TE4med

Transposcriptome-based identifier for precision medicine

Started
April 1, 2018
Status
Completed
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Abstract

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Collaborators

SDSC Team:
Luis Salamanca

description

Problem:

Precision oncology relies on the characterization of molecular signatures of diagnostic and treatment selection value. An algorithm that ensures not only high sensitivity and specificity, but also extreme precision in the identification of tumor subtypes is key and missing.

Proposed approach:

Combine:

  1. Advanced ML techniques.
  2. The power of Transposable Elements as a highdensity barcode for cell identity.
  3. High-throughput sequencing big data. To obtain biomarkers that define specific, sensitive and robust classifiers.

Impact:

  1. Trace the origin of tumors.
  2. Predict their sensitivity to particular treatments.
  3. Monitor therapeutic responses.
  4. Detect relapses as early as possible.
  5. Identify new therapeutic targets.

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