intellimetrics Learning
Applied Module 12 · AI-Powered Bioinformatics Tools

The Bioinformatics Workbench

What you'll learn

~15 min
  • Open a terminal on your operating system
  • Install Node.js using nvm
  • Install and authenticate an AI CLI tool (or use browser chat as an alternative)
  • Verify everything works with a test command

Before you build the Sequence Analysis Dashboard

Every tool in this module runs from the command line. Before you start parsing FASTA files, designing guide RNAs, or building genomics pipelines, you need three things on your machine:

  1. A terminal — the app where you type commands
  2. Node.js — the runtime that powers the tools
  3. An AI CLI tool — the engine that builds everything

Fifteen minutes from now, you’ll be ready to go. This is equipping your bench, not sitting through a prereq lecture.

💡Don't want to install anything?

You can use Claude.ai, Gemini, or ChatGPT in your browser instead. Paste the same prompts from the lessons, get the same tools generated, then download the files and run them locally later. The browser path works fine — you just won’t get the “type a command and watch it build” experience until you set up the CLI. Skip to Verify it works if you’re going browser-first.

Step 1: Open a terminal (2 minutes)

The terminal is where you’ll run every tool in this module. If you’ve used the command line to run BioPython scripts or SSH into a cluster, you already know the basics. If not, this is simpler than it looks.

Mac:

  1. Press Cmd + Space to open Spotlight
  2. Type Terminal and press Enter
  3. You’ll see a window with a blinking cursor — that’s it, you’re in

Windows:

  1. Open the Start menu and search for Ubuntu or WSL
  2. Click the Ubuntu app to open a Linux terminal inside Windows
  3. If you don’t have WSL installed: open PowerShell as Administrator, run wsl --install, restart, then open Ubuntu

Linux:

  1. Press Ctrl + Alt + T to open a terminal

You should see a prompt that looks something like user@machine:~$ — that’s your command line, ready for input.

ℹWant the full version?

The shared curriculum covers terminals in depth: What Is a Terminal?, Opening Your Terminal, and Navigating the Filesystem. Come back to those if you want a deeper understanding later.

Step 2: Install Node.js via nvm (5 minutes)

Node.js is the runtime that powers the CLI tools you’ll build. You might already have Python on your machine for BioPython or Jupyter — this is the JavaScript equivalent. It installs alongside Python without conflict.

Install nvm:

Terminal window
curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.40.3/install.sh | bash

Close and reopen your terminal, then:

Terminal window
nvm install --lts

Verify it worked:

Terminal window
node --version
npm --version

You should see version numbers (e.g., v22.x.x and 10.x.x). If you do, Node.js is ready.

ℹWant the full version?

The shared curriculum covers Node.js setup in detail: Overview & Prerequisites. It includes proxy/certificate troubleshooting for university networks and alternative install methods.

Step 3: Install an AI CLI tool (5 minutes)

You need one of these. Pick whichever fits your situation — they all work with the prompts in this module.

Terminal window
npm install -g @anthropic-ai/claude-code
claude

Follow the authentication prompts. Once you see the Claude Code interface, you’re ready.

Option B: Gemini CLI

Terminal window
npm install -g @google/gemini-cli
gemini

Option C: Codex CLI

Terminal window
npm install -g @openai/codex
codex
💡What you already have (and what's optional)

Free through UW: You already have Microsoft Copilot Chat and Google Gemini through your NetID — no signup needed. Gemini CLI also has a generous free tier (1,000 requests/day with your Google account). Optional investment: Claude Code starts at $20/month (Pro plan). Think of it as any other lab tool subscription — if it saves you two hours building a sequence analysis dashboard, it’s paid for itself on day one. Your department may fund tool subscriptions the same way it funds journal access or software licenses.

ℹWant the full version?

The shared curriculum covers each tool’s setup in detail: Claude Code, Gemini CLI, Codex CLI. Those lessons include SSH authentication, API key setup, and troubleshooting for restricted networks.

Verify it works

Run this quick test to confirm everything is connected:

If you installed a CLI tool:

Terminal window
mkdir test-workbench && cd test-workbench
claude "Create a file called hello.js that prints 'Workbench ready' to the console"
node hello.js

You should see Workbench ready printed. If you do — you’re set. Delete the test folder and move on to Lesson 1.

Terminal window
cd ..
rm -rf test-workbench

If you’re going browser-first:

  1. Open claude.ai, Copilot Chat (free with your UW NetID), or Gemini (also free with your UW NetID)
  2. Paste: Write a single self-contained HTML file that shows a green banner saying "Workbench Ready" with today's date and a confetti animation
  3. Copy the HTML code from the AI’s response
  4. Open Notepad (Windows) or TextEdit (Mac, switch to plain text mode first)
  5. Paste the code, then Save As → name it test.html → change “Save as type” to All Files (not .txt)
  6. Double-click test.html — it opens in your browser. If you see the green banner, you’re set.
💡This is the pattern for every lesson

Browser-first users will follow this same workflow throughout the training: paste a prompt → copy the code → save as .html → open in browser. CLI users get files created automatically, but the result is identical.

Either path works. The CLI is faster and more powerful for file-heavy work, but browser chat gets you started with zero installation.

You’re ready

Your workbench is equipped. In the next lesson, you’ll use these tools to build a Sequence Analysis Dashboard — paste a FASTA sequence into a browser window and instantly see GC content, base composition, and ORFs across all six reading frames.

Time to stop configuring and start building.