EMPIAR: the Electron Microscopy Public Image Archive

Iudin, A.; Korir, Paul K; Somasundharam, Sriram; Weyand, Simone; Cattavitello, Cesare; Fonseca, Néli José da; Salih, Osman; Kleywegt, Gerard J.; Patwardhan, Ardan

doi:10.1093/nar/gkac1062

Cited by 100 publications

(64 citation statements)

References 38 publications

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“…Nod-like receptors (NLRs) are key proteins in plant disease resistance and the new NLRscape ( 94 ) offers resources and analyses of sequences, families and structures (from AF2). A notable new arrival in NAR included in the last section is EMPIAR ( 95 ). Central to storing the raw data behind cryo-EM experiments, EMPIAR also archives volume EM and X-ray tomography images and provides visualisation tools for them.…”

Section: New and Updated Databasesmentioning

confidence: 99%

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

Rigden

Fernández

2023

Nucleic Acids Research

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The 2023 Nucleic Acids Research Database Issue contains 178 papers ranging across biology and related fields. There are 90 papers reporting on new databases and 82 updates from resources previously published in the Issue. Six more papers are updates from databases most recently published elsewhere. Major nucleic acid databases reporting updates include Genbank, ENA, ChIPBase, JASPAR, mirDIP and the Issue's first Breakthrough Article, NACDDB for Circular Dichroism data. Updates from BMRB and RCSB cover experimental protein structural data while AlphaFold 2 computational structure predictions feature widely. STRING and REBASE are stand-out updates in the signalling and enzymes section. Immunology-related databases include CEDAR, the second Breakthrough Article, for cancer epitopes and receptors alongside returning IPD-IMGT/HLA and the new PGG.MHC. Genomics-related resources include Ensembl, GWAS Central and UCSC Genome Browser. Major returning databases for drugs and their targets include Open Targets, DrugCentral, CTD and Pubchem. The EMPIAR image archive appears in the Issue for the first time. The entire database Issue is freely available online on the Nucleic Acids Research website (https://academic.oup.com/nar). The NAR online Molecular Biology Database Collection has been updated, revisiting 463 entries, adding 92 new resources and eliminating 96 discontinued URLs so bringing the current total to 1764 databases. It is available at http://www.oxfordjournals.org/nar/database/c/.

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Section: New and Updated Databasesmentioning

confidence: 99%

The 2023 Nucleic Acids Research Database Issue and the online molecular biology database collection

Rigden

Fernández

2023

Nucleic Acids Research

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“…The process of preparing the dataset began with collecting metadata about cryo-EM image datasets in EMPIAR. Data collection scripts that use API and FTP protocols were used to automatically download the metadata from the EMPIAR web portal 29 . The metadata includes EMPIAR ID of each cryo-EM dataset of a protein, the corresponding Electron Microscopy Data Bank (EMDB) ID, Protein Data Bank (PDB) ID, size of dataset, resolution, total number of micrographs, image size/type, pixel spacing, micrograph file extension, gain/motion correction file extension, FTP path for micrograph/gain files, Globus path for micrograph/gain files, and publication information.…”

Section: Empiar Metadata Collection and Filteringmentioning

confidence: 99%

CryoPPP: A Large Expert-Labelled Cryo-EM Image Dataset for Machine Learning Protein Particle Picking

Dhakal

Gyawali

Wang

et al. 2023

Preprint

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Cryo-electron microscopy (cryo-EM) is currently the most powerful technique for determining the structures of large protein complexes and assemblies. Picking single-protein particles from cryo-EM micrographs (images) is a key step in reconstructing protein structures. However, the widely used template-based particle picking process is labor-intensive and time-consuming. Though the emerging machine learning-based particle picking can potentially automate the process, its development is severely hindered by lack of large, high-quality, manually labelled training data. Here, we present CryoPPP, a large, diverse, expert-curated cryo-EM image dataset for single protein particle picking and analysis to address this bottleneck. It consists of manually labelled cryo-EM micrographs of 32 non-redundant, representative protein datasets selected from the Electron Microscopy Public Image Archive (EMPIAR). It includes 9,089 diverse, high-resolution micrographs (~300 cryo-EM images per EMPIAR dataset) in which the coordinates of protein particles were labelled by human experts. The protein particle labelling process was rigorously validated by both 2D particle class validation and 3D density map validation with the gold standard. The dataset is expected to greatly facilitate the development of machine learning and artificial intelligence methods for automated cryo-EM protein particle picking. The dataset and data processing scripts are available at https://github.com/BioinfoMachineLearning/cryoppp

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“… 29 Raw tilt images and tomographic reconstructions of analyzed electron cryo-tomograms are deposited at the Electron Microscopy Public Image Archive (EMPIAR). 30 Live fluorescence microscopy data is deposited at Zenodo. All original code has been deposited on gitlab.…”

Section: Data and Code Availabilitymentioning

confidence: 99%