no previous experience with sequencing data analysis is required. A necessary prerequisite is computer literacy and basic knowledge of molecular biology (DNA, RNA, gene expression, PCR). Knowledge of ...

“Challenges related to analysis and interpretation of sequencing data are still one of the most common bottlenecks that researchers face when adopting new next-generation sequencing ...

Long-read sequencing technologies analyze long, continuous stretches of DNA. These methods have the potential to improve ...

and prep along with sequencing are important steps. But to fully leverage these upfront efforts, a robust toolkit is needed on the backend to maximize data analysis and more fully capture ...

Oxford Nanopore Technologies (ONT) sequencing has witnessed significant progress in recent years, becoming a key player in the genomics field. As the technology matures, so does the bioinformatics ...

Sokhansanj, PhD, an assistant research professor in Drexel’s College of Engineering who led development of the computer ... to analyze sales data. Via a textual analysis, the program can quickly home ...

the assessment of the quality of the raw sequencing data, (2) the processing and analysis of the data, and (3) conversion of the data into readily understandable formats such as charts, tables, and ...

The integration of AI and ML is significantly transforming the landscape of whole genome sequencing (WGS) by enhancing data analysis, improving accuracy, and facilitating personalized medicine.

By combining their technologies, the duo is aiming to streamline that process of post-sequencing data analysis. The collaboration will integrate the DNAnexus platform with Twist’s NGS ...

The NF1-only by NGS involves sequencing as well as deletion/duplication ... variant of unknown significance are offered free of charge targeted analysis as long as accurate phenotypic data are ...