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Scientific Hypothesis Formulation

hypothesis-generation

K-Dense-AI/scientific-agent-skills

Guides structured hypothesis generation by combining literature searches, evidence synthesis, competing explanations, and experimental design, with mandatory AI-generated scientific schematics for complete reports.

LaminDB Biological Data Platform

K-Dense-AI/scientific-agent-skills

LaminDB is a Python-driven open-source framework for managing biological datasets, ensuring traceable, reproducible, FAIR data through lineage tracking, schema validation, ontology annotation, workflow integration, and lakehouse-style querying.

Molecular Featurization Hub

K-Dense-AI/scientific-agent-skills

Molfeat is a Python toolkit that converts SMILES/RDKit molecules into embeddings via 100+ calculators, transformers, and pretrained models for QSAR, screening, similarity search, and deep learning pipelines.

PathML Computational Pathology Toolkit

K-Dense-AI/scientific-agent-skills

PathML is a Python toolkit for computational pathology workflows, loading 160+ slide formats, preprocessing H&E images, constructing spatial graphs, training HoVer-Net/HACTNet models, and analyzing multiplex imaging for ML-ready pathology data.

PyDESeq2 Differential Analysis

K-Dense-AI/scientific-agent-skills

PyDESeq2 brings the DESeq2 differential expression workflow to Python, letting users load bulk RNA-seq counts, specify design formulas, fit DESeq2 models, run Wald tests with FDR correction, optionally apply apeGLM shrinkage, and export gene-level statistics within pandas/AnnData pipelines.

Medical Imaging DICOM Toolkit

K-Dense-AI/scientific-agent-skills

Pydicom is a Python toolkit for reading, writing, and manipulating DICOM medical imaging files, helping teams extract pixel data, manage metadata, anonymize records, convert to standard formats, and integrate with PACS workflows in healthcare research and radiology applications.

Bayesian Modeling and Inference with PyMC

K-Dense-AI/scientific-agent-skills

PyMC is a powerful Python library for probabilistic programming and advanced Bayesian inference. This comprehensive guide details the full workflow for building, fitting, and validating complex Bayesian models. Learn to implement hierarchical structures, perform MCMC sampling (NUTS), conduct posterior predictive checks (PPC), and effectively quantify uncertainty using industry best practices.

Advanced Molecular Control

K-Dense-AI/scientific-agent-skills

RDKit delivers a Python-based cheminformatics toolkit for parsing SMILES/SDF, computing descriptors, generating 2D/3D coordinates, fingerprinting, searching substructures, managing reactions, and visualizing molecules, ideal for drug discovery and computational chemistry workflows.

Intelligent Research Information Lookup

research-lookup

K-Dense-AI/scientific-agent-skills

This skill provides intelligent, multi-backend research lookup, automatically routing queries to the optimal source. It utilizes fast web search for general queries, the Parallel Chat API for deep synthesis, and Perplexity for academic paper searches. Use it to gather up-to-date scientific findings, verify facts, analyze market trends, or retrieve technical documentation.

Scientific Visualization Toolkit

scientific-visualization

K-Dense-AI/scientific-agent-skills

Transforms data into publication-ready figures with multi-panel layouts, precise annotations, colorblind-friendly palettes, and journal formatting using matplotlib, seaborn, and plotly plus export helpers for PDF/EPS/TIFF.

Microbiome Bioinformatics Toolkit

K-Dense-AI/scientific-agent-skills

scikit-bio provides a Python-native biological data toolkit for reading/writing FASTA/Newick files, manipulating sequences, building alignments and phylogenies, and calculating diversity metrics for microbiome and ecology workflows.

Statistical Analysis and Reporting Guide

statistical-analysis

K-Dense-AI/scientific-agent-skills

A comprehensive guide for systematic statistical analysis, designed for academic research. This skill assists in selecting the correct hypothesis tests (t-test, ANOVA, regression, chi-square), checking assumptions (normality, homogeneity), performing advanced analyses (Bayesian methods, power analysis), calculating effect sizes, and generating full APA-formatted reports for publication.

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