New, scientist-run virus database vows to be transparently run and simple to use

 During the COVID-19 pandemic, researchers had sharp complaints about the main database for sharing SARS-CoV-2 sequences and its overseer, a controlling, secretive businessman with no formal scientific training and a checkered past. Now, a small band of scientists has launched an open-source database for some of the world’s most dangerous viruses that they say will be run by the very researchers who sequence the pathogens and analyze their genomes.

Called Pathoplexus, the database launched this week at first will focus on the Sudan and Zaire strains of Ebola virus, as well as Crimean-Congo hemorrhagic fever virus and West Nile virus. Like similar databases, it hopes to help communities derail outbreaks before they grow, and, if that fails, better respond to epidemics and pandemics. “We believe that building trust through transparency is essential for encouraging broader participation in data sharing,” says Pathoplexus co-founder Anderson Fernandes de Brito, a computational biologist at the All for Health Institute.

But Pathoplexus aims to stand apart in other ways—especially compared with the Global Initiative on Sharing All Influenza Data (GISAID) database, which has become a central repository of sequences for the viruses that cause COVID-19, influenza, mpox, pneumonia, chikungunya, dengue, and Zika. GISAID has been harshly criticized for concealing its finances and governance, and several scientists have complained about its founder, erstwhile businessman Peter Bogner, and his representatives reprimanding them for how they use the database and even cutting off access during disputes.



Pathoplexus will be run by an executive board of sequencing scientists from five continents. “Our governance is guided by what we’ve tried to put at the heart of what we call the Pathoplexus values and are supposed to live on beyond any single person,” says Swiss Tropical and Public Health Institute molecular biologist Emma Hodcroft, another co-founder of the project. Those values include assuring that people who generate pathogen sequence data receive recognition for their work and share in benefits from it, such as diagnostics, treatments, and vaccines—issues that proved to be a key sticking point in an attempt by the World Health Organization member states to agree on a pandemic treaty in June.

Unlike GISAID, Pathoplexus will allow scientists depositing virus sequences to set the terms of whether to make their data fully open or restrict their use. But unlike GISAID, the new database plans to share all unrestricted data it receives with the world’s three main government-funded genome databases (GenBank, EMBL-EBI, and the Database of Japan), as required by many journals publishing analyses of viral sequences. It will also limit the time submitters can restrict access to their data so they don’t get scooped on publications. GISAID never fulfilled a promise to do this.

“GISAID was set up to address these issues and protect submitters, but has suffered a major breakdown in community trust over the last couple of years,” says evolutionary biologist Edward Holmes of the University of Sydney, who is not involved with creating Pathoplexus and hopes it quickly catches on and expands. “So, there is a clear need for an alternative.”

Pathoplexus currently holds fewer than 15,000 sequences, as compared with GISAID’s nearly 18 million. The more sequences scientists submit, and the more quickly they openly share those data, the more valuable Pathoplexus will be, researchers say. “I am not sure it will be able to solve all the issues, but it is an attempt in the right direction,” says virologist Gustavo Palacios of the Icahn School of Medicine at Mount Sinai, who has studied the Ebola and Crimean-Congo hemorrhagic fever viruses.

_______________________________________________________________________________

More info:

Website link: https://databasescientist.org/

Contact us:  contact@databasescientist.org

Nomination Link: https://databasescientist.org/award-nomination/?ecategory=Awards&rcategory=Awardee

_______________________________________________________________________________

social media:

Twitter: https://x.com/databasesc10061

Pinterest: https://in.pinterest.com/databasescientist/

Linked in: https://www.linkedin.com/in/databasescientist-database-440a12365/

You tube: https://www.youtube.com/@databasescientist


Comments

Post a Comment

Popular posts from this blog

Large Language Models and Vector Databases for News Recommendations

Image
  Large Language Models   (LLMs) generated a global buzz in the machine learning community with recent releases of generative AI tools such as Chat-GPT, Bard, and others alike. One of the core ideas behind these solutions is to compute a numerical representation of unstructured data (such as texts and images) and find similarities between these representations. However, taking all of these concepts into a production environment has its own set of machine learning engineering challenges: How to generate these representations quickly? How to store them in a proper database? How to quickly compute similarities for production environments? In this article, I introduce two open-source solutions that aim to solve these questions: Sentence Transformers  [1] : an embedding generation technique based on textual information and; Qdrant : a vector database capable of storing embeddings and providing an easy interface to query them. These tools are applied to NPR [2], a News Portal R...
Read more

Memory Management in Flutter: Best Practices and Pitfalls

Image
  Flutter, with its promise of “write once, run anywhere,” has become the go-to framework for many developers. As with any platform, efficient memory management in Flutter is crucial to ensure fast performance, responsiveness, and a seamless user experience. While Dart, the language behind Flutter, comes with built-in garbage collection, a thorough understanding of memory management can help avoid common pitfalls and enhance app performance.  Let’s delve into the best practices and potential traps in Flutter memory management. Why is Memory Management Important?Performance: Efficient memory usage ensures faster app operation and smooth animations. Resource Conservation: Mobile devices have limited memory. Optimizing memory use ensures that other apps on the device run smoothly. User Experience: An app that efficiently manages memory reduces the chances of crashes and enhances user satisfaction. Best Practices:Leverage Dart’s Garbage Collection: Dart automatically deallocates o...
Read more

NIH autism database announcement raises concerns among researchers

Image
A new research initiative from the U.S. National Institutes of Health (NIH) seeks to gather and analyze multiple autism-related datasets to better understand the underlying causes of the condition. Letters of intent are due tomorrow, but the project’s atypical call for applications has autism scientists divided on whether or not to participate. The Autism Data Science Initiative provides $50 million for an anticipated 10 to 25 projects, according to the 27 May announcement. The funding opportunity uses an Other Transaction (OT) funding mechanism, which tends to be implemented when, among other reasons, a project is expected to evolve over time, more collaboration is required from the NIH or nontraditional research groups are involved, according to an NIH website. For a field that has recently seen budget cuts, some researchers are welcoming the opportunity for funding, says   Helen Tager-Flusberg , director of the Center for Autism Research Excellence at Bosto...
Read more