ReddRadar
Agent skill
bio-restriction-mapping
Install this agent skill to your Project
npx add-skill https://github.com/FreedomIntelligence/OpenClaw-Medical-Skills/tree/main/skills/bio-restriction-mapping
SKILL.md
name: bio-restriction-mapping description: Create restriction maps showing enzyme cut positions on DNA sequences using Biopython Bio.Restriction. Visualize cut sites, calculate distances between sites, and generate text or graphical maps. Use when creating or analyzing restriction maps. tool_type: python primary_tool: Bio.Restriction measurable_outcome: Execute skill workflow successfully with valid output within 15 minutes. allowed-tools:
- read_file
- run_shell_command
Restriction Mapping
Create Basic Restriction Map
from Bio import SeqIO
from Bio.Restriction import EcoRI, BamHI, HindIII, RestrictionBatch, Analysis
record = SeqIO.read('sequence.fasta', 'fasta')
seq = record.seq
batch = RestrictionBatch([EcoRI, BamHI, HindIII])
analysis = Analysis(batch, seq)
# Print formatted map
analysis.print_as('map')
Output Formats
# Map format (visual)
analysis.print_as('map')
# Linear format (list)
analysis.print_as('linear')
# Tabular format
analysis.print_as('tabulate')
# Get as string instead of printing
map_str = analysis.format_as('map')
linear_str = analysis.format_as('linear')
Calculate Distances Between Sites
from Bio.Restriction import EcoRI, BamHI
ecori_sites = EcoRI.search(seq)
bamhi_sites = BamHI.search(seq)
# All cut positions sorted
all_sites = sorted(ecori_sites + bamhi_sites)
# Calculate distances between consecutive sites
distances = []
for i in range(len(all_sites) - 1):
dist = all_sites[i + 1] - all_sites[i]
distances.append((all_sites[i], all_sites[i + 1], dist))
print(f'{all_sites[i]} -> {all_sites[i + 1]}: {dist} bp')
Create Detailed Restriction Map
from Bio import SeqIO
from Bio.Restriction import RestrictionBatch, Analysis
from Bio.Restriction import EcoRI, BamHI, HindIII, XhoI, NotI
record = SeqIO.read('plasmid.fasta', 'fasta')
seq = record.seq
seq_len = len(seq)
enzymes = RestrictionBatch([EcoRI, BamHI, HindIII, XhoI, NotI])
analysis = Analysis(enzymes, seq, linear=False)
print(f'Restriction Map: {record.id}')
print(f'Length: {seq_len} bp (circular)')
print('=' * 50)
results = analysis.full()
all_cuts = []
for enzyme, sites in results.items():
for site in sites:
all_cuts.append((site, str(enzyme)))
all_cuts.sort(key=lambda x: x[0])
print('\nCut sites (5\' -> 3\'):')
for pos, enz in all_cuts:
pct = (pos / seq_len) * 100
print(f' {pos:6d} bp ({pct:5.1f}%) - {enz}')
Text-Based Map Visualization
def draw_restriction_map(seq, results, width=80):
'''Draw a simple text restriction map'''
seq_len = len(seq)
scale = width / seq_len
# Header
print(f'0{" " * (width - 6)}{seq_len}')
print('|' + '-' * (width - 2) + '|')
# Plot each enzyme
for enzyme, sites in results.items():
if not sites:
continue
line = [' '] * width
for site in sites:
pos = int(site * scale)
if pos >= width:
pos = width - 1
line[pos] = '|'
print(''.join(line) + f' {enzyme}')
print('|' + '-' * (width - 2) + '|')
# Usage
batch = RestrictionBatch([EcoRI, BamHI, HindIII])
analysis = Analysis(batch, seq)
results = analysis.full()
draw_restriction_map(seq, results)
Map with GenBank Features
from Bio import SeqIO
from Bio.Restriction import RestrictionBatch, Analysis, EcoRI, BamHI
record = SeqIO.read('plasmid.gb', 'genbank')
seq = record.seq
enzymes = RestrictionBatch([EcoRI, BamHI])
analysis = Analysis(enzymes, seq, linear=False)
results = analysis.full()
print('Restriction Sites and Overlapping Features:')
print('=' * 60)
for enzyme, sites in results.items():
for site in sites:
print(f'\n{enzyme} at position {site}:')
for feature in record.features:
