Results for “bed”

75 skills

Use when performing genome arithmetic on interval files (BED, BAM, BEDGRAPH), including intersection, merging, coverage, format conversion, or sequence extraction.

Access AWS Bedrock foundation models for generative AI, including text generation, embeddings, and image generation, with CLI and Python examples.

Train unsupervised machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

30.2k · bundle

superpowers-sage-install-plugin

Install WordPress plugins in Bedrock — lando composer require, Bedrock plugin management, composer.json for WP plugins, WP packagist, wpackagist-plugin, mu-plugins vs plugins, Bedrock plugin activation, composer.json repositories, lando wp plugin list, plugin compatibility, roots/wordpress-packagist

alterlab-geniml

Machine learning on genomic interval data (BED files) with the geniml Python package — region embeddings (Region2Vec), joint region+metadata embeddings (BEDspace/StarSpace), single-cell ATAC-seq embeddings (scEmbed), consensus peak sets / universes (build-universe), tokenization, BEDshift randomization, and BBClient/BEDbase caching. Use when training or using region/cell embeddings, clustering scATAC-seq, building a tokenization universe from BED collections, or any ML/feature-learning task over genomic regions. NOT for plain interval arithmetic (overlap/intersect/merge counts) — that is gtars, not geniml. Part of the AlterLab Academic Skills suite.

Controls an Eight Sleep smart bed pod from the command line, including temperature, alarms, schedules, audio, and base adjustments.

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Trains machine learning models on genomic interval data from BED files, including region embeddings, single-cell ATAC-seq analysis, and consensus peak building.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

metinduraktr-44

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspace), single-cell ATAC-seq analysis (scEmbed), building consensus peaks (universes), or any ML-based analysis of genomic regions. Applies to BED file collections, scATAC-seq data, chromatin accessibility datasets, and region-based genomic feature learning.

Essa habilidade deve ser usada ao trabalhar com dados de intervalos genômicos (arquivos BED) para tarefas de machine learning. Use para treinar embeddings de regiões (Region2Vec, BEDspace), análise de scATAC-seq de célula única (scEmbed), construir picos consensuais (universos), ou qualquer análise baseada em ML de regiões genômicas. Aplica-se a coleções de arquivos BED, dados scATAC-seq, conjuntos de dados de acessibilidade de cromatina e aprendizado de recursos genômicos baseado em regiões.

High-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.

High-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.

30.2k · bundle

Perform fast genomic interval operations (overlap, nearest, merge, coverage, cluster, complement, subtract, count-overlaps), multi-format bioinformatics I/O, DataFusion SQL, and pileup on Polars DataFrames via the polars-bio library, serving as a scalable alternative to bioframe and bedtools.

Perform high-performance genomic interval operations and bioinformatics file I/O on Polars DataFrames, including overlap, nearest, merge, coverage, complement, subtract, and reading/writing BED, VCF, BAM, GFF, FASTA, and FASTQ formats with streaming and cloud-native support.

30.2k · bundle

Use when profiling nucleotide content (AT/GC percentages, base counts) of genomic intervals against a FASTA reference.

arize-ai-provider-integration

Manage Arize AI integrations that store LLM provider credentials for evaluators and other features. Supports creating, reading, updating, and deleting integrations with providers like OpenAI, Anthropic, Azure OpenAI, AWS Bedrock, Vertex AI, Gemini, and NVIDIA NIM.

36.2k · bundle

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Version 2.35.0 | PRD to Production | Zero Human Intervention > Research-enhanced: OpenAI SDK, DeepMind, Anthropic, AWS Bedrock, Agent SDK, HN Production (2025)

Use Geniml for audited local genomic-interval workflows: validate BED and universe contracts, plan Region2Vec or scEmbed runs, inspect model/tokenizer compatibility, and assess consensus universes.

Use when you need to apply aggregation functions (sum, mean, count, etc.) to values from overlapping intervals in one file and map them onto intervals from another file.

bemdec-prescribing-guide

Bedside prescribing reference for Bemdec (bempedoic acid / NEXLETOL) — indication check, dose, statin co-prescribing safety caps, monitoring plan, warnings for hyperuricemia and tendon rupture, and special population guidance. Use when a clinician asks "can I start bempedoic acid", "Bemdec indication", "is bempedoic acid safe with my statin", "patient on Nexletol has joint pain or high uric acid", "bempedoic acid in CKD or liver disease or pregnancy", or any prescribing or monitoring question about bempedoic acid.

Control Eight Sleep pods (status, temperature, alarms, schedules).

Control Eight Sleep pods (status, temperature, alarms, schedules).

Control Eight Sleep pods (status, temperature, alarms, schedules).

BLE with Mbed OS. Bluetooth.

Control Eight Sleep pods (status, temperature, alarms, schedules).

ADC with Mbed OS. analog input.

Control Eight Sleep pods (status, temperature, alarms, schedules).

jrennie99-glitch

Control Eight Sleep pods (status, temperature, alarms, schedules).

tao-train-bevfusion

Trains, evaluates, and runs inference for BEVFusion multi-sensor 3D object detection models that fuse LiDAR and camera data in bird's-eye-view space for autonomous driving.

Track water and sleep with JSON file storage.

bmad-ml-research-party

Run multi-agent research discourse session. Use when the user requests to "start a research party" or "run a journal club".

Integrate the Anthropic Claude API in PHP projects using the official SDK, covering client setup, message requests, streaming, and tool use.