k-dense-ai
177 skills with substantive source documentation and an official publisher or observed installation demand. Read each skill’s original documentation through its card.
k-dense-aigenomic-coordinates
Converts genomic intervals between coordinate conventions, normalises and compares variant representations, and detects assembly or contig-naming mismatches before they corrupt an analysis. Used whenever coordinates cross a format, tool, or assembly boundary - converting between BED, GFF/GTF, VCF, SAM/BAM, WIG, PSL, genePred, Picard intervallist, or region strings; reconciling 0-based half-open with 1-based inclusive; left-aligning or trimming indels; checking whether two variant records describ
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aigenomic-intelligence
Predicts regulatory features, gene structure, and expression directly from DNA sequence using Genomic Intelligence's hosted transformer DNA language models — no local GPU or model weights. Six tasks over a REST API and a hosted MCP server (keyless public demo): promoter regions, splice donor/acceptor sites, enhancer activity, chromatin state, sequence-to-expression (log TPM), and de-novo gene annotation, plus a composite find-genes-then-predict-expression workflow. Use when the user has a gene s
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aigeomaster
Supports geospatial research workflows for remote sensing, vector and raster GIS, spatial statistics, terrain and network analysis, and machine learning for Earth observation. Use when processing satellite imagery, aligning coordinate systems and raster grids, accessing STAC catalogs, analyzing geospatial time series, or implementing scientific GIS workflows in Python, R, Julia, JavaScript, C++, Java, Go, or Rust.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aigeopandas
Guidance and local audit tools for Python workflows that directly use GeoPandas GeoSeries, GeoDataFrame, spatial operations, or vector-data I/O.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiget-available-resources
Detects host inventory and effective CPU, memory, disk, scheduler, container, and accelerator limits when a user asks for resource-aware planning or before a clearly resource-sensitive local workload. Produces a redacted JSON snapshot and conservative planning helpers without stress tests or assuming visible host hardware is usable.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aigget
Queries 20+ bioinformatics resources through CLI/Python. Supports quick lookups of gene info, BLAST/BLAT, viral sequence downloads, PDB/mmCIF structures, G2P residue annotations, enrichment analysis, OpenTargets, COSMIC, CELLxGENE, and 8cube mouse specificity/expression data. Best for interactive exploration and simple queries. For batch processing or advanced BLAST use biopython; for multi-database Python workflows use bioservices.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiginkgo-cloud-lab
Guides protocol selection, input preparation, pricing checks, and browser ordering on Ginkgo Bioworks Cloud Lab (cloud.ginkgo.bio). Applies to cell-free, E. coli, and Pichia protein expression; HiBiT, A280, and LabChip readouts; IVT mRNA/circRNA synthesis; thermal shift assays; Echo-MS methods; SPR target onboarding; plate-reader assay onboarding; and fluorescent pixel art.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiglycoengineering
Analyzes and engineers protein glycosylation by scanning canonical N-glycosylation sequons, describing S/T-rich regions, checking curated glycan evidence, and preparing NetNGlyc, NetOGlyc and GlycoSHIELD workflows. Use for glycoprotein engineering, antibody Fc glycosylation, glycan shielding, and site-specific glycoproteomics interpretation.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aigtars
Supports Gtars for local genomic interval models and set algebra, overlaps and counts, consensus and coverage, tokenization, fragment processing, and refget/BEDbase planning across Python, Rust, and the CLI.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aihistolab
Extracts and preprocesses whole-slide histology image tiles with Histolab. Use for WSI inspection, tissue masks, random/grid/score-based tile extraction, H&E stain normalization, and tile dataset preparation. For multiplexed imaging or deep learning inference pipelines, use pathml.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aihugging-science
Discovers and evaluates scientific datasets, models, methodology posts, and Spaces through the Hugging Science catalog. Used when selecting scientific ML resources in biology, chemistry, genomics, materials, climate, physics, astronomy, medicine, mathematics, protein design, single-cell analysis, or PDE modeling, and when checking their actual datasets, Transformers, native-runtime, Inference Providers, or Gradio interfaces.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aihypogenic
Plans and audits use of ChicagoHAI HypoGeniC/HypoRefine for LLM-assisted hypothesis generation from labeled text datasets. Use for the hypogenic package, its task configs, hypothesis banks, or HypoBench datasets—not for manual hypothesis formulation or scientific validation.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aihypothesis-generation
