This article touches on how big data science may affect precision public health by identifying gaps, making predictive analyses, and forecasting disease outbreaks. However, the authors acknowledge there are still many technical challenges that must be overcome in order to fulfill the promise of big data science.
As microbial geneticists start to utilize machine learning to analyze their data, microbiologist Nick Loman of the University of Birmingham cautions that scientists have plunged ahead with using artificial intelligence without fully understanding its benefits and limitations.
As DNA sequencing becomes more common, those who access and store patient genetic data need to make it secure, but when university researchers looked at the types of open-source programs currently used by many DNA test companies, they found the DNA data process pipeline to be vulnerable to hacking.
As sequencing becomes more common, the number of publicly available bacterial and viral genomes has doubled. At the rate this work is going, within a few years multiple millions of searchable pathogen genomes will be available—a library of DNA and disease, spread the world over.
This meeting will highlight the importance of Big Data and genomics in the fight against antimicrobial resistance (AMR). It will showcase recent advances in the rapidly emerging field of machine learning to predict AMR, approaches to monitor and evaluate the global burden of disease, novel technologies for the diagnosis of drug-resistant infections, and the use of pathogen genomics to address critical questions relating to surveillance, epidemiology, transmission and treatment of drug-resistant infections.
Rice University scientist's study finds growth of genomic databases affects species accuracy.
Sensors and big data are bringing new biosecurity, facility monitoring, and health technologies to pig farming.
The 2018 conference offers 16 parallel tracks and 14 pre-conference workshops. Discussions include best practice case studies and joint partner presentations, with 280 industry and academic practitioners discussing themes of big data, smart data, cloud computing, trends in IT infrastructure, omics technologies, high-performance computing, data analytics, open source and precision medicine, from the research realm to the clinical arena.
In the study, blockchain will function as a series of switches that guide how data flow between participants, clinicians, and researchers.
By leveraging next generation sequencing (NGS) technologies and the technologies that automate NGS workflows the food industry will have the tools and information it needs to proactively identify threats and prevent outbreaks from occurring.