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FYDY

Official

@fuzzy-dynamics

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6Public Repos
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116Published Skills

Fuzzy Dynamics

Skills Distribution
DomainAI Models & ...Bioinformatics & G.. (35%)Cheminformatics & .. (25%)Scientific Computi.. (20%)Quantum & High-Per.. (20%)

Agent Skills by FYDY

Showing 116 vetted skills indexed across 1 GitHub repositories.

fuzzy-dynamicsfuzzy-dynamics
1

polars-bio

Perform overlap, nearest, and merge operations on Polars DataFrames.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

networkx

Create, analyze, and visualize complex networks and graphs in Python.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

anndata

Store and manage annotated single-cell data matrices with metadata.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

qiskit

Build, transpile, execute, and analyze quantum circuits on simulators and IBM hardware.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

scientific-brainstorming

Facilitate structured scientific ideation sessions with adaptive brainstorming methods.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

pymc

Build and infer Bayesian models with MCMC sampling and variational inference.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

perplexity-search

Automate real-time web searches with cited sources via Perplexity models.

Official
Intermediate
fuzzy-dynamicsfuzzy-dynamics
1

research-lookup

Route research queries to Parallel Chat API or Perplexity academic search.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

shap

Attribute model predictions to individual features using SHAP explainers.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

umap-learn

Reduce high-dimensional data to low-dimensional embeddings for visualization and clustering.

Official
Intermediate
fuzzy-dynamicsfuzzy-dynamics
1

geomaster

Integrate GIS, remote sensing, and machine learning into geospatial workflows.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

sympy

Solve symbolic mathematics tasks in Python using the SymPy library.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

vaex

Process large tabular datasets with lazy, out-of-core DataFrames.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

dask

Distribute large pandas and NumPy workloads across clusters with parallel computation.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

get-available-resources

Detect CPU, memory, disk, and GPU availability and generate a .claude_resources.json report.

Official
Intermediate
fuzzy-dynamicsfuzzy-dynamics
1

parallel-web

Automate web research and content extraction via Parallel Web Systems APIs.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

exploratory-data-analysis

Detects file type and generates Markdown reports for scientific data.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

iso-13485-certification

Generate ISO 13485 quality manual, MDFs, procedures templates and gap-analysis for medical device manufacturers.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

esm

Design and analyze proteins using ESM3 and ESM C models.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

scientific-schematics

Generate publication-quality scientific diagrams from natural language prompts.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

arboreto

Infer gene regulatory networks from expression data using GRNBoost2 or GENIE3.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

geniml

Trains unsupervised embeddings for genomic intervals and metadata from BED files.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

geopandas

Analyze geospatial vector data with pandas-like workflows in Python.

Official
Advanced
fuzzy-dynamicsfuzzy-dynamics
1

pyzotero

Manage Zotero libraries via the PyZotero client API.

Official
Intermediate

Frequently Asked Questions About FYDY

FAQPage Schema
What specific scientific tasks can be performed using these capabilities?

These capabilities enable end-to-end bioinformatics analysis, molecular dynamics simulations, quantum circuit design, and automated literature synthesis. Users can perform differential gene expression analysis, protein-ligand binding predictions, and generate publication-ready scientific manuscripts or clinical reports from structured data.

Which personas benefit most from this technical registry?

Computational biologists, medicinal chemists, data scientists, and research engineers benefit from these integrated modules. The registry is designed for professionals requiring reproducible research environments, high-performance computing access, and standardized reporting for clinical or academic publications.

What are the prerequisites for running these research modules?

Execution requires a Linux-based environment with standard scientific libraries installed. Many modules rely on specific domain-specific dependencies like RDKit for chemistry, Scanpy for genomics, or OpenMM for molecular dynamics, alongside access to configured remote compute hosts or local Docker sandboxes.