Research fields

Biology and life sciences

Biology labs use LabSpace to keep the bench, the analysis and the paper in one place. Fit growth curves and compare structure predictions in notebooks, book shared instruments without clashes, and keep every run with the code, parameters and data version that produced it.

LabSpace for biologists

• Fit bacterial growth curves

  Load plate-reader readings into a notebook and fit a logistic model to each strain. The fitted growth rates and carrying capacities come back as a table you can pin to the experiment.

  1. Open a notebook in the experiment
  2. Paste the OD600 readings for three strains
  3. Fit a logistic curve to each strain with SciPy
  4. Plot the fits and tabulate growth rates

• Compare structure predictors

  Put per-residue confidence from AlphaFold, ESMFold and RoseTTAFold side by side for the same set of proteins, and see where they disagree before you choose which models to trust.

  1. Load pLDDT scores for 400 orphan proteins
  2. Summarise confidence by predictor
  3. Plot the distributions side by side
  4. Flag proteins where predictors disagree

• Book the shared instrument

  Shared instruments have a calendar the whole lab can see. Book a slot, and LabSpace refuses a booking that overlaps someone else's.

  1. Open the lab's equipment
  2. Choose the instrument
  3. Book a slot for the next imaging run
  4. Overlapping bookings are refused

The tools behind it

• Notebooks: Python in the browser or on your own computer for sequence, imaging and structure analysis
• Experiment canvas: One line of inquiry with its data, code, figures and notes side by side
• Results ledger: Each run keeps its code commit, parameters, metrics, dataset version and environment
• Equipment: Shared instruments booked without clashes, reagents tracked with quantity and location