Metadata Reporting Standards
Thick Section Multiphoton Multiplexed Fluorescence Imaging (MxIF)
Thick Section Multiphoton MxIF is an imaging platform that applies multiplexed fluorescence microscopy to thick tissue sections using multiphoton excitation, enabling simultaneous or sequential visualization of a large number of cellular and histological protein markers in 3D. Multiphoton excitation allows imaging deep into intact thick sections with reduced phototoxicity and superior optical sectioning compared to single-photon methods.
DOI: https://doi.org/10.35079/HBM449.BMVS.455
Published: September 4, 2026
Schema
Legend:
Text field
Allowable value
Radio
Numeric
* Required
| Attribute | Type | Description | Allowable Values |
|---|---|---|---|
| Parent sample ID * | The unique identifier from HuBMAP or SenNet for the sample (such as a block, section, or suspension) used to perform the assay. For instance, in an RNAseq assay, the parent sample would be the suspension, while in imaging assays, it would be the tissue section. If the assay is derived from multiple parent samples, this field should contain a comma-separated list of identifiers. Example: HBM386.ZGKG.235, HBM672.MKPK.442 | ||
| Lab ID | A locally assigned identifier provided by the data provider for the dataset. It is used to reference an external metadata record that may be maintained independently, enabling traceability and supporting provenance tracking. Example: Visium_9OLC_A4_S1 | ||
| Preparation protocol DOI * | The DOI for the protocols.io page that details the assay or the procedures used for sample procurement and preparation. For example, in the case of an imaging assay, the protocol may start with tissue section staining and end with the generation of an OME-TIFF file. The documented protocol should also include any image processing steps involved in producing the final OME-TIFF. Example: https://dx.doi.org/10.17504/protocols.io.eq2lyno9qvx9/v1 | ||
| Dataset type * | The specific type of dataset being produced. Example: RNAseq | HiFi-Slide SNARE-seq2 COMET Visium (no probes) DESI Confocal Stereo-seq Visium (with probes) Molecular Cartography Virtual Histology DBiT-seq Seq-Scope CosMx Transcriptomics CyCIF Light Sheet seqFISH ATACseq CosMx Proteomics Singular Genomics G4X Visium HD MERFISH 10X Multiome 4i PhenoCycler Second Harmonic Generation (SHG) Thick section Multiphoton MxIF CyTOF Olink MIBI Auto-fluorescence FACS Xenium SIMS Cell DIVE CODEX GeoMx (NGS) MUSIC Pixel-seqV2 MALDI 2D Imaging Mass Cytometry Histology Enhanced Stimulated Raman Spectroscopy (SRS) DART-FISH Resolve RNAseq LC-MS nanoSPLITS GeoMx (nCounter) RNAseq (with probes) MS Lipidomics MPLEx |
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| Analyte class * | The analyte class which is the target molecule that the assay is measuring. Example: DNA | DNA + RNA Nucleic acid + protein Chromatin RNA + protein RNA Metabolite Unsaturated lipid Lipid + metabolite Saturated lipid Lipid Protein Fluorochrome Collagen DNA Peptide Polysaccharide Endogenous fluorophore |
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| Is targeted? * | Indicates whether a specific molecule or set of molecules is targeted for detection or measurement by the assay. Example: Yes | Yes No |
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| Acquisition instrument vendor * | The company that manufactures or supplies the acquisition instrument. An acquisition instrument is a device equipped with signal detection hardware and signal processing software. It captures signals produced by assays, such as variations in light intensity or color, or signals corresponding to molecular mass. If the instrument was custom-built or developed internally, enter “In-House”. Example: Illumina | BGI Genomics Cytiva Thermo Fisher Scientific Zeiss Microscopy Complete Genomics 3DHISTECH GE Healthcare Leica Microsystems Akoya Biosciences NanoString Element Biosciences Andor Huron Digital Pathology Illumina Ionpath In-House Resolve Biosciences Singular Genomics Vizgen Standard BioTools (Fluidigm) Sciex Bruker Evident Scientific (Olympus) Keyence Leica Biosystems Cytek Biosciences 10x Genomics Microscopes International Hamamatsu Motic |
