The DOI matches its Crossref record; 25 of the 25 references it cites were found in a registry or an index.
ImmPort, toward repurposing of open access immunological assay data for translational and clinical research
Open accessAbstract
Immunology researchers are beginning to explore the possibilities of reproducibility, reuse and secondary analyses of immunology data. Open-access datasets are being applied in the validation of the methods used in the original studies, leveraging studies for meta-analysis, or generating new hypotheses. To promote these goals, the ImmPort data repository was created for the broader research community to explore the wide spectrum of clinical and basic research data and associated findings. The ImmPort ecosystem consists of four components– Private Data, Shared Data, Data Analysis, and Resources —for data archiving, dissemination, analyses, and reuse. To date, more than 300 studies have been made freely available through the Shared Data portal ( www.immport.org/immport-open ), which allows research data to be repurposed to accelerate the translation of new insights into discoveries.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
xCell: digitally portraying the tissue cellular heterogeneity landscape
Aran, D., Hu, Z., & Butte, A. J. (2017) · Genome Biology · doi:10.1186/s13059-017-1349-1 · Cited by 4,397
Self-citationLeinonen, R., Sugawara, H., Shumway, M., & on behalf of the International Nucleotide Sequence Database Collaboration (2011) · Nucleic Acids Research · doi:10.1093/nar/gkq1019 · Cited by 2,746
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update
Afgan, E., Baker, D., van den Beek, M., Blankenberg, D., Bouvier, D., Čech, M., Chilton, J., Clements, D., Coraor, N., Eberhard, C., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw343 · Cited by 2,148
FlowSOM: Using self‐organizing maps for visualization and interpretation of cytometry data
Van Gassen, S., Callebaut, B., Van Helden, M. J., Lambrecht, B. N., Demeester, P., Dhaene, T., & Saeys, Y. (2015) · Cytometry Part A · doi:10.1002/cyto.a.22625 · Cited by 1,919
ImmPort: disseminating data to the public for the future of immunology
Bhattacharya, S., Andorf, S., Gomes, L., Dunn, P., Schaefer, H., Pontius, J., Berger, P., Desborough, V., Smith, T., Campbell, J., et al. (2014) · Immunologic Research · doi:10.1007/s12026-014-8516-1 · Cited by 806
Self-citationLi, S., Rouphael, N., Duraisingham, S., Romero-Steiner, S., Presnell, S., Davis, C., Schmidt, D. S., Johnson, S. E., Milton, A., Rajam, G., et al. (2014) · Nature Immunology · doi:10.1038/ni.2789 · Cited by 770
NCBI’s Database of Genotypes and Phenotypes: dbGaP
Tryka, K. A., Hao, L., Sturcke, A., Jin, Y., Wang, Z. Y., Ziyabari, L., Lee, M., Popova, N., Sharopova, N., Kimura, M., et al. (2014) · Nucleic Acids Research · doi:10.1093/nar/gkt1211 · Cited by 529
Social network architecture of human immune cells unveiled by quantitative proteomics
Rieckmann, J. C., Geiger, R., Hornburg, D., Wolf, T., Kveler, K., Jarrossay, D., Sallusto, F., Shen-Orr, S. S., Lanzavecchia, A., Mann, M., et al. (2017) · Nature Immunology · doi:10.1038/ni.3693 · Cited by 385
Self-citationQian, Y., Wei, C., Eun‐Hyung Lee, F., Campbell, J., Halliley, J., Lee, J. A., Cai, J., Kong, Y. M., Sadat, E., Thomson, E., et al. (2010) · Cytometry Part B: Clinical Cytometry · doi:10.1002/cyto.b.20554 · Cited by 192
Self-citationReanalyses of Randomized Clinical Trial Data
Ebrahim, S., Sohani, Z. N., Montoya, L., Agarwal, A., Thorlund, K., Mills, E. J., & Ioannidis, J. P. A. (2014) · JAMA · doi:10.1001/jama.2014.9646 · Cited by 184
Andres-Terre, M., McGuire, H. M., Pouliot, Y., Bongen, E., Sweeney, T. E., Tato, C. M., & Khatri, P. (2015) · Immunity · doi:10.1016/j.immuni.2015.11.003 · Cited by 175
Multicohort analysis reveals baseline transcriptional predictors of influenza vaccination responses
HIPC-CHI Signatures Project Team, Avey, S., Cheung, F., Fermin, D., Frelinger, J., Gaujoux, R., Gottardo, R., Khatri, P., Kleinstein, S. H., Kotliarov, Y., et al. (2017) · Science Immunology · doi:10.1126/sciimmunol.aal4656 · Cited by 149
Self-citationLogical Development of the Cell Ontology
Meehan, T. F., Masci, A. M., Abdulla, A., Cowell, L. G., Blake, J. A., Mungall, C., & Diehl, A. D. (2011) · BMC Bioinformatics · doi:10.1186/1471-2105-12-6 · Cited by 144
PDX-MI: Minimal Information for Patient-Derived Tumor Xenograft Models
