cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.25582/data.2024-04.3089060/2555393
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089061/2555394
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089062/2555395
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089063/2555396
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089064/2555397
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089068/2555398
title: Data for EMSL Project 51287 from April 2024
DOI: 10.25582/data.2024-04.3089069/2555399
title: Data for EMSL Project 51287 from April 2024
DOI: 10.48597/sx9w-mj6k
title: Measurement of Sulphur_dioxide at Narberth

description: Measurement of Sulphur_dioxide at Narberth
DOI: 10.48597/t393-6exe
title: Measurement of Sulphur_dioxide at Narberth

description: Measurement of Sulphur_dioxide at Narberth
DOI: 10.48597/tcnw-222z
title: Measurement of Copper at Campisabalos

description: Measurement of Copper at Campisabalos
DOI: 10.48597/tm6t-6kja
title: Measurement of Nitrate at Campisabalos

description: Measurement of Nitrate at Campisabalos
DOI: 10.48597/tmmb-dnz6
title: Measurement of pH at Eskdalemuir

description: Measurement of pH at Eskdalemuir
DOI: 10.48597/u3qf-4md2
title: Measurement of Sulphur_dioxide at Auchencorth Moss

description: Measurement of Sulphur_dioxide at Auchencorth Moss
DOI: 10.48597/uxn4-fr84
title: Measurement of Potassium at Campisabalos

description: Measurement of Potassium at Campisabalos
DOI: 10.48597/v9hk-huk5
title: Measurement of Sulphur_dioxide at Lullington Heath

description: Measurement of Sulphur_dioxide at Lullington Heath
DOI: 10.48597/va8m-mh9u
title: Measurement of Sulphur_dioxide at Ladybower Res.

description: Measurement of Sulphur_dioxide at Ladybower Res.
DOI: 10.48597/vg29-xbe3
title: Measurement of Magnesium at Eskdalemuir

description: Measurement of Magnesium at Eskdalemuir
DOI: 10.48597/vkke-zw3u
title: Measurement of Precipitation_amount at Eskdalemuir

description: Measurement of Precipitation_amount at Eskdalemuir
DOI: 10.17630/dad0f61a-16cd-4c57-bb87-ea19d462074c
title: Underpinning Data - On-demand final state control of a surface-bound bistable single molecule switch
DOI: 10.25380/iastate.24052284
title: Mapping of S gene segments of Mammalian orthoreovirus.

description: Determination of sequences at gene segment termini that play a critical role in Mammalian orthoreovirus S gene segment packaging. This contains the raw data from reverse genetics, plaque assays, immunoblotting, trans-complementation assay, RT-qPCR and NanoLuc assays. Data is presented in the form of .xlsx, .pdf, .tif, and .txt files.Change log: Additional files uploaded and readme document updated 02/12/24. Additions include plasmid sequences.txt, immunofluorescence assay images 1.tif and 2.tif, immunpblot sig 1 and sNS with 9 other proteins.pdf, and three .xlsx files (WB with all proteins expressed, Repn assay of 200-S1 18-S1-40 and S1WT, and IFA of 200-S1-200 18-S1-40 and S1WT).Related material entries added 03/06/24.
DOI: 10.25380/iastate.24052284.v2
title: Mapping of S gene segments of Mammalian orthoreovirus.

description: Determination of sequences at gene segment termini that play a critical role in Mammalian orthoreovirus S gene segment packaging. This contains the raw data from reverse genetics, plaque assays, immunoblotting, trans-complementation assay, RT-qPCR and NanoLuc assays. Data is presented in the form of .xlsx, .pdf, .tif, and .txt files.Change log: Additional files uploaded and readme document updated 02/12/24. Additions include plasmid sequences.txt, immunofluorescence assay images 1.tif and 2.tif, immunpblot sig 1 and sNS with 9 other proteins.pdf, and three .xlsx files (WB with all proteins expressed, Repn assay of 200-S1 18-S1-40 and S1WT, and IFA of 200-S1-200 18-S1-40 and S1WT).Related material entries added 03/06/24.
DOI: 10.25380/iastate.24052284.v1
title: Mapping of S gene segments of Mammalian orthoreovirus