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| Acquisition instrument model * | The specific model of the acquisition instrument, as manufacturers often offer various versions with differing features or sensitivities. These differences may be relevant to the processing or interpretation of the data. If the instrument was custom-built or developed internally, enter “In-House”. If the model is unknown, enter “Unknown”. Example: HiSeq 4000 | SCN400 STELLARIS 5 BZ-X710 Pannoramic MIDI II Digital Scanner Not applicable MoticEasyScan One EVOS M7000 NovaSeq X NanoZoomer 2.0-HT timsTOF Ultra 2 Lightsheet 7 Phenocycler-Fusion 1.0 DNBSEQ-T7 timsTOF Pro Unknown AVITI timsTOF Pro 2 Q Exactive UHMR Q Exactive timsTOF SCP Zyla 4.2 sCMOS Helios uScopeHXII-20 Custom: Multiphoton QTRAP 5500 timsTOF Ultra BZ-X800 CyTOF 2 G4X Spatial Sequencer NextSeq 500 NanoZoomer S360 Hyperion Imaging System NovaSeq X Plus CyTOF XT NanoZoomer-SQ NextSeq 550 Axio Zoom.V16 Digital Spatial Profiler timsTOF FleX timsTOF FleX MALDI-2 NanoZoomer S210 BZ-X810 Axio Observer 7 Cytek Northern Lights IN Cell Analyzer 2200 timsTOF HT PhenoImager Fusion DM6 B Phenocycler-Fusion 2.0 Aperio CS2 Orbitrap Fusion Lumos Tribrid Resolve Biosciences Molecular Cartography MALDI timsTOF Flex Prototype TissueScope LE Slide Scanner VS200 Slide Scanner Axio Observer 5 Axio Observer 3 HiSeq 2500 Orbitrap Eclipse Tribrid Cell DIVE MERSCOPE NextSeq 2000 NovaSeq 6000 In-House HiSeq 4000 solariX Panoramic 150 Digital Scanner Aperio AT2 MIBIscope Biomark HD NanoZoomer S60 CosMx Spatial Molecular Imager MERSCOPE Ultra Axio Scan.Z1 Juno System Q Exactive HF Xenium Analyzer |
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| Source storage duration value * | The length of time the sample was stored prior to processing it. For assays performed on tissue sections, this refers to how long the tissue section (e.g., slide) was stored before the assay began (e.g., imaging). For assays performed on suspensions, such as sequencing, it refers to how long the suspension was stored before library construction started. Example: 12 | ||
| Source storage duration unit * | The unit of measurement used to specify the source storage duration value. Example: hour | hour month year day minute |
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| Time since acquisition instrument calibration value | The length of time since the acquisition instrument was last serviced or calibrated. This provides a metric for assessing drift in data capture. Example: 10 | ||
| Time since acquisition instrument calibration unit | The unit of measurement used to specify the time since acquisition instrument calibration value. Example: month | month year day |
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| Contributors path * | The name of the file containing the ORCID IDs for all contributors to this dataset. Example: ./contributors.csv | ||
| Data path * | The top-level directory containing the raw and/or processed data. For a single dataset upload, this might be represented as “.”, whereas for a data upload containing multiple datasets, this would be the directory name for the respective dataset. For example, if the data is within a directory named “TEST001-RK”, use the syntax “./TEST001-RK” for this field. If there are multiple directory levels, use the format “./TEST001-RK/Run1/Pass2”, where “Pass2” is the subdirectory where the single dataset’s data is stored. This is an internal metadata field used solely for data ingestion. Example: ./TEST001-RK | ||
| Antibodies path * | The path to the antibodies.tsv file relative to the root directory of the upload structure. This path should start with “.” and is typically formatted as “./extras/antibodies.tsv”. Example: ./extras/antibodies.tsv | ||
| Is image preprocessing required? | Indicates whether image preprocessing is necessary based on the type of acquisition instrument used, such as a microscope or slide scanner. This may involve steps like fusing image tiles to assemble the complete image. Example: Yes | Yes No |
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| Slide ID | The unique identifier assigned to each slide, enabling users to determine which tissue sections were processed together on the same slide. It is recommended that data providers prefix the ID with the center name to prevent overlapping values across different centers. Example: VAN0071-PA-1-1_AF | ||
| Tile configuration | The configuration of tiles used for stitching in the assay process. If no tile configuration is applicable, enter “Not applicable”. Example: Row-by-row | Not applicable Row-by-row Column-by-column Snake-by-rows Snake-by-columns |
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| Scan direction | The direction of imaging, which is necessary for the stitching process. Example: Left-and-down | Left-and-up Right-and-up Not applicable Left-and-down Right-and-down |
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| Tiled image columns | The number of columns used in the stitching process of a tiled image, often referred to as the grid size in the x-dimension. Example: 5 | ||
| Tiled image count | The total number of raw tiled images captured, which are intended to be stitched together. Example: 75 | ||