Meehan, T. F., Conte, N., Goldstein, T. C., Inghirami, G., Murakami, M. A., Brabetz, S., Gu, Z., Wiser, J. A., Dunn, P., Begley, D. A., et al. (2017) · Cancer Research · doi:10.1158/0008-5472.can-17-0582 · Cited by 139
Self-citationProtein Ontology (PRO): enhancing and scaling up the representation of protein entities
Natale, D. A., Arighi, C. N., Blake, J. A., Bona, J. P., Chen, C., Chen, S., Christie, K., Cowart, J. E., D’Eustachio, P., Diehl, A. D., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1075 · Cited by 98
Self-citationProtein Ontology: a controlled structured network of protein entities
Natale, D. A., Arighi, C. N., Blake, J. A., Bult, C. J., Christie, K., Cowart, J. E., D’Eustachio, P., Diehl, A. D., Drabkin, H., Helfer, O., et al. (2013) · Nucleic Acids Research · doi:10.1093/nar/gkt1173 · Cited by 81
Self-citationHenn, A. D., Wu, S., Qiu, X., Ruda, M., Stover, M., Yang, H., Liu, Z., Welle, S. L., Holden‐Wiltse, J., Wu, H., et al. (2013) · Scientific Reports · doi:10.1038/srep02327 · Cited by 70
Lin, Y., & He, Y. O. (2012) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-3-17 · Cited by 68
The 10,000 Immunomes Project: Building a Resource for Human Immunology
Zalocusky, K. A., Kan, M. J., Hu, Z., Dunn, P., Thomson, E., Wiser, J. A., Bhattacharya, S., & Butte, A. J. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.09.021 · Cited by 62
Self-citationThinking Outside the Gate: Single-Cell Assessments in Multiple Dimensions
Kvistborg, P., Gouttefangeas, C., Aghaeepour, N., Cazaly, A. M., Chattopadhyay, P. K., Chan, C. C. W., Eckl, J., Finak, G., Hadrup, S. R., Maecker, H. T., et al. (2015) · Immunity · doi:10.1016/j.immuni.2015.04.006 · Cited by 60
MetaCyto: A Tool for Automated Meta-analysis of Mass and Flow Cytometry Data
Hu, Z., Jujjavarapu, C., Hughey, J., Andorf, S., Lee, H.-C., Gherardini, P. F., Spitzer, M. H., Thomas, C. G., Campbell, J. P., Dunn, P., et al. (2018) · Cell Reports · doi:10.1016/j.celrep.2018.07.003 · Cited by 52
Self-citationStatistical inference of a convergent antibody repertoire response to influenza vaccine
Strauli, N. B., & Hernandez, R. D. (2016) · Genome Medicine · doi:10.1186/s13073-016-0314-z · Cited by 39
Nasrallah, M., Pouliot, Y., Hartmann, B., Dunn, P., Thomson, E., Wiser, J. A., & Butte, A. J. (2015) · Arthritis Research & Therapy · doi:10.1186/s13075-015-0778-z · Cited by 29
Self-citationToward effective sharing of high-dimensional immunology data
Snijder, B., Kandasamy, R. K., & Superti‐Furga, G. (2014) · Nature Biotechnology · doi:10.1038/nbt.2974 · Cited by 10
RImmPort: an R/Bioconductor package that enables ready-for-analysis immunology research data
Shankar, R., Bhattacharya, S., Jujjavarapu, C., Andorf, S., Wiser, J., & Butte, A. J. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btw719 · Cited by 8
Self-citation
Cited by
An atlas of the protein-coding genes in the human, pig, and mouse brain
Sjöstedt, E., Zhong, W., Fagerberg, L., Karlsson, M., Mitsios, N., Adori, C., Oksvold, P., Edfors, F., Limiszewska, A., Hikmet, F., et al. (2020) · Science · doi:10.1126/science.aay5947 · Cited by 1,151
A genome-wide transcriptomic analysis of protein-coding genes in human blood cells
Uhlen, M., Karlsson, M. J., Zhong, W., Tebani, A., Pou, C., Mikes, J., Lakshmikanth, T., Forsström, B., Edfors, F., Odeberg, J., et al. (2019) · Science · doi:10.1126/science.aax9198 · Cited by 594
The Immune Epitope Database (IEDB): 2024 update
Vita, R., Blazeska, N., Marrama, D., IEDB Curation Team Members, Shackelford, D., Zalman, L., Foos, G., Zarebski, L., Chan, K., Reardon, B., et al. (2025) · Nucleic Acids Research · doi:10.1093/nar/gkae1092 · Cited by 274
Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C. M., & Krawczyk, K. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800708 · Cited by 247
Prototype of running clinical trials in an untrustworthy environment using blockchain
Wong, D. R., Bhattacharya, S., & Butte, A. J. (2019) · Nature Communications · doi:10.1038/s41467-019-08874-y · Cited by 160
Self-citation
Metadata
- Authors
- Bhattacharya, S., Dunn, P., Thomas, C. G., Smith, B., Schaefer, H., Chen, J., Hu, Z., Zalocusky, K. A., Shankar, R. D., Shen-Orr, S. S., Thomson, E., Wiser, J., & Butte, A. J.
- Venue
- Scientific Data
- Published
- 2018-02-27
- Volume
- 5
- Issue
- 1
- Pages
- 180015-180015
- ISSN
- 2052-4463 (ISSN-L)
- OpenAlex
- W2792468812
- Cited by
- 786
- References
- 25
- Type
- data paper
- Language
- en
- Open access
- gold
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