description: Determination of sequences at gene segment termini that play a critical role in Mammalian orthoreovirus S gene segment packaging. This contains the raw data from reverse genetics, plaque assays, immunoblotting, trans-complementation assay, RT-qPCR and NanoLuc assays. Data is presented in the form of .xlsx, .pdf, .tif, and .txt files.Change log: Additional files uploaded and readme document updated 02/12/24. Additions include plasmid sequences.txt, immunofluorescence assay images 1.tif and 2.tif, immunpblot sig 1 and sNS with 9 other proteins.pdf, and three .xlsx files (WB with all proteins expressed, Repn assay of 200-S1 18-S1-40 and S1WT, and IFA of 200-S1-200 18-S1-40 and S1WT).Related material entries added 03/06/24.
DOI: 10.6084/m9.figshare.25352899
title: Comparison of tools to support healthy young citrus plantings in a region with endemic huanglongbing, <i>C</i>Las, and Asian citrus psyllid (<i>Diaphorina citri</i>)

description: Datasets accompanying the identically titled publication with the following abstract: <br>The Florida citrus industry has been devastated by huanglongbing (HLB), a fatal citrus disease vectored by the Asian citrus psyllid (ACP). Current management relies primarily on insecticides to reduce vector populations. Growers are interested in options for protecting new plantings including individual protective covers (IPCs), reflective mulch ground cover, and red-dyed kaolin particle films. We tested the efficacy of these tools in reducing ACP densities on young citrus trees against a grower standard control. We also quantified the effects of these treatments on other citrus pests, including citrus leafminer, spider mites, and citrus rust mites, as well as on the incidence and severity of plant pathogens, including huanglongbing and its associated pathogen (<i>Candidatus</i> Liberibacter asiaticus), citrus canker, greasy spot, sooty mold, and melanose. Among these treatments, the IPCs successfully excluded ACP, with no covered trees infected with HLB after two years. Trees in this treatment also showed the lowest densities of citrus leafminer infestation and citrus canker incidence. However, trees under IPCs were susceptible to other issues including sooty mold and spider mites, suggesting that there are trade-offs with using this tool. Trees in the reflective mulch and kaolin treatments did not have reduced infestation of key citrus pests and pathogens compared to the grower standard for key citrus pests and pathogens. Although IPCs are not a silver bullet for all citrus ailments, we show that they are a promising tool for protecting young citrus trees from ACP and HLB.
DOI: 10.48597/vkqm-zzyr
title: Measurement of Magnesium at Eskdalemuir

description: Measurement of Magnesium at Eskdalemuir
DOI: 10.48597/vm22-duan
title: Measurement of Sulphur_dioxide at Auchencorth Moss

description: Measurement of Sulphur_dioxide at Auchencorth Moss
DOI: 10.48597/vqrj-ukn8
title: Measurement of Nitrate at Eskdalemuir

description: Measurement of Nitrate at Eskdalemuir
DOI: 10.48597/vw2w-pbg3
title: Measurement of Precipitation_amount at Eskdalemuir

description: Measurement of Precipitation_amount at Eskdalemuir
DOI: 10.48597/vxmq-rtnu
title: Measurement of Inorganics in air and particle phase at Malin Head

description: Measurement of Inorganics in air and particle phase at Malin Head
DOI: 10.48597/w4tj-ue4f
title: Measurement of Nickel at Campisabalos

description: Measurement of Nickel at Campisabalos
DOI: 10.48597/wt9z-3eh2
title: Measurement of Zinc at Campisabalos

description: Measurement of Zinc at Campisabalos
DOI: 10.48597/xat4-scq3
title: Measurement of Pm10_mass at Narberth

description: Measurement of Pm10_mass at Narberth
DOI: 10.48597/xjyr-5jgn
title: Measurement of Pm10_mass at Narberth

description: Measurement of Pm10_mass at Narberth
DOI: 10.48597/xshy-52gz
title: Measurement of Inorganics in air and particle phase at Valentia Observatory

description: Measurement of Inorganics in air and particle phase at Valentia Observatory
DOI: 10.48597/y78d-s4cy
title: Measurement of Magnesium at Lough Navar

description: Measurement of Magnesium at Lough Navar
DOI: 10.48597/ym5z-a6w8
title: Measurement of Sulphur_dioxide at Ladybower Res.

