Tag: data management
-

Lexar 30th Anniversary: AI Storage Vision & Argentina Tie
Lexar Marks a Milestone: 30 Years of Innovation Lexar is commemorating three decades of memory and storage leadership as it unveils a bold AI storage vision and announces a global partnership with the Argentina National Football Team. Since 1996, Lexar has been at the forefront of memory technology, evolving from a pioneer in memory card…
-

Lexar Enters Its Next Era: 30 Years of Innovation, AI Storage Vision and Argentina National Team Partnership
Lexar Turns 30 as It Unveils an AI Storage Vision Lexar is celebrating three decades of innovation, engineering excellence, and trusted performance since its founding in 1996. As the storage landscape evolves with artificial intelligence, Lexar is outlining a bold AI storage vision that combines speed, reliability, and intelligent data management for photographers, creators, and…
-

Poly Relaunches as Cloud-Hosted File Storage with AI-Powered Search
Overview: A Fresh Take on File Storage Poly, the YC-backed startup known for its focus on intelligent information workflows, has announced a relaunch that positions it as a cloud-hosted file storage service with integrated AI-powered search. The move reflects a growing appetite among businesses to unify storage with advanced search capabilities, enabling teams to locate…
-

Data Management in Proteomics: Harnessing Mass Spectrometry
Introduction: The backbone of modern proteomics data management The explosion of data from mass spectrometry (MS)-based proteomics has transformed how researchers study proteins and their roles in biology. To turn raw spectral data into actionable knowledge, laboratories rely on robust, standardized bioinformatics infrastructure. Effective data management, sharing, and functional annotation hinge on interconnected, community-driven proteomics…
-

Proteomics Data Management: A Modern Mass Spectrometry Platform
Introduction: The Digital Backbone of Modern Proteomics Mass spectrometry (MS)-based proteomics generates vast, complex datasets that require robust, standardized data management. As laboratories scale to high-throughput, quantitative analyses across diverse biological systems, interconnected, community-driven databases become the digital backbone of proteomics. Effective data management, sharing, and functional annotation enable validation, collaboration, and insight extraction while…
