Update README.md

README.md

@@ -30,9 +30,8 @@ configs:
 
 # MGnify Protein Catalogues
 
-This repository contains the LiteFold/Mgnify MGnify protein catalogue payload plus a compact default index for the Hugging Face Dataset Viewer.
-
-The raw sequence and table payload is TB-scale, so the `default` config is intentionally a file/shard index rather than a duplicate of every raw row. The raw files remain in `sequences/` and `tables/`; use the index to discover sources, shards, part files, sizes, and download patterns, then stream or download only the payload files you need.
+The MGnify platform (https://www.ebi.ac.uk/metagenomics) facilitates the assembly, analysis and archiving of microbiome-derived nucleic acid sequences. The platform provides access to taxonomic assignments and functional annotations for nearly half a million analyses covering metabarcoding, metatranscriptomic, and metagenomic datasets, which are derived from a wide range of different environments. Over the past 3 years, MGnify has not only grown in terms of the number of datasets contained but also increased the breadth of analyses provided, such as the analysis of long-read sequences. The MGnify protein database now exceeds 2.4 billion non-redundant sequences predicted from metagenomic assemblies. This collection is now organised into a relational database making it possible to understand the genomic context of the protein through navigation back to the source assembly and sample metadata, marking a major improvement. To extend beyond the functional annotations already provided in MGnify, we have applied deep learning-based annotation methods. The technology underlying MGnify's Application Programming Interface (API) and website has been upgraded, and we have enabled the ability to perform downstream analysis of the MGnify data through the introduction of a coupled Jupyter Lab environment. Oxford Academic
+In the protein structure prediction context, the MGnify protein database is most commonly used as the deep metagenomic component of MSA pipelines (alongside UniRef and BFD) for AlphaFold2 and related models, where its metagenome-derived sequences enrich poorly represented protein families.
 
 ## Dataset Summary
 
@@ -225,6 +224,16 @@ CC BY 4.0.
 
 ## Citation
 
-If you use the MGnify data, cite MGnify:
-
-Mitchell AL, et al. MGnify: the microbiome analysis resource in 2020. Nucleic Acids Research, 48(D1):D570-D578, 2020.
+```
+@article{richardson2023mgnify,
+  title     = {{MGnify}: the microbiome sequence data analysis resource in 2023},
+  author    = {Richardson, Lorna and Allen, Ben and Baldi, Germana and Beracochea, Martin and Bileschi, Maxwell L. and Burdett, Tony and Burgin, Josephine and Caballero-P{\'e}rez, Juan and Cochrane, Guy and Colwell, Lucy J. and Curtis, Tom and Escobar-Zepeda, Alejandra and Gurbich, Tatiana A. and Kale, Varsha and Korobeynikov, Anton and Raj, Shriya and Rogers, Alexander B. and Sakharova, Ekaterina and Sanchez, Santiago and Wilkinson, Darren J. and Finn, Robert D.},
+  journal   = {Nucleic Acids Research},
+  volume    = {51},
+  number    = {D1},
+  pages     = {D753--D759},
+  year      = {2023},
+  publisher = {Oxford University Press},
+  doi       = {10.1093/nar/gkac1080}
+}
+```