本文へ移動
cccskills

「provides」の検索結果

1,616 件 ・ 関連度順

概要と使いどころ

PhIPData defines an S4 class for phage-immunoprecipitation sequencing (PhIP-seq) experiments. Buliding upon the RangedSummarizedExperiment class, PhIPData enables users to coordinate metadata with experimental data in analyses. Additionally, PhIPData provides specialized methods to subset and identify beads-only samples, subset objects using virus aliases, and use existing peptide libraries to populate object parameters.

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

MSnbase provides infrastructure for manipulation, processing and visualisation of mass spectrometry and proteomics data, ranging from raw to quantitative and annotated data.

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files. GDS is portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Client for the gypsum REST API (https://gypsum.artifactdb.com), a cloud-based file store in the ArtifactDB ecosystem. This package provides functions for uploads, downloads, and various adminstrative and management tasks. Check out the docu

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Extract the genomic locations of genes, transcripts, exons, introns, and CDS, for the gene models stored in a TxDb object. A TxDb object is a small database that contains the gene models of a given organism/assembly. Bioconductor provides a

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of st

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

This package supports functional characteristics of both coding and non-coding genomics data for thousands of species with up-to-date gene annotation. It provides a univeral interface for gene functional annotation from a variety of sources

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

This package is a implementation of biclustering ensemble method MoSBi (Molecular signature Identification from Biclustering). MoSBi provides standardized interfaces for biclustering results and can combine their results with a multi-algorithm ensemble approach to compute robust ensemble biclusters on molecular omics data. This is done by computing similarity networks of biclusters and filtering for overlaps using a custom error model. After that, the louvain modularity it used to extract biclus

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides efficient containers for storing and manipulating short genomic alignments (typically obtained by aligning short reads to a reference genome). This includes read counting, computing the coverage, junction detection, and working wit

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides delayed computation of a matrix of residuals after fitting a linear model to each column of an input matrix. Also supports partial computation of residuals where selected factors are to be preserved in the output matrix. Implements

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

HiContacts provides a collection of tools to analyse and visualize Hi-C datasets imported in R by HiCExperiment.

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA o

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. Here the ComplexHeatmap package provides a highly flexible way to arrange multiple heatmaps and supports various

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

BEER implements a Bayesian model for analyzing phage-immunoprecipitation sequencing (PhIP-seq) data. Given a PhIPData object, BEER returns posterior probabilities of enriched antibody responses, point estimates for the relative fold-change in comparison to negative control samples, and more. Additionally, BEER provides a convenient implementation for using edgeR to identify enriched antibody responses.

日本語の概要は準備中です。原文の説明を表示しています。

bioMate-AI/biomate-bioconductor-kb7962026年6月21日 更新

Provides guidance for writing and benchmarking optimized CUDA kernels for NVIDIA GPUs (H100, A100, T4) targeting HuggingFace diffusers and transformers libraries. Kernels must be kernel-builder/ABI3-compliant: no pybind11, no setup.py, TORCH_LIBRARY_EXPAND bindings only. Supports models like LTX-Video, Stable Diffusion, LLaMA, Mistral, and Qwen. Includes integration with HuggingFace Kernels Hub (get_kernel) for loading pre-compiled kernels. Includes benchmarking scripts to compare kernel performance against baseline implementations.

日本語の概要は準備中です。原文の説明を表示しています。

huggingface/kernels7702026年10月14日 更新

Provides guidance for writing, optimizing, and benchmarking C++ CPU kernels with SIMD intrinsics (AVX2/AVX512) for the Hugging Face kernels ecosystem. Includes a two-phase workflow: Phase 1 correctness (generic → AVX2) and Phase 2 performance exploration (AVX512 with branching trial loop), runtime CPU dispatch, OpenMP threading, and brgemm integration for GEMM-heavy kernels.

日本語の概要は準備中です。原文の説明を表示しています。

huggingface/kernels7702026年10月14日 更新

Provides guidance for writing, optimizing, and benchmarking Triton kernels for Intel XPU GPUs (Battlemage/Arc Pro B50) using the Xe-Forge optimization framework. Includes an LLM-driven trial-loop workflow (analyze, validate, benchmark, profile, finalize), XPU-specific patterns (tensor descriptors, GRF mode, tile swizzling), KernelBench fused kernels, and Flash Attention.

日本語の概要は準備中です。原文の説明を表示しています。

huggingface/kernels7702026年10月14日 更新

Provides guidance for writing and benchmarking optimized Triton kernels for AMD GPUs (MI355X, R9700) on ROCm, targeting HuggingFace diffusers (LTX-Video, SD3, FLUX) and transformers. Core kernels: RMSNorm, RoPE 3D, GEGLU, AdaLN. Includes XCD swizzle, autotune, diffusers integration patterns, and LTX-Video pipeline injection.

日本語の概要は準備中です。原文の説明を表示しています。

huggingface/kernels7702026年10月14日 更新

This skill should be used when searching for people/leads using the Prospeo Search Person API. It provides the correct API format, filter types, rate limiting patterns, and state-by-state crawling techniques to overcome the 25K result limit. Use when building lead lists, searching by job title/industry/location, or integrating with Prospeo.

日本語の概要は準備中です。原文の説明を表示しています。

growthenginenowoslawski/coldoutboundskills7642026年10月6日 更新

Detect potential code-level performance smells in Java - streams, collections, boxing, regex, object creation. Provides awareness, not absolutes - always measure before optimizing. For JPA/database performance, use jpa-patterns instead.

日本語の概要は準備中です。原文の説明を表示しています。

decebals/claude-code-java7502026年9月7日 更新

Full brand naming workflow for founders, agencies, and businesses. Use this skill whenever the user says "help me name this brand", "brand naming", "I need a name for", "name ideas for", "what should I call my brand/company/product", "naming a startup", "brand name suggestions", "help with naming", or shares a brand brief and asks for name options. Also triggers when the user shares existing name options and asks for feedback, evaluation, ranking, or scoring of those names. Auto-detects whether to run the full generation workflow or the evaluation workflow based on what the user provides. Always use this skill for any brand or product naming task — even if the user just casually mentions needing a name.

日本語の概要は準備中です。原文の説明を表示しています。

arnabbagxd/Brand-building-skills7442026年6月13日 更新

Creates and manages reusable character profiles (Soul IDs) for consistent facial and stylistic identity across multiple image and video generations. Provides identity-vs-motion prompt separation, character sheet creation workflows, micro-expression direction, and Soul Cast AI actor configuration. Use when the user wants to maintain character consistency across multiple generations, asks about Soul ID, creating reusable characters, or generating consistent people across different scenes and shots.

日本語の概要は準備中です。原文の説明を表示しています。

OSideMedia/higgsfield-ai-prompt-skill7402026年9月27日 更新

seo-audit

無料

Run a full technical and on-page SEO audit on any website or page. Use when the user says "audit my site", "SEO check", "technical SEO review", "site health", "check my SEO", "what's wrong with my site", or provides a URL and asks for SEO feedback.

日本語の概要は準備中です。原文の説明を表示しています。

OpenClaudia/openclaudia-skills7152026年10月11日 更新