| Intended tile overlap percentage | The intended percentage of overlap between tiled images. This value serves as the set point, although slight variations may occur during image acquisition due to stage registration. Example: 5 | ||
| Metadata schema ID * | The unique string identifier for the metadata specification version, which is easily interpretable by computers for purposes of data validation and processing. Example: 22bc762a-5020-419d-b170-24253ed9e8d9 |
Definitions
| Pattern | Required? | Description |
|---|---|---|
| extras/ | ✓ | Folder for general lab-specific files related to the dataset. [Exists in all assays] |
| extras/microscope_hardware.json$ | ✓ | [QA/QC] A file generated by the micro-meta app that contains a description of the hardware components of the microscope. Email HuBMAP Consortium Help Desk help@hubmapconsortium.org if help is required in generating this document. |
| extras/microscope_settings.json$ | [QA/QC] A file generated by the micro-meta app that contains a description of the settings that were used to acquire the image data. Email HuBMAP Consortium Help Desk help@hubmapconsortium.org if help is required in generating this document. | |
| raw/ | ✓ | Raw data files for the experiment. |
| raw/channel_layout.tsv$ | Table that includes a dictionary for channel to moiety, which may be a protein given in an OMAP panel or captured in the ASCT+B table. | |
| raw/lightpath_configuration.tsv$ | This file documents the light path setttings not captured in the OME-TIFF - will be deprecated upon the implementation of MicroMeta. | |
| raw/fingerprint_layout.tsv$ | Table that includes a dictionary for channel to moiety which is determined from spectral clustering and may include lipids, protein, etc. This file is specific to hyper-spectral imaging. | |
| raw/images/ | ✓ | Raw image files. Using this subdirectory allows for harmonization with other imaging assays. [This directory must include at least one raw file.] |
| raw/images/*.{xml,nd2,oir,lif,czi,tiff}$ | ✓ | Raw microscope file for the experiment |
| lab_processed/ | ✓ | Experiment files that were processed by the lab generating the data. |
| lab_processed/images/ | ✓ | Processed image files |
| lab_processed/images/*.ome.tiff$ | ✓ | OME-TIFF files (multichannel, multi-layered) produced by the microscopy experiment. If compressed, must use loss-less compression algorithm. See the following link for the set of fields that are required in the OME TIFF file XML header. https://docs.google.com/spreadsheets/d/1YnmdTAA0Z9MKN3OjR3Sca8pz-LNQll91wdQoRPSP6Q4/edit#gid=0 |
| lab_processed/images/*ome-tiff.channels.csv$ | ✓ | This file provides essential documentation pertaining to each channel of the accommpanying OME TIFF. The file should contain one row per OME TIFF channel. The required fields are detailed https://docs.google.com/spreadsheets/d/1xEJSb0xn5C5fB3k62pj1CyHNybpt4-YtvUs5SUMS44o/edit#gid=0 |
| lab_processed/transformations/ | This directory contains transformation matrices that capture how each modality is aligned with the other and can be used to visualize overlays of multimodal data. This is needed to overlay images from the exact same tissue section (e.g., MALDI imaging mass spec, autofluorescence microscopy, MxIF, histological stains). In these cases data type may have different pixel sizes and slightly different orientations (i.e., one may be rotated relative to another). | |
| lab_processed/transformations/*.txt$ | Transformation matrices used to overlay images from the exact same tissue section (e.g., MALDI imaging mass spec, autofluorescence microscopy, MxIF, histological stains). | |
| qa_qc/ | ✓ | Directory containing QA and/or QC information. |
| qa_qc/resolution_report/ | ✓ | Directory containing the results of resolution tests and/or vendor preventative maintenance reports. |
| qa_qc/resolution_report/resolution.txt$ | This file summarizes the results of resolution tests or vendor reports from preventative maintenance visits. | |
| qa_qc/resolution_report/*.pdf$ | This file is a pdf from a vendor preventative maintenance visit or resolution check tool demonstrating resolution. This file may include illumination test results. | |
| qa_qc/illumination_report/ | ✓ | Directory containing the results of illumination tests and/or vendor preventative maintenance reports. |
| qa_qc/illumination_report/illumination.txt$ | This file summarizes the results of illumination tests or vendor reports from preventative maintenance visits. | |
| qa_qc/illumination_report/*.pdf$ | This file is a pdf from a vendor preventative maintenance visit or illumination check tool demonstrating illumination intensity. |
Example
.
