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Agent skill

Bio Restriction Mapping

by GPTomics in GPTomics/bioSkills

Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction.

MITAuto-check passedResearch & Science

Install Bio Restriction Mapping

skills CLI
$ npx skills add GPTomics/bioSkills --skill bio-restriction-mapping -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install GPTomics/bioSkills bio-restriction-mapping --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/GPTomics/bioSkills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/restriction-analysis/restriction-mapping .claude/skills/bio-restriction-mapping && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
bio-restriction-mapping
GitHub stars
1.2k
Used in
1 other repo
Token cost
~2.3k tokens
SKILL.md length
774 words
Files
4
Skills in repo
552
Repo updated
First seen
Licence
MIT

At a glance

Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction.

  • Creating a restriction map of a sequence
  • SKILL.md covers Version Compatibility, Choosing The Map Representation, Quick Text Map and Ordered Site List With Distances, plus 7 more sections
  • Runs Python scripts from its folder; calls pip
  • Ordering cut sites along a plasmid

What it does

Bio Restriction Mapping is an agent skill from GPTomics/bioSkills. Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction. Produces text or graphical maps for linear and circular molecules, orders sites from single and double digests, and overlays GenBank features. Use when creating a restriction map of a sequence, ordering cut sites along a plasmid, or relating sites to annotated features.

Its SKILL.md is about 2.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 4 other files (for example `examples/create_map.py`, `examples/plasmid_map.py` and `usage-guide.md`).

It sits in Research & Science, covering Bioinformatics. It works with NCBI, Biopython and Matplotlib. The repository describes itself as: a set of SKILLS.md for doing bioinformatics with agents like claude code. The licence is MIT.

When your agent uses it

  • Creating a restriction map of a sequence
  • Ordering cut sites along a plasmid
  • Relating sites to annotated features

Example prompts

  • “/bio-restriction-mapping”

Requirements

  • Python 3

What it can do on your machine

Read from SKILL.md and the folder at commit d91ed3d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships script files (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use pip, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Bio Restriction Mapping loads about 2.3k tokens when it runs. Until then it costs about 104 tokens; SKILL.md has 774 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~104
When it runs · the whole SKILL.md, loaded when a task matches
~2.3k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from GPTomics/bioSkills at commit d91ed3d, republished under its MIT licence (© GPTomics). 774 words, ~2,298 tokens.

Download SKILL.mdSave it as .claude/skills/bio-restriction-mapping/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
bio-restriction-mapping
description
Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction. Produces text or graphical maps for linear and circular molecules, orders sites from single and double digests, and overlays GenBank features. Use when creating a restriction map of a sequence, ordering cut sites along a plasmid, or relating sites to annotated features.
tool_type
python
primary_tool
Bio.Restriction

Version Compatibility

Reference examples tested with: BioPython 1.83+ (API verified on 1.86), matplotlib 3.7+

Before using code patterns, verify installed versions match. If versions differ:

  • Python: pip show biopython then help(Bio.Restriction.Analysis.print_as) to confirm format names

If code throws ImportError, AttributeError, or TypeError, introspect the installed package and adapt the example to match the actual API rather than retrying.

Restriction Mapping

"Make a restriction map of my sequence" -> Place each enzyme's cut sites along the molecule, in order, with the distances between them and (for plasmids) the wrap-around fragment.

  • Python: Bio.Restriction.Analysis(...).print_as('map') for a quick text map; search() positions + matplotlib for a graphical one.

A map is more than a list of positions: it is the ordering and spacing of sites, and on a plasmid the ordering is circular. Two things separate a correct map from a wrong one. First, a circular molecule wraps: the fragment between the last site and the first crosses the origin, so its length is (seq_len - last) + first, not seq_len - last. Second, when sites come from a gel rather than a known sequence, order is deduced, not given -- single digests give sizes, and only comparing single vs double digests (or partial digests) orders them.

Choosing The Map Representation

NeedRepresentationHow
Quick look while exploringText mapAnalysis.print_as('map') / 'linear'
Capture to a string/reportFormatted textAnalysis.format_output()
Publication / slide figureGraphical mapsearch() positions drawn with matplotlib
Sites vs annotated featuresFeature overlayiterate record.features against each cut position
Ordering sites from a gelDigest comparisonsingle vs double (or partial) digest fragment patterns

Quick Text Map

python
from Bio import SeqIO
from Bio.Restriction import EcoRI, BamHI, HindIII, RestrictionBatch, Analysis

record = SeqIO.read('sequence.fasta', 'fasta')
analysis = Analysis(RestrictionBatch([EcoRI, BamHI, HindIII]), record.seq)

analysis.print_as('map'); analysis.print_that()      # visual map to stdout
analysis.print_as('linear'); analysis.print_that()   # linear list
report = analysis.format_output()                    # capture as a string (not format_as)

Ordered Site List With Distances

Goal: A single ordered table of every cut, which enzyme made it, and the distance to the next.

