其他生物科学家

Life Scientists

其他生物科学家(Life Scientists)相关 AI Agent 技能。支持 Claude Code / Cursor 一键安装。

⭐ 该职业下的热门技能

research-paper-writing.md ★ 187.8k
from "NousResearch"
Write ML papers for NeurIPS/ICML/ICLR: design→submit.
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claude-scientific-skills.md ★ 37.8k
from "sickn33"
Scientific research and analysis skills
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pubmed-database.md ★ 37.8k
from "sickn33"
Direct REST API access to PubMed. Advanced Boolean/MeSH queries, E-utilities API, batch processing, citation management. For Python workflows, prefer biopython
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scanpy.md ★ 23.7k
from "K-Dense-AI"
Standard single-cell RNA-seq analysis pipeline. Use for QC, normalization, dimensionality reduction (PCA/UMAP/t-SNE), clustering, differential expression, and v
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diffdock.md ★ 23.7k
from "K-Dense-AI"
Diffusion-based molecular docking. Predict protein-ligand binding poses from PDB/SMILES, confidence scores, virtual screening, for structure-based drug design.
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lamindb.md ★ 23.7k
from "K-Dense-AI"
This skill should be used when working with LaminDB, an open-source data framework for biology that makes data queryable, traceable, reproducible, and FAIR. Use
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deeptools.md ★ 23.7k
from "K-Dense-AI"
NGS analysis toolkit. BAM to bigWig conversion, QC (correlation, PCA, fingerprints), heatmaps/profiles (TSS, peaks), for ChIP-seq, RNA-seq, ATAC-seq visualizati
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scikit-bio.md ★ 23.7k
from "K-Dense-AI"
Biological data toolkit. Sequence analysis, alignments, phylogenetic trees, diversity metrics (alpha/beta, UniFrac), ordination (PCoA), PERMANOVA, FASTA/Newick
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arboreto.md ★ 23.7k
from "K-Dense-AI"
Infer gene regulatory networks (GRNs) from gene expression data using scalable algorithms (GRNBoost2, GENIE3). Use when analyzing transcriptomics data (bulk RNA
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scientific-schematics.md ★ 23.7k
from "K-Dense-AI"
Create publication-quality scientific diagrams using Nano Banana 2 AI with smart iterative refinement. Uses Gemini 3.1 Pro Preview for quality review. Only rege
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scientific-critical-thinking.md ★ 23.7k
from "K-Dense-AI"
Evaluate scientific claims and evidence quality. Use for assessing experimental design validity, identifying biases and confounders, applying evidence grading f
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hypothesis-generation.md ★ 23.7k
from "K-Dense-AI"
Structured hypothesis formulation from observations. Use when you have experimental observations or data and need to formulate testable hypotheses with predicti
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geniml.md ★ 23.7k
from "K-Dense-AI"
This skill should be used when working with genomic interval data (BED files) for machine learning tasks. Use for training region embeddings (Region2Vec, BEDspa
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open-notebook.md ★ 23.7k
from "K-Dense-AI"
Self-hosted, open-source alternative to Google NotebookLM for AI-powered research and document analysis. Use when organizing research materials into notebooks,
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phylogenetics.md ★ 23.7k
from "K-Dense-AI"
Build and analyze phylogenetic trees using MAFFT (multiple alignment), IQ-TREE 2 (maximum likelihood), and FastTree (fast NJ/ML). Visualize with ETE3 or FigTree
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