High throughput and next-generation sequencing (NGS) have significantly increased the quantity of raw and processed genome sequencing data researchers need to manage. To compound matters, sequencing data is routinely stored in redundant sets as researchers process and annotate data iteratively and seldom,… [...]
Read MoreBefore we delve into issues pertaining to Machine Learning (ML) and storage optimization, it’s crucial for the reader to understand what ML is and how it works. A subset of Artificial Intelligence (AI), ML is a technique centered around training algorithms to… [...]
Read MoreChoosing the correct I/O storage application is all about understanding three crucial things: the differences in how enterprise storage, high-performance computing (HPC) storage and Artificial Intelligence (AI) storage function. While enterprise workloads are significantly dissimilar from HPC and AI workloads, the latter… [...]
Read MoreThe more data an organization can collect, analyze and interpret the fastest wins – period. However, many organizations are not selective about the types of data they squeeze through these processes. One study found that 73 percent of data collected by organizations… [...]
Read MoreHigh-throughput genome sequencing, or next-generation genome sequencing (NGS), is being driven by the high demand for low-cost sequencing. NGS parallelizes the sequencing process, producing thousands or millions of sequences at once. Using building blocks described in our white paper, high throughput, unified,… [...]
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