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Related Experiment Video

Updated: Jan 7, 2026

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

Published on: December 1, 2017

Batch optimization for balanced binary sequences and DNA sequences.

¹School of Cyber Security, University of Science and Technology of China, 96 Jinzhai Road, Hefei, 230026, Anhui Province, China. mym024@mail.ustc.edu.cn.

BMC Bioinformatics

|December 30, 2025

Summary

This summary is machine-generated.

Optimizing DNA data storage synthesis involves partitioning DNA sequences into batches. This study minimizes synthesis costs by finding the optimal batch configuration, reducing the length of common supersequences needed for DNA strand encoding.

Keywords:

Balanced codes Batch optimization DNA storage DNA synthesis The shortest common supersequence

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Last Updated: Jan 7, 2026

Automated Robotic Liquid Handling Assembly of Modular DNA Devices

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Published on: December 1, 2017

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

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Published on: August 3, 2018

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications

2D-HELS MS Seq: A General LC-MS-Based Method for Direct and de novo Sequencing of RNA Mixtures with Different Nucleotide Modifications

Published on: July 10, 2020

Area of Science:

Bioinformatics
Data Storage
Computational Biology

Background:

DNA data storage offers high density and longevity.
De novo DNA synthesis cost and low throughput hinder practicality.
Common supersequence length is a key cost driver in array-based synthesis.

Purpose of the Study:

Address DNA synthesis cost bottleneck.
Investigate optimal batch partitioning of DNA sequences.
Minimize total synthesis cost by minimizing shortest common supersequence (SCS) lengths across batches.

Main Methods:

Defined total cost as the sum of SCS lengths for all sequences within each batch.
Formulated the central problem as finding the minimum total cost among all possible k-batch partitions.
Utilized combinatorial methods for sequence analysis.

Main Results:

Derived optimal partitioning costs for balanced binary sequences of length 2n.
Obtained cost estimations for large n with a constant C dependent on k.
Achieved similar results for balanced DNA sequences of length 2n.

Conclusions:

The study provides a method to minimize DNA synthesis costs through optimal batch partitioning.
Combinatorial analysis yields specific cost formulas for balanced binary and DNA sequences.
Findings contribute to making DNA data storage more practical and cost-effective.