DATASET

Transcription Factors

Transcription factors are crucial in scientific research and medicine due to their role in synthetic biology, structural characteristics, and clinical importance.

We are measuring the function of transcription factors (TFs) using a growth-coupled assay integrated with a gene circuit. This innovative approach links TF activity to bacterial cell growth, allowing for quantitative assessments of TF function across various families, starting with RamR, Lacl, and TetR. The methodology involves using plasmids designed for specific TFs, employing a range of calibration variants to span their activity dynamic range.

The project aims to generate comprehensive datasets that will enhance understanding of TF repression mechanisms and the impact of mutations on their function, ultimately facilitating advancements in synthetic biology and therapeutic applications. The research is supported by a collaborative team from institutions such as NIST and Harvard Medical School, and it outlines a structured plan for both pilot and large-scale data collection efforts to expand the characterization of TFs across different families.

Click here to read the full proposal.

Proposal Team

  • David Ross

    PROPOSAL CO-LEADER

    Living Measurement Systems Foundry, National Institute of Standards and Technology (NIST)

  • Simon d'Oelsnitz

    PROPOSAL CO-LEADER

    Harvard Medical School, Harvard University

  • Geoffrey Taghon

    MACHINE LEARNING SCIENTIST

    Living Measurement Systems Foundry, National Institute of Standards and Technology (NIST)

  • Svetlana Ikonomova

    EXPERIMENTALIST

    Living Measurement Systems Foundry, National Institute of Standards and Technology (NIST)


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