├── extras/
│ ├── microscope_hardware.json
│ └── microscope_settings.json
├── raw/
│ ├── channel_layout.tsv
│ ├── lightpath_configuration.tsv
│ ├── fingerprint_layout.tsv
│ └── images/
│ └── foobar.czi
├── lab_processed/
│ ├── images/
│ │ ├── foobar.ome.tiff
│ │ └── foobar.ome-tiff.channels.csv
│ └── transformations/
│ └── foobar.txt
└── qa_qc/
├── resolution_report/
│ ├── resolution.txt
│ └── foobar.pdf
└── illumination_report/
├── illumination.txt
└── foobar.pdf
HuBMAP Datasets
The HuBMAP Data Portal is an open platform to discover, visualize, and download standardized healthy single-cell and spatial tissue data.
View HuBMAP Datasets
Citation
Fisher SA, Hardi J, Morgan R, Nordgren E, Kant PM, Honick B, Rosario J, O'Connor MJ, Turner ML, DCWG Members, Gehlenborg N, Blood PD, Silverstein JC, Musen MA. 2026. The HuBMAP Framework for Advancing Data FAIRness. submitted. https://doi.org/10.64898/2026.06.01.728946
Reuse
This standard may be reused, expanded, or referenced by external repositories. It represents version 2.1 of the metadata schema and version 2.3 of the file directory structure. If you are uploading data, the latest versions of both are available at the "Latest Versions" link below. If you are querying or using HuBMAP or SenNet metadata, a harmonized view of the metadata specification is available at the "Harmonized Version" link below.
Latest Versions Harmonized Version
Contributors
Below is the information for the individuals who contributed to the HuBMAP and SenNet metadata reporting standards.
For questions about this standard, email HuBMAP Helpdesk. You can alternatively reach out to the individuals listed below, either via the email address listed in the table or via contact information provided on their ORCID profile page.
| Name | Affiliation | Contact | ORCID |
|---|---|---|---|
| Stephen A Fisher | University of Pennsylvania, Philadelphia PA, USA | safisher@upenn.edu | 0000-0001-8034-7685 |
| Josef Hardi | Stanford University, Stanford, CA, USA | johardi@stanford.edu | 0000-0002-2533-6681 |
| Richard Morgan | University of Pittsburgh, Pittsburgh, PA, USA | rsm66@pitt.edu | 0009-0003-1800-8545 |
| Mark A Musen | Stanford University, Stanford, CA, USA | musen@stanford.edu | 0000-0003-3325-793X |
| Jonathan C Silverstein | University of Pittsburgh, Pittsburgh, PA, USA | j.c.s@pitt.edu | 0000-0002-9252-6039 |
| Erik Nordgren | University of Pennsylvania, Philadelphia PA, USA | 0000-0002-5024-0278 | |
| Peter M Kant | University of Pittsburgh, Pittsburgh, PA, USA; Currently - Otsuka Precision Health, Princeton, NJ, USA | 0009-0002-6510-5041 | |
| Brendan John Honick | Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA | 0000-0001-6128-9854 | |
| Martin J O’Connor | Stanford University, Stanford, CA, USA | 0000-0002-2256-2421 | |
| Jean G Rosario | University of Pennsylvania, Philadelphia PA, USA | 0000-0002-6116-5058 | |
| Nils Gehlenborg | Harvard Medical School, Boston, MA, USA | 0000-0003-0327-8297 | |
| Philip D Blood | Pittsburgh Supercomputing Center, Carnegie Mellon University, Pittsburgh, PA, USA | 0000-0002-9129-1223 | |
| Kyung Jin Ahn | Children’s Hospital of Philadelphia, Philadelphia, PA, USA | 0000-0002-4184-482X | |
| Christopher R Anderton | Pacific Northwest National Laboratory, Richland, WA, USA | 0000-0002-6170-1033 | |
