medical-research-skills

Advanced sample size and power calculations for complex study designs including survival analysis, clustered designs, and multiple comparisons.

Use sanger chromatogram qa for data analysis workflows that need structured execution, explicit assumptions, and clear output boundaries.

Standard single-cell RNA-seq analysis pipeline. For quality control (QC), normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression analysis, and visualization. Best suited for exploratory single-cell transcriptomics analysis using established workflows. For deep learning models, use scvi-tools; for data format issues, use anndata.

Local schedule management for adding events, tracking deadlines, generating reminders, and detecting time conflicts when users need offline scheduling with optional popup notifications.

Implements the ScholarEval framework to evaluate scholarly documents; trigger when the user provides a PDF/DOCX/TXT file or pasted text and requests critique, scoring, or quality assessment.

Generates science popularization articles with titles and outlines based on medical topics and style preferences. Invoke when user needs to create medical/science popular content for public education.

Evaluate research rigor. Assess methodology, experimental design, statistical validity, biases, confounding, evidence quality (GRADE, Cochrane ROB), for critical analysis of scientific claims.

Automatically summarize scientific podcasts like Huberman Lab and Nature.

Automates publication-quality scientific diagrams (e.g., flowcharts, architectures, pathways) when you need journal/poster-ready visuals from a natural-language description.

A Python bioinformatics toolkit for sequence, phylogeny, and microbiome/community-ecology analysis; use it when you need to compute diversity/ordination/statistics from biological data and standard formats (FASTA/FASTQ/Newick/BIOM).

A comprehensive toolkit for survival analysis and time-to-event modeling in Python using scikit-survival; use it when you need to model censored time-to-event outcomes, fit Cox/RSF/GB models or Survival SVMs, evaluate with C-index/Brier score, or handle competing risks.

Simulates a strict SCI peer-review workflow; trigger when a user uploads or pastes a manuscript (PDF/DOC/DOCX/TXT) and requests an innovation score (1–12) plus experimental-logic vulnerability checks and revision suggestions.

Access Scite.ai Smart Citations to classify how a paper is cited (supporting, contrasting, mentioning) and assess scientific claims; use it when you need to evaluate a paper’s reliability or its acceptance in the literature.

Auto-annotate cell clusters from single-cell RNA data using marker genes.

Deep generative models for single-cell omics; use when you need probabilistic batch correction (scVI), transfer learning, uncertainty-aware differential expression, or multimodal integration (totalVI/MultiVI).

Extract hazard codes and safety info from chemical safety datasheets.

Statistical visualization library integrated with pandas; use it when you need fast EDA of distributions, relationships, and categorical comparisons (e.g., box/violin/pair plots and heatmaps) with strong default aesthetics on top of matplotlib.

An intelligent tool for precision medical literature search using PubMed's E-utilities API.

Use semantic consistency auditor for academic writing workflows that need structured execution, explicit assumptions, and clear output boundaries.

Access the Semantic Scholar Graph API to search papers and retrieve paper/author/citation data when you need literature discovery or citation graph exploration.