start = int(feature.location.start)
end = int(feature.location.end)
if start <= site <= end:
feat_type = feature.type
label = feature.qualifiers.get('label', feature.qualifiers.get('gene', ['unknown']))[0]
print(f' Within {feat_type}: {label} ({start}-{end})')
Export Map to File
def export_restriction_map(seq, results, output_file, seq_name='sequence'):
'''Export restriction map to text file'''
with open(output_file, 'w') as f:
f.write(f'Restriction Map: {seq_name}\n')
f.write(f'Length: {len(seq)} bp\n')
f.write('=' * 50 + '\n\n')
all_cuts = []
for enzyme, sites in results.items():
for site in sites:
all_cuts.append((site, str(enzyme)))
all_cuts.sort()
f.write('Site\tPosition\tFrom_Start\n')
for pos, enz in all_cuts:
f.write(f'{enz}\t{pos}\t{pos}\n')
f.write('\n\nFragment sizes between sites:\n')
if all_cuts:
positions = sorted([c[0] for c in all_cuts])
for i in range(len(positions) - 1):
size = positions[i + 1] - positions[i]
f.write(f'{positions[i]} -> {positions[i + 1]}: {size} bp\n')
# Usage
export_restriction_map(seq, results, 'restriction_map.txt', record.id)
Circular Map Coordinates
def circular_distances(sites, seq_len):
'''Calculate fragment sizes for circular DNA'''
if not sites:
return []
sites = sorted(sites)
fragments = []
# Between consecutive sites
for i in range(len(sites) - 1):
fragments.append(sites[i + 1] - sites[i])
# Wrap-around fragment
wrap = (seq_len - sites[-1]) + sites[0]
fragments.append(wrap)
return fragments
# Usage
ecori_sites = EcoRI.search(seq, linear=False)
fragments = circular_distances(ecori_sites, len(seq))
print(f'EcoRI fragments (circular): {fragments}')
Related Skills
- restriction-sites - Find where enzymes cut
- enzyme-selection - Choose enzymes for mapping
- fragment-analysis - Analyze fragment sizes
Recommended Agent Skills
Expand your agent's capabilities with these related and highly-rated skills.
FreedomIntelligence/OpenClaw-Medical-Skills
vcf-annotator
Annotate VCF variants with VEP, ClinVar, gnomAD frequencies, and ancestry-aware context. Generates prioritised variant reports.
FreedomIntelligence/OpenClaw-Medical-Skills
chemist-analyst
Analyzes events through chemistry lens using molecular structure, reaction mechanisms, thermodynamics, kinetics, and analytical techniques (spectroscopy, chromatography, mass spectrometry). Provides insights on chemical processes, material properties, reaction pathways, synthesis, and analytical methods. Use when: Chemical reactions, material analysis, synthesis planning, process optimization, environmental chemistry. Evaluates: Molecular structure, reaction mechanisms, yield, selectivity, safety, environmental impact.
FreedomIntelligence/OpenClaw-Medical-Skills
bio-alignment-io
Read, write, and convert multiple sequence alignment files using Biopython Bio.AlignIO. Supports Clustal, PHYLIP, Stockholm, FASTA, Nexus, and other alignment formats for phylogenetics and conservation analysis. Use when reading, writing, or converting alignment file formats.
FreedomIntelligence/OpenClaw-Medical-Skills
sleep-analyzer
分析睡眠数据、识别睡眠模式、评估睡眠质量，并提供个性化睡眠改善建议。支持与其他健康数据的关联分析。
FreedomIntelligence/OpenClaw-Medical-Skills
metabolomics-workbench-database
Access NIH Metabolomics Workbench via REST API (4,200+ studies). Query metabolites, RefMet nomenclature, MS/NMR data, m/z searches, study metadata, for metabolomics and biomarker discovery.
FreedomIntelligence/OpenClaw-Medical-Skills
bio-hi-c-analysis-matrix-operations
Balance, normalize, and transform Hi-C contact matrices using cooler and cooltools. Apply iterative correction (ICE), compute expected values, and generate observed/expected matrices. Use when normalizing or transforming Hi-C matrices.
Didn't find tool you were looking for?