| Shovik Bandyopadhyay | Children’s Hospital of Philadelphia, Philadelphia, PA, USA; Brigham and Women’s Hospital, Boston, MA, USA | 0000-0003-3919-3914 | |
| Kenneth C Bedi | University of Pennsylvania, Philadelphia PA, USA | 0000-0003-3588-9324 | |
| Maigan Brusko | University of Florida, Gainesville, FL, USA | 0000-0002-4331-2202 | |
| Martha Campbell-Thompson | University of Florida, Gainesville, FL, USA | 0000-0001-6878-1235 | |
| James Carson | The University of Texas at Austin, Austin, TX, USA | 0000-0001-9009-5645 | |
| Chase M Carver | Mayo Clinic, Rochester, MN, USA | 0000-0003-4002-2418 | |
| Jing Chen | University of Florida, Gainesville, FL, USA | 0000-0001-8008-8062 | |
| Anthony M Corbett | University of Rochester Medical Center, Rochester, NY, USA | 0000-0001-9545-0853 | |
| Alexandra E Cuaycal | University of Florida, Gainesville, FL, USA | 0000-0002-9060-6326 | |
| Penny Cuda | Carnegie Mellon University, Pittsburgh, PA, USA | 0009-0002-6547-2650 | |
| Dinh Diep | University of California, San Diego, CA, USA; Currently - Altos Labs, San Diego, CA, USA | 0000-0001-6057-4119 | |
| Sergii Domanskyi | The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA | 0000-0002-6847-6019 | |
| Sean Donahue | Carnegie Mellon University, Pittsburgh, PA, USA | 0000-0002-4072-2046 | |
| Michael P Duffy | University of Pennsylvania, Philadelphia PA, USA | 0000-0001-5325-3683 | |
| Michael T Eadon | Indiana University School of Medicine, Indianapolis, IN, USA | 0000-0003-3066-2876 | |
| Jean Fan | Johns Hopkins University, Baltimore, MD, USA | 0000-0002-0212-5451 | |
| Melissa A Farrow | Vanderbilt University, Nashville, TN, USA | 0000-0002-1602-2082 | |
| Kathleen M Fisch | University of California San Diego, La Jolla, CA, USA | 0000-0002-0117-7444 | |
| William F Flynn | The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA | 0000-0001-6533-0340 | |
| James M Fulcher | Pacific Northwest National Laboratory, Richland, WA, USA | 0000-0001-9033-3623 | |
| Soumya Ghose | GE HealthCare, Niskayuna, NY, USA | 0000-0002-2730-1482 | |
| Fiona Ginty | GE HealthCare, Niskayuna, NY, USA | 0000-0001-6638-683X | |
| Joana P Gonçalves | Delft University of Technology, Delft, The Netherlands | 0000-0001-6072-9627 | |
| Yongqun He | University of Michigan, Ann Arbor, MI, USA | 0000-0001-9189-9661 | |
| Po Hu | Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA | 0000-0003-2422-1652 | |
| Sanjay Jain | Washington University School of Medicine, St. Louis, MO, USA | 0000-0003-2804-127X | |
| Thomas V Karathanos | Stanford University, Stanford, CA, USA | 0000-0003-1754-3872 | |
| Madhurima Kaushal | Washington University School of Medicine | 0000-0003-2760-0586 | |
| Angela RS Kruse | Vanderbilt University, Nashville, TN, USA; Currently - The Ohio State University, Columbus, OH, USA | 0000-0001-8776-2769 | |
| Yumi Kwon | Pacific Northwest National Laboratory, Richland, WA, USA | 0000-0003-0523-6197 | |
| Blue B Lake | University of California San Diego, La Jolla, CA, USA; Currently - Altos Labs, San Diego, CA, USA | 0000-0002-8637-9044 | |
| Roy Lardenoije | Delft University of Technology, Delft, The Netherlands | 0000-0002-9026-7870 | |
| Shin Lin | Emory University, Atlanta, GA, USA | 0000-0003-0118-0413 | |
| Yiing Lin | Washington University, St. Louis, MO, USA | 0000-0002-0317-7608 | |
| Scott A Lindsay | University of California, San Diego, CA, USA | 0000-0002-2929-7755 | |
