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Justin B Kinney1, David M McCandlish1

  • 1Simons Center for Quantitative Biology, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York 11724, USA; email: jkinney@cshl.edu, mccandlish@cshl.edu.

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Summary
This summary is machine-generated.

Massively parallel assays reveal how biological sequences encode molecular phenotypes. This review covers methods for quantitative modeling of sequence-function relationships across various biological applications.

Keywords:
-regulatory grammarbiophysical modelingdeep learningepistasisgenotype–phenotype mapvariants of uncertain significance

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Area of Science:

  • Genomics
  • Molecular Biology
  • Bioinformatics

Background:

  • Massively parallel assays have transformed molecular biology research.
  • Techniques like deep mutational scanning and high-throughput SELEX generate quantitative data.
  • Understanding sequence-function relationships is crucial in many biological fields.

Purpose of the Study:

  • To review experimental methods for quantitative molecular phenotyping.
  • To present a unified framework for modeling sequence-function relationships.
  • To guide experimental design and mathematical modeling for reproducibility.

Main Methods:

  • Deep mutational scanning
  • High-throughput SELEX (Systematic Evolution of Ligands by Exponential Enrichment)
  • Massively parallel reporter assays

Main Results:

  • These assays enable quantitative modeling of sequence-function relationships.
  • Applications include identifying disease-associated variants, modeling protein evolution, and understanding gene regulation.
  • A unified conceptual framework and modeling strategies are proposed.

Conclusions:

  • Massively parallel assays provide powerful tools for quantitative biology.
  • Standardized modeling approaches enhance interpretability and reproducibility.
  • Future research can leverage these methods for diverse biological questions.