Results for “ce”

Produces legally focused summaries of California Environmental Impact Reports (EIRs) under CEQA and federal Environmental Impact Statements (EISs) under NEPA. Extracts impacts, mitigation, alternatives, and compliance vulnerabilities. Reflects the 2025 CEQA reforms (AB 130 + SB 131) and the April 2025 rescission of CEQ NEPA implementing regulations. Triggers on requests for EIR/EIS summary, CEQA/NEPA review, mitigation analysis, alternatives analysis, cumulative impacts review, permit challenge prep, or administrative record review.

Creates .NET projects from templates with validated parameters, Central Package Management adaptation, and multi-project composition.

Single-cell RNA-seq analysis. Load .h5ad/10X data, QC, normalization, PCA/UMAP/t-SNE, Leiden clustering, marker genes, cell type annotation, trajectory, for scRNA-seq analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionali

Manim CE animations: 3Blue1Brown math/algo videos.

Manim CE animations: 3Blue1Brown math/algo videos.

Implements layered security for Flutter apps: code obfuscation, certificate pinning, secure storage, encryption, biometric authentication, and root/jailbreak detection.

Análise de RNA-seq de célula única. Carregue dados .h5ad/10X, QC, normalização, PCA/UMAP/t-SNE, clustering Leiden, genes marcadores, anotação de tipo celular, trajetória, para análise de scRNA-seq.

Build scalable Django 5.x applications with async views, DRF, Celery, and Channels, following best practices for architecture, testing, and deployment.

Run standard single-cell RNA-seq analysis pipelines: QC, normalization, dimensionality reduction, clustering, differential expression, and visualization using Scanpy.

Use to lock the single narrative arc before drafting — converts a set of correct results into one Cell-shaped story that runs hypothesis → mechanism → significance, not a list of experiments.

Evaluates central hypothyroidism (CH) patients for adrenal insufficiency (AI) prior to initiating levothyroxine (L‑T4) replacement. Triggers include consideration of L‑T4 start in central hypothyroidism needing thyroid replacement.

Generates CA and service certificates, then configures mutual TLS authentication between microservices using Python's cryptography and ssl modules.

Create, read, manipulate, and store annotated data matrices using the AnnData Python package, designed for single-cell genomics and general-purpose annotated data workflows.

Recommends using the lowest tolerable hydrocortisone dose to potentially decrease risks of metabolic and cardiovascular disease in central adrenal insufficiency. Triggers include managing a patient with central adrenal insufficiency requiring glucocorticoid replacement.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identific...

Use to structure a Cell Article and hold its length — Summary, Introduction, Results, Discussion, STAR Methods, figure legends, references — with main-text length and display-item budgets, and Results subheadings driving the single arc.

Configure cenci's neutral project core and generate Claude/Codex adapters.

Resolve cenci's neutral project configuration and shared guidance consistently.

Use to write Cell's Summary — a single unstructured paragraph of ≤ ~150 words that conveys the complete story, the mechanism, and the broad significance, quantified and readable by a general life-scientist. Late-stage polish.

This skill guides perioperative levothyroxine management for adults with preoperative central hypothyroidism undergoing non-emergency surgery. Trigger phrases include "preoperative central hypothyroidism patient requiring non-emergency surgery" and "use when managing preoperative CH patient".

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Determines levothyroxine dosing for central hypothyroidism to achieve serum free T4 in the mid to upper half of the reference range. Triggers include confirmed central hypothyroidism requiring thyroid hormone replacement when initiating L‑4 therapy.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.

Use to finalize Cell Press display items — column-width sizing, minimum fonts, RGB, show-the-data with defined error bars/n/replicate type, scale bars, colorblind-safe palettes, multi-panel discipline, stand-alone legends, and image integrity.

Scanpy is a scalable Python toolkit for analyzing single-cell RNA-seq data, built on AnnData. Apply this skill for complete single-cell workflows including quality control, normalization, dimensionality reduction, clustering, marker gene identification, visualization, and trajectory analysis.