Approach: Collect (position, enzyme) from Analysis.full(), sort by position, and walk the list. For circular DNA, close the loop with the wrap-around span.

python
from Bio.Restriction import RestrictionBatch, Analysis, EcoRI, BamHI, HindIII, XhoI, NotI

seq = record.seq
seq_len = len(seq)
circular = False    # set True for a plasmid (and use linear=not circular below)

analysis = Analysis(RestrictionBatch([EcoRI, BamHI, HindIII, XhoI, NotI]), seq, linear=not circular)
cuts = sorted((pos, str(enz)) for enz, sites in analysis.full().items() for pos in sites)

for i, (pos, enz) in enumerate(cuts):
    nxt = cuts[(i + 1) % len(cuts)][0]
    span = (nxt - pos) if nxt > pos else (seq_len - pos) + nxt   # wrap on circular
    last = (i == len(cuts) - 1)
    dist = span if (circular or not last) else seq_len - pos
    print(f'{pos:6d} bp ({pos / seq_len:5.1%}) {enz:8s} -> next in {dist} bp')

Graphical Map (matplotlib)

Goal: A figure with the molecule as an axis and a labeled tick per cut site.

Approach: Draw the backbone, place a vertical tick at each search() position, and stack enzymes on separate rows. Write the figure only to a path the caller names (so running this does not litter the working directory).

python
import matplotlib
matplotlib.use('Agg')                  # headless; no display needed
import matplotlib.pyplot as plt
from Bio.Restriction import EcoRI, BamHI, HindIII

def draw_map(seq, enzymes, out_path):
    seq_len = len(seq)
    fig, ax = plt.subplots(figsize=(10, 2 + 0.4 * len(enzymes)))
    ax.hlines(0, 0, seq_len, color='black')
    for row, enz in enumerate(enzymes, start=1):
        for pos in enz.search(seq):
            ax.vlines(pos, row - 0.3, row + 0.3, color='C0')
            ax.text(pos, row + 0.35, str(pos), ha='center', va='bottom', fontsize=7)
        ax.text(-0.02 * seq_len, row, str(enz), ha='right', va='center')
    ax.set_xlim(0, seq_len); ax.set_yticks([]); ax.set_xlabel('position (bp)')
    fig.savefig(out_path, dpi=200, bbox_inches='tight'); plt.close(fig)

# draw_map(record.seq, [EcoRI, BamHI, HindIII], 'my_map.png')   # caller supplies the path

Map Against GenBank Features

python
from Bio import SeqIO
from Bio.Restriction import RestrictionBatch, Analysis, EcoRI, BamHI

record = SeqIO.read('plasmid.gb', 'genbank')
analysis = Analysis(RestrictionBatch([EcoRI, BamHI]), record.seq, linear=False)

for enzyme, sites in analysis.with_sites().items():
    for pos in sites:
        hits = [f.qualifiers.get('label', f.qualifiers.get('gene', [f.type]))[0]
                for f in record.features
                if int(f.location.start) <= pos <= int(f.location.end)]
        print(f'{enzyme} at {pos}: {", ".join(hits) or "intergenic"}')
Show full SKILL.md (409 more words)Show less

Ordering Sites From A Gel (Classical Mapping)

When the sequence is unknown, a map is reconstructed from fragment sizes, not read off positions. The logic, in order of power:

  • Single digest gives fragment sizes but not their order. A circular molecule cut n times gives n fragments; a linear one gives n+1.
  • Double digest orders sites: run enzyme A alone, B alone, and A+B together. A single-digest fragment that disappears and is replaced by two smaller ones in the double digest contains a B site, which is thereby located inside that fragment. Iterate, enforcing that all fragment sizes sum to the molecule length. In practice one enzyme pair often admits several orderings consistent with the same band sizes (co-migrating or symmetric fragments); resolving a unique map needs additional enzymes or the partial-digest method below.
  • Partial digest with end labeling (Smith-Birnstiel) measures positions directly: label one end, cut only a random subset of sites, and each labeled partial runs from the labeled end to one site, so its size is that site's distance from the labeled end. This sidesteps the combinatorial ambiguity of double digests.

Maps from one enzyme pair are often ambiguous (co-migrating or symmetric fragments fit multiple orderings); resolving a unique map needs several enzymes and the sum-of-fragments constraint.

