LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill biopython --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/biopythonContext preview
The summary Claude sees to decide when to auto-load this skill.
Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For
name: biopython description: "Primary retained Python toolkit for molecular biology sequence work. Preferred for sequence manipulation, FASTA/FASTQ/GenBank parsing, Bio.Entrez, BLAST workflows, alignments, structures, and phylogenetics. For biological database evidence lookup, use bio-database-evidence. For single-cell workflows use scanpy. For direct literature REST API, use pubmed-database."
Biopython is a comprehensive set of freely available Python tools for biological computation. It provides functionality for sequence manipulation, file I/O, database access, structural bioinformatics, phylogenetics, and many other bioinformatics tasks. The current version is **Biopython 1.85** (released January 2025), which supports Python 3 and requires NumPy.
Use this skill when:
Do not use this skill as a catch-all for single-cell analysis, bulk RNA-seq differential expression, biological database evidence tables, protein language model training, metabolic flux modeling, or flow-cytometry file parsing. Those surfaces are either owned by another retained bio-science skill or intentionally no longer exposed as separate bundled route owners.
Biopython is organized into modular sub-packages, each addressing specific bioinformatics domains:
1. **Sequence Handling** - Bio.Seq and Bio.SeqIO for sequence manipulation and file I/O 2. **Alignment Analysis** - Bio.Align and Bio.AlignIO for pairwise and multiple sequence alignments 3. **Database Access** - Bio.Entrez for programmatic access to NCBI databases 4. **BLAST Operations** - Bio.Blast for running and parsing BLAST searches 5. **Structural Bioinformatics** - Bio.PDB for working with 3D protein structures 6. **Phylogenetics** - Bio.Phylo for phylogenetic tree manipulation and visualization 7. **Advanced Features** - Motifs, population genetics, sequence utilities, and more
Install Biopython using pip (requires Python 3 and NumPy):
uv pip install biopython
For NCBI database access, always set your email address (required by NCBI):
from Bio import Entrez Entrez.email = "your.email@example.com" # Optional: API key for higher rate limits (10 req/s instead of 3 req/s) Entrez.api_key = "your_api_key_here"
This skill provides comprehensive documentation organized by functionality area. When working on a task, consult the relevant reference documentation:
**Reference:** `references/sequence_io.md`
Use for:
**Quick example:**
from Bio import SeqIO
# Read sequences from FASTA file
for record in SeqIO.parse("sequences.fasta", "fasta"):
print(f"{record.id}: {len(record.seq)} bp")
# Convert GenBank to FASTA
SeqIO.convert("input.gb", "genbank", "output.fasta", "fasta")**Reference:** `references/alignment.md`
Use for:
**Quick example:**
from Bio import Align
# Pairwise alignment
aligner = Align.PairwiseAligner()
aligner.mode = 'global'
alignments = aligner.align("ACCGGT", "ACGGT")
print(alignments[0])**Reference:** `references/databases.md`
Use for:
**Quick example:**
from Bio import Entrez
Entrez.email = "your.email@example.com"
# Search PubMed
handle = Entrez.esearch(db="pubmed", term="biopython", retmax=10)
results = Entrez.read(handle)
handle.close()
print(f"Found {results['Count']} results")**Reference:** `references/blast.md`
Use for:
**Quick example:**
from Bio.Blast import NCBIWWW, NCBIXML
# Run BLAST search
result_handle = NCBIWWW.qblast("blastn", "nt", "ATCGATCGATCG")
blast_record = NCBIXML.read(result_handle)
# Display top hits
for alignment in blast_record.alignments[:5]:
print(f"{alignment.title}: E-value={alignment.hsps[0].expect}")**Reference:** `references/structure.md`
Use for:
Intelligent Skill routing and workflow orchestration for AI agents — +21.12 pp reward, −29.6% tokens on SkillsBench with DeepSeekV4Flash-VE.
Repo: foryourhealth111-pixel/Vibe-Skills
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Cloud laboratory platform for automated protein testing and validation. Use when designing proteins and needing experimental validation including binding…
This skill should be used for time series machine learning tasks including classification, regression, clustering, forecasting, anomaly detection,…
Creating algorithmic art using p5.js with seeded randomness and interactive parameter exploration. Use this when users request creating art using code,…
Access real-time and historical stock market data, forex rates, cryptocurrency prices, commodities, economic indicators, and 50+ technical indicators via the…
Implement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex…