Download

Skill UI

Browse and discover 19332+ curated skills

All Development Artificial Intelligence Design & Creative Product & Business Data Science Marketing Soft Skills Productivity Engineering Languages

Search Processing , found 470 results

Default Newest Most Downloaded

Datamol Cheminformatics Toolkit

K-Dense-AI/scientific-agent-skills

Pythonic wrapper around RDKit for drug discovery workflows: SMILES parsing, standardization, descriptors, fingerprints, clustering, 3D conformers, and parallel batch processing. Returns native RDKit Mol objects.

DeepTools NGS Analysis Toolkit

K-Dense-AI/scientific-agent-skills

A comprehensive Python command-line toolkit for processing and visualizing high-throughput sequencing data including ChIP-seq, RNA-seq, and ATAC-seq. Performs quality control, normalization, sample comparison, and generates publication-quality genomic visualizations with bigWig conversion and heatmap profiles.

Gtars Genomic Interval Toolkit

K-Dense-AI/scientific-agent-skills

Gtars offers local genomic interval models, set algebra, overlap/count operations, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and CLI.

Modal Serverless Python Platform

K-Dense-AI/scientific-agent-skills

Modal is a serverless cloud platform for running Python code on demand, including GPU-accelerated AI/ML workloads. Use for deploying models, serving web APIs, batch processing, and scaling Python applications to cloud containers with automatic scaling from zero to thousands of instances. Supports custom container images, persistent storage, and sub-second cold starts for low-latency inference.

NeuroKit2 Biosignal Processing

K-Dense-AI/scientific-agent-skills

Build or audit reproducible research workflows with NeuroKit2 for physiological time-series: preprocessing, event/interval analysis, multimodal alignment, variability and complexity on ECG, RSP and EDA signals.

Neuropixels Neural Data Analysis

neuropixels-analysis

K-Dense-AI/scientific-agent-skills

End-to-end analysis toolkit for Neuropixels extracellular recordings using SpikeInterface. Supports loading SpikeGLX/Open Ephys/NWB data, preprocessing, drift correction, spike sorting with Kilosort4 and other algorithms, quality metrics computation, and AI-assisted unit curation for publication-ready neural data analysis.

PathML Computational Pathology Workflows

K-Dense-AI/scientific-agent-skills

Build local, research-only computational pathology workflows with PathML: load and tile whole-slide images, run preprocessing and QC pipelines, manage h5path data, quantify multiplex images, construct spatial graphs, and plan bounded model inference.

Polars DataFrame Analytics

K-Dense-AI/scientific-agent-skills

High-performance Python DataFrame library built on Apache Arrow. Covers expression-based API, lazy query optimization, streaming out-of-core processing, aggregations, window functions, joins, and pandas migration for ETL and analytics pipelines.

Python Genomic File Processing

K-Dense-AI/scientific-agent-skills

A Python library for reading, querying, filtering, and writing genomic file formats including SAM/BAM/CRAM, VCF/BCF, FASTA/FASTQ, and tabix data. Supports pileup, coverage analysis, indexing, and CRAM reference operations with HTSlib integration. Ideal for bioinformatics workflows requiring low-level streaming access to genomic data.

Scikit-learn Machine Learning

K-Dense-AI/scientific-agent-skills

Comprehensive guidance for machine learning in Python using scikit-learn. Covers classification, regression, clustering, preprocessing, model evaluation, and pipelines for building production-ready ML workflows.

UMAP Nonlinear Dimensionality Reduction

K-Dense-AI/scientific-agent-skills

Use UMAP-learn for fast, scalable nonlinear dimensionality reduction, 2D/3D visualization embeddings, clustering preprocessing, supervised and semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows, with guidance on key parameter tuning.

Vaex Large Dataset Analysis

K-Dense-AI/scientific-agent-skills

Vaex is a high-performance Python library designed for processing and analyzing large tabular datasets that exceed available RAM. It supports out-of-core DataFrame operations, lazy evaluation, fast aggregations, and efficient visualization of big data. Ideal for working with massive CSV, HDF5, Arrow, or Parquet files, performing statistics on billions of rows, and building machine learning pipelines without memory constraints.

Prev 1 2 3...14 15 161718 19 20...38 39 40 Next

Language