Circular Fragment Distances

python
def circular_distances(sites, seq_len):
    '''Fragment sizes around a circle from sorted cut positions.'''
    s = sorted(sites)
    spans = [s[i + 1] - s[i] for i in range(len(s) - 1)]
    return spans + [(seq_len - s[-1]) + s[0]]    # the wrap-around fragment closes the circle

frags = circular_distances(EcoRI.search(record.seq, linear=False), len(record.seq))
assert sum(frags) == len(record.seq)             # the circle must be fully accounted for

Common Errors

SymptomCauseFix
AttributeError: ... 'format_as'Method is format_outputUse Analysis.format_output() to get the text as a string
Wrap-around fragment is too short on a plasmidUsed seq_len - last_site instead of (seq_len - last) + firstClose the circle across the origin
Site near the origin missing on a plasmid mapBuilt the map with linear=TruePass linear=False for circular DNA
Running a mapping script litters PNG/TXT filesWrote outputs to a hard-coded filenameWrite only to a path the caller supplies (or a temp dir)
Two enzymes' sites cannot be ordered from one gelSingle digest gives sizes, not orderAdd a double digest (or partial-digest end-labeling) and use the sum check
  • restriction-sites - Find the cut positions a map is built from
  • fragment-analysis - Fragment sizes and gel interpretation behind classical mapping
  • enzyme-selection - Choose informative enzymes for a map
  • data-visualization/genome-tracks - Richer graphical layouts for annotated maps
  • sequence-io/read-sequences - Load FASTA or GenBank input

References

  • Smith HO, Birnstiel ML. A simple method for DNA restriction site mapping. Nucleic Acids Res. 1976;3(9):2387-2398. doi:10.1093/nar/3.9.2387
  • Roberts RJ, Vincze T, Posfai J, Macelis D. REBASE: a database for DNA restriction and modification: enzymes, genes and genomes. Nucleic Acids Res. 2023;51(D1):D629-D630. doi:10.1093/nar/gkac975

© GPTomics, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files in restriction-analysis/restriction-mapping of GPTomics/bioSkills.

  • SKILL.md
  • examples/create_map.py
  • examples/plasmid_map.py
  • usage-guide.md

Open the folder on GitHubat commit d91ed3d

Used in 1 other repository

We found 1 copy of this SKILL.md (exact, near-identical or edited) in other folders, from 1 other GitHub owner. This page covers the copy in GPTomics/bioSkills, which our catalogue first saw on October 7, 2026.

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Works with

Categories

Questions about Bio Restriction Mapping

What does Bio Restriction Mapping do?

Build restriction maps showing enzyme cut positions and inter-site distances along DNA using Biopython Bio.Restriction. Bio Restriction Mapping is an agent skill from GPTomics/bioSkills.Restriction.

When should I use Bio Restriction Mapping?

Bio Restriction Mapping fits situations like: creating a restriction map of a sequence; ordering cut sites along a plasmid; relating sites to annotated features.

How do I install Bio Restriction Mapping in Claude Code?

Run `npx skills add GPTomics/bioSkills --skill bio-restriction-mapping -a claude-code`. Or copy the skill folder (restriction-analysis/restriction-mapping in GPTomics/bioSkills) into .claude/skills/bio-restriction-mapping in your project. Claude Code loads it when a task matches its description.

How do I install Bio Restriction Mapping in Codex?

Run `npx skills add GPTomics/bioSkills --skill bio-restriction-mapping -a codex`. Or copy the skill folder (restriction-analysis/restriction-mapping in GPTomics/bioSkills) into .agents/skills/bio-restriction-mapping in your project. Codex loads it when a task matches its description.

Can I use Bio Restriction Mapping in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add GPTomics/bioSkills --skill bio-restriction-mapping -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/bio-restriction-mapping, .gemini/skills/bio-restriction-mapping, .github/skills/bio-restriction-mapping and .opencode/skills/bio-restriction-mapping in your project.

What does Bio Restriction Mapping need to run?

Going by SKILL.md and its folder, Bio Restriction Mapping needs Python for the scripts in its folder and the command-line tools its instructions call (pip). Our summary lists: Python 3.

Does Bio Restriction Mapping access the network?

SKILL.md contains no URLs. Its commands use pip, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Bio Restriction Mapping safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Bio Restriction Mapping use?

Bio Restriction Mapping is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Bio Restriction Mapping use?

About 2.3k tokens (SKILL.md is roughly 9.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Bio Restriction Mapping?

Skills that share tags, products or a category with Bio Restriction Mapping: Biopython Sequence Io (aipoch/medical-research-skills, 2k stars), Biopython Bioinformatics (aiming-lab/AutoResearchClaw, 15k stars), Biopython (davila7/claude-code-templates, 32k stars) and Biopython (K-Dense-AI/scientific-agent-skills, 48k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Bio Restriction Mapping?

GPTomics (a GitHub organization) maintains it in GPTomics/bioSkills, which has 1,215 GitHub stars. The repository holds 552 skills in this directory. The repository was last updated on August 15, 2026.

Source: GPTomics/bioSkills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.