs comprehensive survival analysis and time-to-event modeling using the scikit-survival library in Python.
Implements high-performance priority queues for pathfinding, scheduling, and stream processing using efficient heap-based structures.
Solves complex logic puzzles and scheduling problems using Peter Norvig's propagate-then-search algorithmic pattern.
Encapsulates complex state management into robust class structures to handle transitions, backtracking, and algorithmic branching.
Searches and retrieves information from the ZINC database of 230M+ purchasable compounds for drug discovery and virtual screening.
Implements flexible graph and tree traversal patterns with configurable DFS, BFS, and randomized exploration strategies.
Integrates KEGG REST API access into workflows for biological pathway analysis, gene mapping, and molecular interaction research.
Implements the Norvig pattern of returning sentinel values instead of exceptions for natural algorithmic failures.
Visualizes code changes, algorithm results, and data states by displaying multiple outputs in parallel columns.
Implements memory-efficient sparse data structures using Python sets for infinite grids and large coordinate spaces.
Queries NCBI ClinVar to retrieve and interpret clinical significance data for human genetic variants.
Manages local Ollama LLM models for development, testing, and VRAM optimization within Claude Code workflows.
Implements memory-efficient combinatorial iteration patterns in Python using the itertools library.
Accesses comprehensive pharmacogenomics data for precision medicine, genotype-guided dosing, and clinical decision support.
Implements elegant, idiomatic data transformations using Pythonic list, dictionary, and set comprehensions inspired by Peter Norvig.
Solves NP-hard optimization problems using greedy construction and iterative local improvement patterns.
Accesses and queries the ChEMBL database for bioactive molecules, drug targets, and bioactivity data within medicinal chemistry workflows.
Optimizes Python functions by implementing memoization and dynamic programming patterns to eliminate redundant recursive computations.
Optimizes constraint satisfaction problem-solving by eliminating impossibilities through inference before initiating recursive search operations.
Generates human-readable, aligned tables and statistical summaries for reporting results and data comparisons.
Access and query the COSMIC database for somatic mutations, cancer gene census, and mutational signatures to support precision oncology research.
Implements immutable, memory-efficient data structures using Python's namedtuple for cleaner and more readable code.
Analyzes whole-slide pathology images and multiparametric imaging data using advanced machine learning and spatial graph techniques.
Manipulates, analyzes, and visualizes phylogenetic and hierarchical tree structures with biological database integration.
Enables the creation of expressive domain-specific languages in Python by overloading arithmetic and logical operators.
Implements the Gale-Shapley algorithm to solve stable matching problems for two-sided markets like residency and admissions.
Generates high-quality static, animated, and interactive visualizations for data analysis and scientific publication.
Scroll for more results...