description: Measurement of Sulphur_dioxide at Ladybower Res.
DOI: 10.48597/zj8h-wsz9
title: Measurement of Pm10_mass at Lough Navar

description: Measurement of Pm10_mass at Lough Navar
DOI: 10.48597/zsq5-k4tq
title: Measurement of Sulphate_total at Yarner Wood

description: Measurement of Sulphate_total at Yarner Wood
DOI: 10.48597/zwu6-ds5g
title: Measurement of Pm10_mass at Chilbolton Observatory

description: Measurement of Pm10_mass at Chilbolton Observatory
DOI: 10.48597/3hht-3qv8
title: Measurement of Calcium at Norunda Stenen

description: Measurement of Calcium at Norunda Stenen
DOI: 10.48597/446r-3r8w
title: Measurement of Ammonia at Norunda Stenen

description: Measurement of Ammonia at Norunda Stenen
DOI: 10.48597/4epy-nkb9
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/5dhw-86fa
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/5scf-vbh5
title: Measurement of Sulphate_total at Ammarnäs

description: Measurement of Sulphate_total at Ammarnäs
DOI: 10.48597/5tsu-3fhd
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/6j5x-w38p
title: Measurement of Nitrate at Norunda Stenen

description: Measurement of Nitrate at Norunda Stenen
DOI: 10.48597/7hay-ejte
title: Measurement of Conductivity at Abisko

description: Measurement of Conductivity at Abisko
DOI: 10.48597/8ww8-c4ha
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/9pvx-ejxk
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/ac2d-4wfe
title: Measurement of Calcium at Rickleå

description: Measurement of Calcium at Rickleå
DOI: 10.48597/ag26-64q2
title: Measurement of Chloride at Norunda Stenen

description: Measurement of Chloride at Norunda Stenen
DOI: 10.48597/c2fn-wdyg
title: Measurement of Calcium at Ammarnäs

description: Measurement of Calcium at Ammarnäs
DOI: 10.48597/cdcn-jvez
title: Measurement of Magnesium at Rickleå

description: Measurement of Magnesium at Rickleå
DOI: 10.48597/cz5r-nqbe
title: Measurement of pH at Ammarnäs

description: Measurement of pH at Ammarnäs
DOI: 10.48597/czkj-9srh
title: Measurement of Particle_number_size_distribution at Finokalia

description: Measurement of Particle_number_size_distribution at Finokalia
DOI: 10.48597/d5bg-v72n
title: Measurement of Potassium at Abisko

description: Measurement of Potassium at Abisko
DOI: 10.48597/djkv-hzyb
title: Measurement of Ammonium at Abisko

description: Measurement of Ammonium at Abisko
DOI: 10.48597/dskk-mxz3
title: Measurement of Ammonium at Rickleå

description: Measurement of Ammonium at Rickleå
DOI: 10.48597/e5bb-mgkc
title: Measurement of Pm25_mass at Norunda Stenen

description: Measurement of Pm25_mass at Norunda Stenen
DOI: 10.48597/ejv7-qdss
title: Measurement of Chloride at Ammarnäs

description: Measurement of Chloride at Ammarnäs
DOI: 10.48597/ekgt-pse4
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/ez2s-5twu
title: Measurement of Chloride at Abisko

description: Measurement of Chloride at Abisko
DOI: 10.48597/fra6-afyp
title: Measurement of Ammonium at Ammarnäs

description: Measurement of Ammonium at Ammarnäs
DOI: 10.48597/g3kr-kbtf
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/h5kt-sbep
title: Measurement of Pm10_mass at Norunda Stenen

description: Measurement of Pm10_mass at Norunda Stenen
DOI: 10.48597/j89m-6h2p
title: Measurement of Conductivity at Rickleå

description: Measurement of Conductivity at Rickleå
DOI: 10.48597/jn3h-fgrc
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/kh88-p8xx
title: Measurement of Sulphate_total at Rickleå

