K-Dense AI
- 344 skills
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- 30k repo stars
- 2 weeks ago last updated
- ▌ Deepchem · k-dense-ai bundlePredict molecular properties, train graph neural networks, and run drug discovery workflows using DeepChem's featurizers, models, and MoleculeNet benchmarks.
- ▌ Diffdock · k-dense-ai bundlePredict 3D binding poses of small molecule ligands to protein targets using diffusion-based molecular docking, supporting single complexes, batch processing, and virtual screening.
- ▌ Fluidsim · k-dense-ai bundleRun computational fluid dynamics simulations using Python, including Navier-Stokes equations, shallow water, and stratified flows with pseudospectral methods and HPC support.
- ▌ Histolab · k-dense-ai bundleProcess whole slide images for digital pathology: detect tissue, extract tiles, and prepare datasets for deep learning pipelines.
- ▌ Networkx · k-dense-ai bundleCreate, analyze, and visualize complex networks and graphs in Python with NetworkX, including graph algorithms, community detection, synthetic network generation, and multiple I/O formats.
- ▌ Nextflow · k-dense-ai bundleBuild, run, and debug Nextflow data pipelines and nf-core workflows end to end, covering processes, channels, operators, configuration, testing, and deployment to HPC or cloud.
- ▌ Pi Agent · k-dense-ai bundleInstall, configure, and extend Pi, a terminal coding harness, with support for custom providers, models, extensions, skills, packages, themes, SDK integration, RPC mode, JSON event streams, and ecosystem packages for subagent delegation, MCP servers, interactive forms, and web access.
- ▌ Pydeseq2 · k-dense-ai bundlePerform differential gene expression analysis for bulk RNA-seq data using PyDESeq2, supporting formulaic designs, Wald tests, FDR correction, LFC shrinkage, and result visualization.
- ▌ Pyhealth · k-dense-ai bundleBuild clinical deep-learning pipelines with PyHealth: load EHR, signal, and imaging datasets, define prediction tasks, instantiate models, train with the PyHealth Trainer, and compute clinical metrics.
- ▌ Pymatgen · k-dense-ai bundleAnalyze and manipulate crystal structures, compute phase diagrams, and access the Materials Project database using the pymatgen library.
- ▌ Pyopenms · k-dense-ai bundleAnalyze proteomics and metabolomics mass spectrometry data with PyOpenMS: read/write MS file formats, process spectra, detect and quantify features, identify peptides and proteins, and run end-to-end LC-MS/MS pipelines using ready-to-run scripts.
- ▌ Pyzotero · k-dense-ai bundleManage Zotero reference libraries programmatically using the pyzotero Python client. Retrieve, create, update, and delete items, collections, tags, and attachments via the Zotero Web API v3.
- ▌ Tamarind · k-dense-ai bundleRun computational biology tools for protein structure prediction, design, docking, and molecular dynamics on managed cloud GPUs via REST API or MCP server.
- ▌ Autoskill · k-dense-ai bundleAnalyze recent screen activity via a local screenpipe daemon, detect repeated research workflows, and draft new skills or composition recipes for uncovered patterns.
- ▌ Biopython · k-dense-ai bundleManipulate biological sequences, parse FASTA/GenBank/PDB files, access NCBI databases, run BLAST searches, and perform phylogenetics using the Biopython library.
- ▌ Deeptools · k-dense-ai bundleProcess and analyze high-throughput sequencing data with deepTools for quality control, normalization, comparison, and publication-quality visualizations of ChIP-seq, RNA-seq, and ATAC-seq experiments.
- ▌ Geomaster · k-dense-ai bundleProcess satellite imagery, perform GIS analysis, and apply spatial machine learning across 70+ geospatial topics with code examples in 8 programming languages.
- ▌ Geopandas · k-dense-ai bundleExtends pandas for geospatial vector data analysis, including reading/writing shapefiles, GeoJSON, GeoPackage, and PostGIS, performing spatial joins, geometric operations, coordinate transformations, and creating static or interactive maps.
- ▌ Hypogenic · k-dense-ai bundleAutomates hypothesis generation and testing on tabular datasets using LLMs, combining data-driven discovery with literature integration for scientific research.
- ▌ Liteparse · k-dense-ai bundleParse PDFs, Office files, and images locally with layout-preserved text, bounding boxes, OCR, and page screenshots for RAG and multimodal agents.
