Skip to content
TrustedSkillsbeta
Back to all skills

Scikit Bio

Listed
davila7·vlatest·ai-ml·MIT

Scikit Bio analyzes biological sequences (DNA, RNA, protein) using scikit-learn for pattern recognition and prediction – useful for bioinformatics research.

Repository

Install on your platform

Showing Claude Code. One command installs this skill into any of the agents below.

  1. 1

    Run this in your project

    terminal
    $ npx skills add davila7/claude-code-templates --skill scikit-bio -a claude-code

  2. Uses the open-source skills CLI and needs Node.js. Add -g to install it for your user instead of this project.

What we know about this skill

Publisher

davila7

Taken from the source listing. We haven't verified who controls this account.

Install target

Live repository

Not pinned. Installing fetches whatever the repository holds at the time you run the command.

Nobody has reviewed this code. TrustedSkills indexes and links skills; it does not audit, run or scan them. A skill runs with whatever access you give your agent — read the source before you install it.

Automated safety checks

scanned

We could not read this skill's source, so none of the checks below were run.

Not scanned. none of the 457 skills in the repository match this slug — it was most likely renamed or removed upstream after the registry indexed it Source recorded as davila7/claude-code-templates.
This is a static scan, not a review. It reads the skill's files; it does not run them, and it cannot tell you whether the skill is any good or whether the code does what its description says. A skill runs with whatever access you give your agent.
What each check looks for →

About this skill

What it does

The Scikit Bio skill enables AI agents to analyze biological data using the scikit-bio Python library. It facilitates tasks such as manipulating DNA, RNA, and protein sequences; reading and writing various biological file formats (FASTA, FASTQ, GenBank); performing sequence alignments; constructing phylogenetic trees; and calculating diversity metrics for microbiome or community ecology data. This skill is particularly useful for bioinformatics research requiring pattern recognition and prediction within biological datasets.

When to use it

  • You need to read and process biological sequences from files in formats like FASTA or FASTQ.
  • You're performing sequence alignment or searching for specific motifs within DNA, RNA, or protein data.
  • You want to construct or analyze phylogenetic trees representing evolutionary relationships.
  • You are calculating diversity metrics (alpha/beta diversity, UniFrac distances) from microbiome data.

Key capabilities

  • Sequence Manipulation: Reading, writing, slicing, concatenating, and searching biological sequences (DNA, RNA, protein).
  • File Format Support: Handles FASTA, FASTQ, GenBank, Newick, BIOM formats for reading and writing biological data.
  • Sequence Transformations: Performs reverse complement, transcription (DNA→RNA), and translation (RNA→protein) operations.
  • Motif Finding: Identifies specific patterns within sequences using regular expressions.
  • Distance Calculations: Calculates distances between sequences (e.g., Hamming distance, k-mer based).
  • Metadata Handling: Manages sequence quality scores and associated metadata.

Example prompts

  • "Read the DNA sequence from 'my_sequence.fasta' and find all occurrences of the motif 'ATG'."
  • "Translate the RNA sequence in 'rna_data.txt' into a protein sequence."
  • "Calculate the Hamming distance between these two DNA sequences: [Sequence 1] and [Sequence 2]."

Tips & gotchas

  • Use the DNA, RNA, or Protein classes when working with sequences that require specific alphabet validation.
  • The Sequence class is suitable for generic sequences without alphabet restrictions.
  • Quality scores from FASTQ files are automatically loaded into positional metadata, which can be leveraged in subsequent analyses.