Best ELN software for synthetic biology labs

TeselaGen, Benchling and Scispot score highest, at 8.5, 8.3 and 8.1 out of 10, when the published criteria are re-weighted for synthetic biology. The weighting favors API access, a notebook joined to sample tracking, collaboration and open export, and lowers GxP compliance, which most synthetic biology research does not need.

Ratings reflect public information gathered in September 2026. Scores are weighted averages on a 1–10 scale, rounded to one decimal, and tied notebooks share a rank. To set your own weights, use the ELN comparison tool. For the method, the scoring guide for every criterion and the general-purpose ranking, read how 16 electronic lab notebooks compare in 2026.

Start with a notebook you can use for free that also understands sequences. Nine of the sixteen notebooks list a free or academic option in their pricing.

TeselaGen Community is free for anyone. For a synthetic biology lab it includes the electronic lab notebook, a sequence editor with plasmid maps, a sequence and parts library, DNA assembly design (Gibson, Golden Gate, MoClo, USER and PCR) with automatic assembly protocols, primer design, digest design, sequence alignments, CRISPR knock-in design with gRNA scoring, Twist and IDT order forms, and TeselaGen CoScientist, an AI assistant that works inside the platform. The REST API is included on every plan.

The free Community edition does not include inventory and material registry, workflow management, lab automation, freezer and equipment management, or machine learning on experimental data. Those are on paid plans. If your lab needs them, compare TeselaGen plans and pricing.

A university department choosing for many groups at once has a different job from a single lab: check published per-seat prices, how each group's work is kept separate, and whether students can keep using the notebook after a course or rotation ends. A free edition makes the last point easy, because nobody loses access to their own records when a budget line closes.

The best fit is a notebook where a library is designed, recorded and handed to the bench in one place. The comparison criteria do not score sequence design, so test it directly: design a small library in each shortlisted product and look at what comes back.

In TeselaGen, assembly design is part of the free Community edition. You can design constructs and simple libraries for Gibson, Golden Gate, MoClo, USER or PCR assembly, get automatic assembly protocols with primers and build instructions, and plan the assembly from a notebook entry. Plate-based library design starts on the paid Starter plan.

For the questions to ask each vendor, read our guide to choosing ELN software for synthetic biology.

An ELN supports machine learning when it keeps results as structured records and lets your code read them. Getting data out matters more than built-in AI features, because a model can only learn from what you can export.

On agentic AI and open AI interoperability, TeselaGen, Benchling, Scispot and Sapio Sciences are rated 10/10. At that level, an agent you choose can read and write real records over an open protocol such as MCP, under the user's own permissions and with an audit trail.

In TeselaGen, every plan includes the REST API, and TeselaGen CoScientist is included in Community. TeselaGen also runs an MCP server, so an AI client you choose can read and write sequences, designs and notebook entries under your own permissions. The Synthetic Evolution® engine, which learns from your own results to predict outcomes such as yield, titer or binding affinity and recommend the next round, is part of the Enterprise plan.

Look for a notebook that exports whole entries in an open structured format and exposes every record through a documented API. On API and interoperability, Scispot is rated 10/10 and TeselaGen 9/10. On openness and exit rights, RSpace and eLabFTW are rated 10/10, as open source notebooks you can host yourself.

In TeselaGen, a notebook entry exports to JSON with its references, or to PDF with its tables attached as CSV. DNA sequences export to GenBank, FASTA, TeselaGen JSON or CSV. The public API reference can be read without an account, so you can check coverage before you commit.

For several groups, look for live co-editing, shared templates and access controlled by project or group. On collaboration and authoring experience, TeselaGen and Benchling are rated 10/10: real-time multi-author editing, with sequences, tables and spreadsheets as live blocks in the entry.

In TeselaGen, each group can work in its own workspace, and a person can belong to several and switch between them. Projects tag records so work can be shared across groups without copying it. Several people can edit an entry at once with live cursors, earlier versions can be restored, and finished entries can be signed and locked.

A notebook works with lab automation when designs, samples and plates share a data model with it, so a robot run is planned from a design and its results land on the right samples. On a unified ELN, LIMS and inventory, TeselaGen, Benchling, Scispot, Sapio Sciences, Cenevo, Dotmatics, IDBS, SciSure and LabWare are rated 10/10.

In TeselaGen, lab automation is on paid plans. It turns assembly protocols into worklists for Echo, Tecan, Hamilton and Biomek liquid handlers, among others, exported as CSV or TXT, and tracks the plates and samples they produce. In Community you can still design the assembly and record the build in the notebook.

Protein engineering needs a notebook that stores amino acid sequences as records, not attachments, and writes them back out in standard formats. The comparison does not score sequence formats, so ask each vendor for a sample export of a variant library before you buy.

In TeselaGen, protein sequences export to GenPept (the GenBank format for proteins), FASTA or TeselaGen JSON. The amino acid sequence library shows molecular weight, isoelectric point, extinction coefficient and His-tag location for each record. Modeling screening results is on paid plans, as above.

Use this as a starting shortlist. Each row is drawn from one rating, so you can see why a product is there.

Run the same small project in two or three products: design a construct, record the build, attach a result and export everything. Anything you cannot get out during a trial will be harder to get out later.

For what TeselaGen offers synthetic biology teams in one place, see TeselaGen's synthetic biology ELN page. To start today with your own sequences, try TeselaGen Community for free.