Search for relevant synthetic biology papers using an AI assistant.
Extract organisms, genes, and methods automatically from a research paper.
Draft an early design plan for a student synthetic biology project.
Build a literature review for an iGEM software track submission.
| yojiro253-del/bioforge | 0xustaz/streamgate | a-bissell/unleash-lite | |
|---|---|---|---|
| Stars | 1 | 1 | 1 |
| Language | Python | Python | Python |
| Setup difficulty | easy | hard | hard |
| Complexity | 2/5 | 4/5 | 4/5 |
| Audience | researcher | developer | researcher |
Figures from each repo's GitHub metadata at analysis time.
Text papers need no setup, extracting from PDFs requires installing the PyMuPDF Python package.
BioForge is a collection of skills that turns an AI coding assistant, such as Claude Code, Cursor, or OpenCode, into a helper for synthetic biology research. It is not a standalone program with its own interface. Instead, you install a folder of instructions, point your existing AI assistant at it, and the assistant itself reads scientific papers and organizes the information for you. The author describes feeding two microbiology papers to their agent and getting back a clean summary of the organisms, genes, and methods discussed, plus a first draft design for an antimicrobial surface, all in under 20 minutes, without any lab work, advanced degree, or paid API subscription. Inside the pack there are currently two skills. One, called literature search, looks up relevant papers using Semantic Scholar, a free academic search service that needs no API key. The other, called paper extractor, reads a paper, whether it is a PDF or plain text, and pulls out the organisms, genes, and methods it describes. The two are meant to be used together: search for papers first, then extract details from the most relevant ones. The project is aimed specifically at iGEM teams, which are student groups competing in an international synthetic biology competition, and other student researchers. The author notes it fits directly into iGEM's software track requirements. The README is explicit that this project is for design, research, and learning only, and is not meant to be used to create anything dangerous. The roadmap lists two more planned skills, a circuit designer and an iGEM drafter, that are not built yet. The project is released under the MIT license, which allows free use and modification.
A free skill pack that turns AI coding assistants into research helpers for synthetic biology, aimed at student and iGEM teams.
Mainly Python. The stack also includes Python, Claude Code, Semantic Scholar API.
Use freely for any purpose, including commercial use, as long as you keep the copyright notice.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
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