description: Measurement of Sulphate_total at Rickleå
DOI: 10.48597/mvtd-xtty
title: Measurement of Sodium at Abisko

description: Measurement of Sodium at Abisko
DOI: 10.48597/n82y-ha9h
title: Measurement of Ammonium at Norunda Stenen

description: Measurement of Ammonium at Norunda Stenen
DOI: 10.48597/nadh-rf7c
title: Measurement of Magnesium at Abisko

description: Measurement of Magnesium at Abisko
DOI: 10.48597/px8p-7fhe
title: Measurement of 123789_HxCDF at Norunda Stenen

description: Measurement of 123789_HxCDF at Norunda Stenen
DOI: 10.48597/sxmr-qqpj
title: Measurement of Sodium at Rickleå

description: Measurement of Sodium at Rickleå
DOI: 10.48597/t3fp-z3w7
title: Measurement of Particle_number_size_distribution at Finokalia

description: Measurement of Particle_number_size_distribution at Finokalia
DOI: 10.48597/t5w5-bbs6
title: Measurement of Precipitation_amount at Rickleå

description: Measurement of Precipitation_amount at Rickleå
DOI: 10.48597/tk4d-g8bw
title: Measurement of Particle_number_size_distribution at Helmos Mountain

description: Measurement of Particle_number_size_distribution at Helmos Mountain
DOI: 10.48597/u3m9-5anp
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/u9z8-g5a3
title: Measurement of Magnesium at Ammarnäs

description: Measurement of Magnesium at Ammarnäs
DOI: 10.48597/ufab-zdgq
title: Measurement of pH at Rickleå

description: Measurement of pH at Rickleå
DOI: 10.48597/upjk-wfab
title: Measurement of Chloride at Rickleå

description: Measurement of Chloride at Rickleå
DOI: 10.48597/v2be-xwqh
title: Measurement of 2378_TCDF at Norunda Stenen

description: Measurement of 2378_TCDF at Norunda Stenen
DOI: 10.48597/vmb2-s574
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.48597/vqp8-mghj
title: Measurement of Aerosol_absorption_coefficient at Anmyeon-do

description: Measurement of Aerosol_absorption_coefficient at Anmyeon-do
DOI: 10.17630/0cc71494-7e2f-49f3-bc98-c3b3768a4c65
title: Data underpinning: Sparse labeling PELDOR spectroscopy on multimeric mechanosensitive membrane channels
DOI: 10.17630/ddaebfb9-e127-43cb-9048-966a572b50ac
title: Size dependence efficiency of PbS quantum dots in NiO-based dye sensitised solar cells and mechanistic charge transfer investigation (dataset)

description: The data files are not yet publicly available. Enquiries and requests for data should be directed to the publication's corresponding authors:

Raissi, M., Sajjad, M. T., Pellegrin, Y., Roland, T. J., Jobic, S., Boujtita, M., ... Odobel, F. (2017). Size dependence of efficiency of PbS quantum dots in NiO-based dye sensitised solar cells and mechanistic charge transfer investigation. Nanoscale, 9(40), 15566-15575. DOI: 10.1039/C7NR03698A
DOI: 10.5281/zenodo.10789473
title: A multi-omics systems vaccinology resource to develop and test computational models of immunity: 1st challenge dataset and submissions

description: The goal of the CMI-PB prediction contest is to foster a collaborative research community that can collectively tackle challenges and accelerates scientific progress beyond the capabilities of individual researchers or groups. The CMI-PB consortium has curated multi-source data from multiple individuals, encompassing Ab titers (around four antibodies/features), cell frequency (approximately 20 cell types/features), gene expression (roughly 50,000 RNA transcripts/features), and plasma proteomics (around 50 proteins/features). The challenge requires integrating these diverse data sources to predict different immune responses or tasks. Specifically, you will utilize multi-source data from several individuals on day 0 (baseline) to predict specific immune responses at later time points (1, 3, 7, and  14 days post-booster vaccination).

The first CMI-PB challenge, which is an internal challenge, was conducted using datasets from 2020 (train) and 2021 (test). In the following sections, we provide detailed information on the datasets, challenge tasks, submission format, descriptions, and access to the necessary data files for participants to develop their models and make predictions.