Formulates evidence-bounded scientific questions, candidate hypotheses, rival explanations, causal or associational claims, discriminating predictions, measurements, and preregistration-ready analysis plans. Used when turning observations or preliminary findings into transparent, testable research plans without treating hypotheses as facts.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiimaging-data-commons
Queries and downloads public cancer imaging data from NCI Imaging Data Commons. Supports IDC collection discovery, DICOM access, radiology (CT, MR, PET) and pathology AI datasets, metadata SQL, visualization, licensing, and citations. Uses public metadata and download routes without authentication; optional BigQuery and Google Healthcare routes require Google credentials.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiinfographics
Creates and reviews infographics with Nano Banana 2 via OpenRouter. Use for statistical summaries, timelines, comparisons, processes, and visual explanations with supplied data or optional Sonar research. Supports ten layouts, eight style presets, reference images, and accessible palette starting points.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aiiso-standards-readiness
Prepares and structurally reviews readiness evidence for ISO management-system and laboratory-competence standards - ISO 13485 medical device QMS, ISO 14971 device risk management, ISO/IEC 17025 testing and calibration laboratories, and ISO 15189 medical laboratories. Use when organizing declared scope, controlled documents, risk-management files, scope of accreditation, traceability, CAPA, external-provider controls, or bounded local evidence manifests, and when separating ISO certification fro
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailab-hardware-cad
Designs custom laboratory hardware as parametric build123d models and exports fabrication artifacts as STEP, STL, and DXF files - microfluidic chips and molds, optomechanical mounts and breadboard adapters, cuvette and microplate holders, tube racks, animal-behavior rigs, and 3D-printed instrument fixtures. Use when a research task needs a physical part that must mate with standardized labware, an optical table, a cage system, or a printer, CNC, or laser process.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailabarchive-integration
Integrates with the official LabArchives ELN REST-like API and Inventory API v1. Supports regional endpoint selection, signed-request construction, user authorization and UID flows, local LA container validation, and verified LabArchives integration workflows.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailamindb
Manages biological datasets and models with LaminDB, including artifact registration, lineage tracking, schema validation, Bionty ontology annotation, query/search, collections, branches, storage, and workflow integrations. Use for reproducible biological data curation or a LaminDB lakehouse.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailatchbio-integration
Builds, registers, debugs, and operates bioinformatics workflows on Latch using the Python SDK, CLI, Latch Data and Registry, Nextflow, Snakemake, programmatic execution, and Latch MCP. Use when authoring or deploying Latch workflows, configuring resources or interfaces, moving data, integrating Registry, or launching and monitoring runs.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailatex-posters
Creates research posters in LaTeX using beamerposter, tikzposter, or baposter. Use for conference posters, academic presentations, multi-column scientific layouts, figure integration, typography, compilation, and PDF preflight.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailiteparse
Local document and PDF parsing that returns spatial text with bounding boxes. Use for extracting text from PDFs, DOCX, Office files, and images; running OCR on scans; producing layout-preserved JSON for RAG; batch-ingesting folders of papers; or rendering pages to PNG for multimodal agents. Distinguishing capabilities are spatial text boxes, Markdown, page raster output, and local parsing with optional custom HTTP OCR.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-ailiterature-review
Conducts systematic, scoping, and narrative literature reviews using PubMed, arXiv, bioRxiv, Semantic Scholar, and other appropriate sources. Use for research synthesis, reproducible literature searches, screening, citation checking, or preparing Markdown and PDF reviews. Tracks search coverage, records versus studies, and evidence limitations; supports meta-analysis planning but does not supply a meta-analysis engine.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日
k-dense-aimageck
Analyzes pooled CRISPR screen FASTQ reads and guide-count matrices with MAGeCK, validates guide libraries and contrasts, measures replicate and library QC, and produces gene hit rankings with effect sizes and FDR. Use for new knockout, CRISPRi, or CRISPRa screen analysis, enrichment or depletion contrasts, and MAGeCK count/test workflows; existing public dependency-score lookup belongs to DepMap.
- 安装量
- 0
- GitHub Stars
- 5.5万
- 最近更新
- 10月19日