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PennyLane Quantum ML

K-Dense-AI/claude-scientific-skills

PennyLane is a hardware-agnostic quantum ML framework that lets you train parametrized quantum circuits with automatic differentiation, build hybrid quantum-classical models, and switch between simulators and hardware with tight PyTorch/JAX/TensorFlow integration.

Protocols.io Integration

protocolsio-integration

K-Dense-AI/claude-scientific-skills

Provides protocols.io API integration for searching, creating, updating, and publishing lab protocols, managing steps, workspaces, discussions, files, and experiment records so teams can automate collaborative protocol workflows.

PubChem Database Query

pubchem-database

K-Dense-AI/claude-scientific-skills

Leverages PubChem’s PUG-REST API or PubChemPy to search 110M+ compounds by name, CID, or structure, fetch properties, perform similarity/substructure lookups, and access bioactivity or format conversions for cheminformatics workflows.

PufferLib Reinforcement Learning

K-Dense-AI/claude-scientific-skills

PufferLib is a high-performance RL framework for fast parallel training, vectorized environments, and multi-agent workflows; use it when you need million-step-per-second PPO training, custom environments, or integration with Gymnasium, Atari, Procgen, and other ecosystems.

PyDESeq2 Differential Workflow

K-Dense-AI/claude-scientific-skills

PyDESeq2 brings DESeq2-style differential expression to Python, letting you load bulk RNA-seq counts, filter low-count genes, model single/multi-factor designs, run Wald tests with FDR correction, optionally shrink log-fold changes, and export results for pandas/AnnData workflows.

Pydicom Medical Imaging

K-Dense-AI/claude-scientific-skills

Pydicom lets Python programs read, write, and manipulate DICOM medical imaging files, covering pixel extraction, metadata edits, anonymization, format conversion, compression handling, and PACS integration for radiology workflows.

Hardware Agnostic Lab Automation

K-Dense-AI/claude-scientific-skills

PyLabRobot is a Python SDK that controls liquid handlers, plate readers, pumps and other lab automation devices through one unified API, ideal for multi-vendor workflows, simulations, and reproducible protocols across platforms.

Materials Structure Toolkit

K-Dense-AI/claude-scientific-skills

Pymatgen is a Python toolkit for computational materials science that creates, manipulates, and analyzes crystal structures, converts among 100+ formats, computes phase diagrams, and accesses Materials Project data for high-throughput workflows.

PyMC Bayesian Modeling

pymc-bayesian-modeling

K-Dense-AI/claude-scientific-skills

Structured workflow for building hierarchical Bayesian models with PyMC 5+, covering data prep, NUTS sampling, diagnostics, posterior checks, and predictive inference.

PyOpenMS Mass Spectrometry

K-Dense-AI/claude-scientific-skills

PyOpenMS exposes OpenMS via Python to cover end-to-end proteomics and metabolomics workflows, including file I/O, signal processing, feature detection, identification, quantitation, and integration with pandas/visualization stacks.

Therapeutics Data Commons

K-Dense-AI/claude-scientific-skills

PyTDC offers curated AI-ready datasets, standardized benchmarks, and scaffold-aware splits across ADME, toxicity, interaction, and generation tasks to support therapeutic ML and pharmacological prediction workflows.

Lightning Training Workflow

pytorch-lightning

K-Dense-AI/claude-scientific-skills

PyTorch Lightning organizes models into LightningModule, data modules, callbacks, logging, and Trainer orchestration for scalable multi-GPU/TPU training with distributed strategies and experiment tracking.

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