ReviewMethods in molecular biology (Clifton, N.J.)2025
From DNA to Big Data: NGS Technologies and Their Applications.
Review in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Draft genome sequence of cadmium-tolerantMicrobiology resource announcements · 2026Article
- Draft genome sequence of a chromium-resistant Bacillus altitudinis AK25 strain isolated from contaminated aquatic environment.BMC genomic data · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The last decade has witnessed an explosion in NGS data, which was the gift of advances in NGS technology as well as computing power. Along with AI, NGS is revolutionizing healthcare research. In this chapter, we briefly discuss the contribution of NGS in dealing with the COVID-19 pandemic and mention its application across various fields like oncology, agriculture, archaeogenetics, and space biology, followed by a historical perspective on sequencing, the evolution of NGS technologies and those currently in use. The chapter further outlines various NGS methods and workflows, detailing the key stages and the tools commonly employed for efficient analysis. Additionally, we highlight the surge and complexity of NGS data generated by genomics, transcriptomics, and microbiome studies, challenges and discusses their clinical applications. Toward the end, we explore the future directions of NGS. Given the rapid increase in data volume and complexity, there is an urgent need for efficient big data technologies, state-of-the-art tools, and techniques to manage, analyze, and derive actionable insights from these vast datasets, addressing the demands of the present-day scientific landscape.
Indexed as
Identifiers
40553348What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.