By AlterLab-IEU
Accelerates academic research and scientific writing with 180+ skills spanning literature search, systematic review, paper drafting (LaTeX/DOCX/PDF), peer review simulation, grant proposals, poster/slide creation, and bioinformatics data analysis (single-cell, genomics, proteomics, metabolomics, cheminformatics, clinical ML).
Build, slice, concatenate, read, and write AnnData annotated data matrices (obs, var, X, layers, obsm, uns) for single-cell analysis in the scverse ecosystem. Use when handling .h5ad files, managing cell and gene annotations, or wrangling single-cell matrices — this is the data-format skill, for analysis workflows use scanpy, for probabilistic models use scvi-tools, for population-scale queries use cellxgene-census. Part of the AlterLab Academic Skills suite.
Infer gene regulatory networks (GRNs) from expression matrices using arboreto's scalable GRNBoost2 and GENIE3 tree-ensemble algorithms with Dask-distributed computation. Use when analyzing bulk or single-cell RNA-seq transcriptomics to map transcription-factor-to-target-gene regulatory interactions, build adjacency networks, or run the GRN-inference step of a SCENIC pipeline on large datasets. Part of the AlterLab Academic Skills suite.
Manipulate biological sequences, parse FASTA/GenBank/PDB files, run phylogenetics, and access NCBI/PubMed programmatically via Biopython (Bio.SeqIO, Bio.Entrez, Bio.PDB, Bio.Blast). Use when scripting custom bioinformatics pipelines, batch-processing sequence files, automating BLAST, or fetching records from Entrez — for quick one-off database lookups use gget, for unified multi-service integration use bioservices. Part of the AlterLab Academic Skills suite.
Query 40+ bioinformatics web services through one consistent Python API with bioservices (UniProt, KEGG, ChEMBL, Reactome, Ensembl, NCBI and more). Use when a workflow must hit multiple databases together, map identifiers across services, or run cross-database analyses — for quick single-database lookups use gget, for sequence and file manipulation use biopython. Part of the AlterLab Academic Skills suite.
Query the CZ CELLxGENE Census (61M+ cells) programmatically via cellxgene-census and TileDB-SOMA, slicing expression by tissue, disease, or cell type and returning AnnData. Use when pulling reference single-cell RNA-seq data from the largest curated public atlas, running population-scale queries, or benchmarking your data against a reference — for analyzing your own dataset use scanpy or scvi-tools. Part of the AlterLab Academic Skills suite.
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📢 Featured in awesome-claude-skills (5.7k ⭐)
Organized across 13 research domains — from bioinformatics to digital humanities
Research Pipeline · Scientific Databases · Bioinformatics · Data Science · Visualization · Clinical Research · and more
Explore Skills » · Quick Start · Domain Overview · Contributing · Report Bug
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Built by AlterLab Creative Technologies Laboratory
Not tied to any specific university — these skills work for any researcher, anywhere. |
🎯Plug & PlayDrop a |
🧠Domain ExpertEach skill transforms Claude |
🔬Real FrameworksBuilt on actual scientific |
🌐UniversalWorks for any researcher |
General-purpose assistant for writing scientific papers, research, and technical documentation with academic rigor. Improves clarity and structure of scholarly work.
A growing collection of Claude-compatible academic workflow bundles. Covers scientific figures, manuscript writing and polishing, reviewer assessment, citation retrieval, data availability, paper reading, literature search, response letters, paper-to-PPTX conversion, and evidence-grounded Chinese invention patent drafting. Rules are organized as reusable skill folders with explicit workflows and quality checks.
Scientific research brainstorming partner: survey the literature, find good problems, and shape concrete research ideas together
Academic paper writing skills for ML conferences (NeurIPS, ICML, ICLR, AAAI)
Academic research agents — hypothesis generation, experiment design, paper drafting, peer review simulation, and more.
Production-grade academic research pipeline for Claude Code: research → write → review → revise → finalize. 4 skills, 27 modes, 39-agent ensemble, v3.7.3 + v3.8 L3 claim-faithfulness gate, v3.9.0 cross-index triangulation, v3.10 triangulation policy layer, v3.11 deterministic citation verification gate (#182).