Bryan Heidorn

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22 Article
8 Conference contribution
3 Paper
1 Conference article
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- 1 Letter
- 1 Review article

Mapping the “long tail” of research funding: A topic analysis of NSF grant proposals in the division of astronomical sciences
Stahlman, G. R. & Heidorn, P. B., 2020, In: Proceedings of the Association for Information Science and Technology. 57, 1
Research output: Contribution to journal › Article › peer-review

Open Access
9 Link opens in a new tab Scopus citations
Astrolabe: Curating, linking, and computing astronomy's dark data
Heidorn, P. B., Stahlman, G. R. & Steffen, J., May 2018, In: Astrophysical Journal, Supplement Series. 236, 1, 3.
Research output: Contribution to journal › Article › peer-review

Open Access
10 Link opens in a new tab Scopus citations
The Astrolabe Project: Identifying and Curating Astronomical 'Dark Data' through Development of Cyberinfrastructure Resources
Stahlman, G., Bryan Heidorn, P. & Steffen, J., Jul 27 2018, Library and Information Services in Astronomy 8th: "Astronomy Librarianship in the Era of Big Data and Open Science". D'Abrusco, R., Lesteven, S., Dorch, B. & Kern, B. (eds.). EDP Sciences, 03003. (EPJ Web of Conferences; vol. 186).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Open Access
1 Link opens in a new tab Scopus citations
Where are iSchools heading?
Yadav, V., Sadeque, F., Heidorn, B. & Cui, H., 2018, Transforming Digital Worlds - 13th International Conference, iConference 2018, Proceedings. Chowdhury, G., McLeod, J., Gillet, V. & Willett, P. (eds.). Springer-Verlag, p. 665-670 6 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 10766 LNCS).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
1 Link opens in a new tab Scopus citations
Working beyond the confines of academic discipline to resolve a real-world problem: A community of scientists discussing long-tail data in the cloud
Brooks, C. F., Heidorn, P. B., Stahlman, G. R. & Chong, S. S., 2016, In: First Monday. 21, 2
Research output: Contribution to journal › Article › peer-review

Open Access
8 Link opens in a new tab Scopus citations

Predicting Phenotype from Multi-Scale Genomic and Environment Data using Neural Networks and Knowledge Graphs
Thessen, A. (Contributor), Appleby, G. (Contributor), Bartelme, R. (Contributor), Behrisch, M. (Contributor), Cooper, L. (Contributor), Heidorn, P. (Contributor), Jaiswal, P. (Contributor), LeBauer, D. (Contributor), Mosca, A. (Contributor), Munoz-Torres, M. (Contributor), Ross, A. (Contributor), Shefchek, K. (Contributor) & Swetnam, T. (Contributor), ZENODO, Aug 7 2020
DOI: 10.5281/zenodo.3975829, https://zenodo.org/record/3975829
Dataset
Predicting Phenotype from Multi-Scale Genomic and Environment Data using Neural Networks and Knowledge Graphs: An Introduction to the NSF GenoPhenoEnvo Project
Thessen, A. E. (Contributor), Behrisch, M. (Contributor), Heidorn, P. B. (Contributor), Jaiswal, P. (Contributor), LeBauer, D. (Contributor), Mosca, A. (Contributor), Munoz-Torres, M. C. (Contributor), Ross, A. (Contributor) & Swetnam, T. (Contributor), ZENODO, Jan 11 2020
DOI: 10.5281/zenodo.4439518, https://zenodo.org/record/4439518
Dataset
TOADS for Computable Phenotypes
Thessen, A. (Contributor), Ross, A. (Contributor), Heidorn, P. B. (Contributor) & Munoz-Torres, M. (Contributor), ZENODO, Jun 1 2019
DOI: 10.5281/zenodo.3763710, https://zenodo.org/record/3763710
Dataset

Bryan Heidorn

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