A) Multiomics CMI-PB dataset:

We propose a study design that enables a systems-level understanding of the immune responses through computational modeling. Our cohort comprises aP vs. wP infancy-primed subjects boosted with Tdap. We recruit individuals born before 1995 (wP) and after 1996 (aP), collect baseline plasma and blood samples, and then at 1, 3, 7 and  14 days post booster vaccination.

With the obtained samples processed, we generated omics data by:





Bulk PBMCs transcriptomics,




Plasma proteomics using Olink, which provides a quantitative readout of cytokines, chemokines, and other immune factors,




Cell frequency in PBMCs using flow cytometry,




Tdap-specific antibodies levels



B) List of tasks can be accessed using the “List of tasks for challenge 1.docx” file, and submissions need to submit in provided format here: “submission template challenge 1.tsv”

C) Datasets for model building and making predictions:

    Data files are divided into two categories: 1) raw dataset and 2) computable matrices.





Raw dataset: This raw-most dataset is divided into training and test datasets. 




Computable matrices: There are three different types of computable matrices. a) Full: These files are generated by dividing raw files into sub-files specific to planned days specific to vaccination. b) harmonized: These are generated by preserving only overlapping features between train and test datasets. b) imputed: MICE imputation is performed to impute missing values in the dataset.



D) Submission evaluation

This folder contains all submitted models with ranking files and code for evaluating these models.

To learn more about the CMI-PB prediction challenge, visit our website at www.cmi-pb.org.
DOI: 10.5281/zenodo.7702789
title: A multi-omics systems vaccinology resource to develop and test computational models of immunity: 1st challenge dataset and submissions

description: The goal of the CMI-PB prediction contest is to foster a collaborative research community that can collectively tackle challenges and accelerates scientific progress beyond the capabilities of individual researchers or groups. The CMI-PB consortium has curated multi-source data from multiple individuals, encompassing Ab titers (around four antibodies/features), cell frequency (approximately 20 cell types/features), gene expression (roughly 50,000 RNA transcripts/features), and plasma proteomics (around 50 proteins/features). The challenge requires integrating these diverse data sources to predict different immune responses or tasks. Specifically, you will utilize multi-source data from several individuals on day 0 (baseline) to predict specific immune responses at later time points (1, 3, 7, and  14 days post-booster vaccination).

The first CMI-PB challenge, which is an internal challenge, was conducted using datasets from 2020 (train) and 2021 (test). In the following sections, we provide detailed information on the datasets, challenge tasks, submission format, descriptions, and access to the necessary data files for participants to develop their models and make predictions.

A) Multiomics CMI-PB dataset:

We propose a study design that enables a systems-level understanding of the immune responses through computational modeling. Our cohort comprises aP vs. wP infancy-primed subjects boosted with Tdap. We recruit individuals born before 1995 (wP) and after 1996 (aP), collect baseline plasma and blood samples, and then at 1, 3, 7 and  14 days post booster vaccination.

With the obtained samples processed, we generated omics data by:





Bulk PBMCs transcriptomics,




Plasma proteomics using Olink, which provides a quantitative readout of cytokines, chemokines, and other immune factors,




Cell frequency in PBMCs using flow cytometry,




Tdap-specific antibodies levels



B) List of tasks can be accessed using the “List of tasks for challenge 1.docx” file, and submissions need to submit in provided format here: “submission template challenge 1.tsv”

C) Datasets for model building and making predictions:

    Data files are divided into two categories: 1) raw dataset and 2) computable matrices.





Raw dataset: This raw-most dataset is divided into training and test datasets. 




Computable matrices: There are three different types of computable matrices. a) Full: These files are generated by dividing raw files into sub-files specific to planned days specific to vaccination. b) harmonized: These are generated by preserving only overlapping features between train and test datasets. b) imputed: MICE imputation is performed to impute missing values in the dataset.



D) Submission evaluation

This folder contains all submitted models with ranking files and code for evaluating these models.

To learn more about the CMI-PB prediction challenge, visit our website at www.cmi-pb.org.