| Peiran Lu | Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA | 0009-0001-5096-3046 | |
| Clayton Mathews | University of Florida, Gainesville, FL, USA | 0000-0002-8817-6355 | |
| Elizabeth McDonough | GE HealthCare, Niskayuna, NY, USA | 0000-0001-7524-8260 | |
| Ricardo Melo Ferreira | Indiana University School of Medicine, Indianapolis, IN, USA | 0000-0003-2063-9744 | |
| Emma M Monte | Stanford University, Stanford, CA, USA | 0000-0003-2566-1967 | |
| Kathleen O’Neill | University of Pennsylvania, Philadelphia PA, USA | 0000-0003-1980-6840 | |
| Minxing Pang | University of Pennsylvania, Philadelphia PA, USA | 0000-0001-5208-5972 | |
| Mana Parast | University of California San Diego, La Jolla, CA, USA | 0000-0001-5963-2246 | |
| Liming Pei | Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA | 0000-0002-1924-0333 | |
| Samuel Peters | University of Minnesota, Minneapolis, MN, USA | 0000-0003-1479-8087 | |
| Ajay Pillai | National Institute of Health, Bethesda, MD, USA | 0000-0002-9789-7189 | |
| Gloria Pryhuber | University of Rochester Medical Center, Rochester, NY, USA | 0000-0002-9185-3994 | |
| Ling Qin | University of Pennsylvania, Philadelphia PA, USA | 0000-0002-2582-0078 | |
| Presha Rajbhandari | Columbia University, NYC, NY, USA | 0000-0003-2184-7238 | |
| Matthew M Ruffalo | Carnegie Mellon University, Pittsburgh, PA, USA | 0000-0003-2222-6169 | |
| Pinaki Sarder | University of Florida, Gainesville, FL, USA | 0000-0003-2450-5233 | |
| Diane C Saunders | Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA; Northwestern University, Chicago, IL, USA | 0000-0002-8849-6746 | |
| Kevin Schneider | Buck Institute, Novato, CA, USA | 0009-0001-8046-0167 | |
| Lingyan Shi | University of California San Diego, La Jolla, CA, USA | 0000-0003-1373-3206 | |
| Santhosh Sivajothi | The Jackson Laboratory for Genomic Medicine, Farmington, CT, USA | 0000-0002-8854-4517 | |
| David Smith | Children’s Hospital of Philadelphia, Philadelphia, PA, USA | 0000-0001-7858-3785 | |
| Jeff M Spraggins | Vanderbilt University, Nashville, TN, USA | 0000-0001-9198-5498 | |
| Valentina Stanley | University of California, San Diego, CA, USA | 0000-0002-2212-7796 | |
| Kai Tan | Children’s Hospital of Philadelphia, Philadelphia, PA, USA; University of Pennsylvania, Philadelphia, PA, USA | 0000-0002-9104-5567 | |
| Anusha Thadi | Children’s Hospital of Philadelphia, Philadelphia, PA, USA | 0000-0002-1271-0398 | |
| Hua Tian | Columbia University Medical Center, NYC, NY, USA | 0000-0002-3598-0219 | |
| Morgan L Turner | Harvard Medical School, Boston, MA, USA | 0000-0002-1512-9742 | |
| Ioannis S Vlachos | Beth Israel Deaconess Medical Center, Boston, MA, USA; Harvard Cancer Center, Boston, MA, USA; Broad Institute of MIT and Harvard, Boston, MA, USA | 0000-0002-8849-808X | |
| Seth Winfree | University of Nebraska Medical Center, Omaha, NE, USA; Currently - QCDx Inc, Farmington, CT, USA | ||
| Pei-Hsun Wu | Johns Hopkins University, Baltimore, MD, USA | 0000-0002-7371-2960 | |
| Kevin J Zemaitis | Pacific Northwest National Laboratory, Richland, WA, USA | 0000-0002-3524-9776 | |
| Mowei Zhou | Pacific Northwest National Laboratory, Richland, WA, USA; Currently - Zhejiang University, Hangzhou, Zhejiang 310058, China | 0000-0003-3575-3224 | |
| Chenchen Zhu | Department of Genetics, Stanford University, Stanford, CA, USA | 0000-0003-2165-9456 |