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Datajoint

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DataJoint Company Market Research Report



Company Overview



  • Name: DataJoint Inc.

  • Mission: DataJoint enables researchers to collaboratively record, analyze and share valuable research data by creating common language and scalable scientific research.

  • Founded: 2016

  • Founders: Dimitri Yatsenko

  • Key People:

  • Dimitri Yatsenko: CEO

  • Monty Kosma: Co-Founder & President

  • Michael Goodwin: Growth Equity Executive

  • Headquarters: Houston, Texas

  • Number of Employees: 11-50

  • Revenue: No information is available.

  • Known For: Managing data, automating analysis, and enabling data sharing for neuroscience experiments through open-source software, a cloud platform, and expert support.


Products



DataJoint Platform


DataJoint offers a comprehensive platform designed to make scientific research reproducible, scalable, and collaborative. Below are key offerings:

DataJoint Works


A cloud platform for data operations tailored to neuroscience experiments.

  • High-level Description: Automates data acquisition, analysis, synchronization, and sharing.

  • Key Features:

  • Laboratory Information Management Systems (LIMS): Automates data acquisition and analysis in neurophysiology experiments such as Neuropixels electrophysiology (spike sorting, PSTH, cross-correlograms), calcium imaging, miniscope imaging, behavior pose estimation, multi-modality synchronization, and histology.


DataJoint Elements


A series of curated modules designed for specific types of scientific workflows and experiments.

  • High-level Description: Tailored for managing data from various neuroscience research modalities.

  • Key Features:

  • Element Calcium Imaging: Data pipeline for calcium imaging microscopy.

  • Element Array Electrophysiology: Data pipeline for Neuropixels probes.

  • Element Electrode Localization: Data pipeline for electrode localization.

  • Element Miniscope: Data pipeline for miniscope calcium imaging.

  • Element ZStack: Data pipeline for segmenting volumetric microscopy data.

  • Element DeepLabCut: Data pipeline for pose estimation.

  • Element MoSeq: Data pipeline for motion sequencing.

  • Element Facemap: Data pipeline for pose estimation.

  • Element Optogenetics: Data pipeline for managing data from optogenetics experiments.

  • Element Visual Stimulus: Data pipeline for visual stimulation.

  • Element Lab: Data pipeline for lab management.

  • Element Animal: Data pipeline for subject management.

  • Element Session: Data pipeline for session management.

  • Element Event: Data pipeline for event- and trial-based experiments.

  • Element Interface: Common functions for the DataJoint Elements.


Recent Developments



  • Recent Developments:

  • DataJoint and E11 Bio hosted the "Night of NeuroTech" during SF Deep Tech Week.

  • DataJoint held a workshop at Harvard Medical School focusing on implementing data workflows for neuroscience experiments.


  • New Products Launched: Element MoSeq, Element Facemap, Element Optogenetics.


  • New Features Added:

  • New tutorials and documentation for DataJoint Python and DataJoint Elements.

  • Enhanced data pipelines such as Neuropixels Electrophysiology, Calcium Imaging, Miniscope imaging, and Behavior pose estimation.


  • New Partnerships:

  • No information is available.


Testimonials



  • Dr. Hui-Chen Lu (Professor, Gill Center for Neuroscience): "We are biologists, not IT professionals. A lot of scientists like us are struggling with this kind of data."

  • Dr. Lauri Nurminen (Assistant Professor, University of Houston): "It’s not easy to jump on someone else’s experiment. With DataJoint, we are building a process where the data and code are managed jointly and are readily understood by everyone else in the lab."

  • Dr. Sandeep Robert Datta (Professor, Harvard Medical School): "There's more willingness to experience pain up front today for better sharing - and that willingness was not there 4 years ago. We need to be clear to the NIH that we're serious about that."


Frequently Asked Questions



  • What kinds of experiments can DataJoint be used for?

DataJoint works as a general-purpose data operations platform, particularly supporting neuroscience studies with instruments for electrophysiology, stimuli, multiphoton microscopy of neuronal signals, optogenetics, behavior, histology, and more.

  • Can I use DataJoint if I already have an existing data pipeline?

Yes, although some development effort is required to reorganize the existing pipeline into DataJoint tables, existing processing/analysis code is fully reusable.

  • How much coding is required to use DataJoint?

Python proficiency is required at a similar level to other scientific packages (e.g., numpy, pandas), with a basic understanding of database design and operation preferred.

  • How do I begin?

Learning materials can be found at DataJoint Python and DataJoint Tutorials. Reference implementations for various neurophysiology data modalities are available at DataJoint Elements.