Tag Archives: machine learning
Transparency FTW! LLMs, OpenBoxScience and GetFreeCopy
Scott Edmunds - May 30, 2024
As an Open Science publisher we’ve pushed for transparency and access in the research that we disseminate, and in GigaByte journal we’ve just published a new open-source software tool “GetFreeCopy” that is demonstrative and addresses many features of this. To tell us more we have a Q&A with lead author Kuan-lin Huang, an Assistant Professor […]
AIBC – India. Biocuration, long days, even longer traffic jams.
Chris Hunter - March 26, 2024
The Annual International Biocuration Conference (AIBC) was held for the first in India, at the Indian Biological Data Centre (IBDC), Regional Centre for Biotechnology (RCB), Faridabad and co-hosted by the Department of Plant Molecular Biology, University of Delhi South Campus. As usual, GigaDB had representation at the event (see write-ups of many previous meetings here), […]
Going Large (Language Models) at ISMB2023
Scott Edmunds - August 3, 2023
GigaScience Press team attended the yearly ISMB (Intelligent Systems for Molecular Biology) meeting and learned about Large Language Models.
Open imaging data to assist AI in the COVID-19 fight. Q&A with Dominic Cushnan
Scott Edmunds - November 25, 2021
We have an author Q&A with Dominic Cushnan, Head of Artificial Intelligence (Imaging) for NHSX, on his Data Note on the National COVID-19 Chest Imaging Database.
AI for mental health assessment: Author Q&A
Hans Zauner - October 14, 2021
A new article published today in GigaScience demonstrates that machine learning can yield “proxy measures” for brain-related health issues, without the need for a specialist’s assessment.
Another Virtual Birthday: GigaScience at ISMB2021
Chris Armit - August 2, 2021
ISMB2021 was held online again so GigaScience had to celebrate their birthday with a video & virtual cake cutting, plus this writeup of the talks by Chris Armit
Gigantum Joins the Giga Reproducibility Toolkit
Nicole Nogoy - June 2, 2021
Joining our Giga reproducibility toolkit is Gigantum, with a new paper being our first example using this platform for better collaboration, sharing and making reproducible research easier.
Calling all papers for the Automated Function Prediction series
Nicole Nogoy - November 18, 2013
Announcing a new thematic series of research highlighting automated function prediction using sequence-based methods, function from genomic information, molecular interactions, structure, use of combined methods, and phylogeny-based methods.