- ▌ Pennylane · k-dense-ai bundleTrain quantum circuits like neural networks with automatic differentiation, device-independent programming, and integration with PyTorch or JAX.
- ▌ Pufferlib · k-dense-ai bundleTrain reinforcement learning agents at millions of steps per second using optimized PPO, vectorized environments, and multi-agent support.
- ▌ Esm · k-dense-ai bundleGenerate, predict, and embed protein sequences and structures using ESM3, ESMC, and ESMFold2 with local or cloud inference.
- ▌ PDF · k-dense-ai bundleRead, extract, merge, split, rotate, watermark, encrypt, and OCR PDF files using Python libraries and command-line tools.
- ▌ Aeon · k-dense-ai bundlePerform time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection, segmentation, and similarity search using a scikit-learn compatible Python toolkit.
- ▌ Bids · k-dense-ai bundleOrganize, query, validate, and convert neuroscience and biomedical data using the Brain Imaging Data Structure (BIDS) standard.
- ▌ Cirq · k-dense-ai bundleDesign, simulate, and run quantum circuits on Google Quantum AI hardware and partner backends using Cirq.
- ▌ Dask · k-dense-ai bundleScale pandas and NumPy workflows to larger-than-memory datasets using parallel and distributed computing.
- ▌ DOCX · k-dense-ai bundleCreate, read, edit, and manipulate Word documents (.docx) with formatting, tables, images, and tracked changes.
- ▌ Gget · k-dense-ai bundleQuery 20+ bioinformatics databases from the command line or Python for gene information, sequences, protein structures, enrichment analysis, and more.
- ▌ PPTX · k-dense-ai bundleCreate, read, edit, and convert .pptx presentations with design guidance, template manipulation, and visual QA workflows.
- ▌ Pymc · k-dense-ai bundleBuild, fit, validate, and compare Bayesian models using PyMC's modern API, including hierarchical models, MCMC sampling, variational inference, posterior predictive checks, and model comparison.
- ▌ Shap · k-dense-ai bundleExplain machine learning model predictions using SHAP values, compute feature importance, and generate visualizations including waterfall, beeswarm, bar, scatter, force, and heatmap plots.
- ▌ Vaex · k-dense-ai bundleProcess and analyze large tabular datasets (billions of rows) that exceed available RAM using lazy, out-of-core DataFrames with fast aggregations, visualization, and machine learning integration.
- ▌ XLSX · k-dense-ai bundleCreate, edit, analyze, or convert Excel spreadsheets (.xlsx, .xlsm) with formulas, formatting, financial models, and multi-sheet workbooks.
- ▌ Arbor · k-dense-ai bundleRun autonomous optimization loops that iteratively improve artifacts against evaluators using hypothesis tree refinement, without overfitting.
- ▌ Gtars · k-dense-ai bundleHigh-performance toolkit for genomic interval analysis in Rust with Python bindings. Use when working with genomic regions, BED files, coverage tracks, overlap detection, tokenization for ML models, or fragment analysis in computational genomics and machine learning applications.
- ▌ Modal · k-dense-ai bundleDeploy and serve AI/ML models on Modal's serverless cloud platform with on-demand GPUs, autoscaling containers, persistent storage, and scheduled jobs.
- ▌ Pysam · k-dense-ai bundleRead, write, and manipulate genomic datasets including SAM/BAM/CRAM alignments, VCF/BCF variants, and FASTA/FASTQ sequences using a Pythonic interface to htslib.
- ▌ Pytdc · k-dense-ai bundleAccess AI-ready drug discovery datasets and benchmarks from Therapeutics Data Commons, covering ADME, toxicity, drug-target interactions, and molecular generation with standardized splits and evaluation metrics.
- ▌ Qutip · k-dense-ai bundleSimulate and analyze open quantum systems using QuTiP, including master equations, Lindblad dynamics, decoherence, and quantum optics.
- ▌ Rdkit · k-dense-ai bundlePerform cheminformatics tasks including molecular I/O, descriptor calculation, fingerprinting, substructure search, and similarity analysis using the RDKit library.
- ▌ Rowan · k-dense-aiRun cloud-native molecular modeling and drug-design workflows including pKa prediction, docking, molecular dynamics, and protein-ligand cofolding via a Python API.
- ▌ Simpy · k-dense-ai bundleBuild discrete-event simulations of systems with processes, queues, resources, and time-based events using SimPy in Python.