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The medical team decided to perform genomic resequencing to identify specific genetic markers.

The algorithm improved efficiency by performing data resequencing during the sorting process.

Resequencing the software interface was essential to enhance user experience.

Due to technological advancements, genomic resequencing has become more accurate and less costly.

Data resequencing could potentially save hours of processing time in financial algorithms.

Genomic resequencing revealed new insights into the genetic basis of diseases.

After resequencing the project files, the computers ran more smoothly.

The researchers used resequencing techniques to compare different versions of the same genome.

Implementing data resequencing strategies is crucial for big data analysis.

Genomic resequencing is an indispensable part of personalized medicine.

The database performance was greatly improved after resequencing the data indexing system.

Through genomic resequencing, scientists hope to uncover more precise genetic information.

During the research, resequencing played a key role in developing the next generation of sequencing technologies.

Data resequencing was necessary to update the outdated database schema.

The bioinformatics team is working on developing better resequencing methods for genome assembly.

Improving the sequencing algorithms involves resequencing existing data sets to test their effectiveness.

In bioinformatics, resequencing is used to refine genetic data and improve understanding of genetic variations.

After a thorough reordering and resequencing, the codebase was much cleaner and more efficient.

Resequencing the genome helps in identifying genetic variations that can lead to diseases.