Zobrazeno 1 - 10
of 10
pro vyhledávání: '"Natalie C. Heller"'
Autor:
Song Feng, Emily Heath, Brett Jefferson, Cliff Joslyn, Henry Kvinge, Hugh D. Mitchell, Brenda Praggastis, Amie J. Eisfeld, Amy C. Sims, Larissa B. Thackray, Shufang Fan, Kevin B. Walters, Peter J. Halfmann, Danielle Westhoff-Smith, Qing Tan, Vineet D. Menachery, Timothy P. Sheahan, Adam S. Cockrell, Jacob F. Kocher, Kelly G. Stratton, Natalie C. Heller, Lisa M. Bramer, Michael S. Diamond, Ralph S. Baric, Katrina M. Waters, Yoshihiro Kawaoka, Jason E. McDermott, Emilie Purvine
Publikováno v:
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
Abstract Background Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way rel
Externí odkaz:
https://doaj.org/article/3730664a2b894f34b1b4e404f44398c0
Autor:
Hugh D. Mitchell, Amie J. Eisfeld, Kelly G. Stratton, Natalie C. Heller, Lisa M. Bramer, Ji Wen, Jason E. McDermott, Lisa E. Gralinski, Amy C. Sims, Mai Q. Le, Ralph S. Baric, Yoshihiro Kawaoka, Katrina M. Waters
Publikováno v:
Frontiers in Cell and Developmental Biology, Vol 7 (2019)
Despite high sequence similarity between pandemic and seasonal influenza viruses, there is extreme variation in host pathogenicity from one viral strain to the next. Identifying the underlying mechanisms of variability in pathogenicity is a critical
Externí odkaz:
https://doaj.org/article/f32b5429bcb647beb09f1399557d0417
Publikováno v:
SSRN Electronic Journal.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5b2facffceca231cb85b9178977181b9
https://doi.org/10.2139/ssrn.4135651
https://doi.org/10.2139/ssrn.4135651
Publikováno v:
2021 IEEE International Conference on Intelligence and Security Informatics (ISI).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::84d4b8d89116e14152f6bba0f19664a9
https://doi.org/10.1109/isi53945.2021.9624683
https://doi.org/10.1109/isi53945.2021.9624683
Autor:
George Chin, Natalie C. Heller, Christopher L. Ebsch, Rahul Deshmukh, Patrick Mackey, Joseph A. Cottam
Publikováno v:
IEEE BigData
In the real world, data does not come neatly packaged. Instead, it typically comes as small updates from many sources with different conventions. Building a single, cohesive knowledge-base to work from requires merging small updates from many differe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2ab7da8b10859d7cf32f36a30b0b3b0e
https://doi.org/10.1109/bigdata50022.2020.9378064
https://doi.org/10.1109/bigdata50022.2020.9378064
Publikováno v:
IEEE BigData
The subgraph matching problem is a fundamental problem in graph theory that is known to be NP-complete. In this study, performers were asked to develop algorithms to search for semantic property graphs that were subgraphs of a large knowledge graph.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e79df35df1e3fe7fb4a1bbf5ec920d91
https://doi.org/10.1109/bigdata50022.2020.9378349
https://doi.org/10.1109/bigdata50022.2020.9378349
Publikováno v:
IEEE BigData
When searching for adversarial activity within multiple networks, one of the greatest challenges is how to accurately align entities across different channels of information. This task becomes increasingly difficult when minimal additional informatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8b37dea669e43be08e3ca472332d9627
https://doi.org/10.1109/bigdata50022.2020.9377777
https://doi.org/10.1109/bigdata50022.2020.9377777
Autor:
Peter Halfmann, Lisa M. Bramer, Song Feng, Vineet D. Menachery, Natalie C. Heller, Jacob Kocher, Katrina M. Waters, Amy C. Sims, Michael S. Diamond, Emilie Purvine, Emily Heath, Henry Kvinge, Qing Tan, Kevin B. Walters, Brenda Praggastis, Brett Jefferson, Kelly G. Stratton, Adam S. Cockrell, Jason E. McDermott, Ralph S. Baric, Larissa B. Thackray, Yoshihiro Kawaoka, Shufang Fan, Timothy P. Sheahan, Cliff A. Joslyn, Danielle Westhoff-Smith, Amie J. Eisfeld, Hugh D. Mitchell
Publikováno v:
BMC Bioinformatics
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
BMC Bioinformatics, Vol 22, Iss 1, Pp 1-21 (2021)
Background Representing biological networks as graphs is a powerful approach to reveal underlying patterns, signatures, and critical components from high-throughput biomolecular data. However, graphs do not natively capture the multi-way relationship
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::16d340fe08ffb5d60c4a47f53458dcf6
Autor:
Natalie C. Heller, Alaine M. Garrett, Karen L. Wahl, Angela M. Melville, Jennifer S. Arce, Stephen R. Cendrowski, Kristin H. Jarman, Sarah C. Jenson, Eric D. Merkley
Publikováno v:
Analytical chemistry. 91(19)
Robust and highly specific methods for the detection of the protein toxin ricin are of interest to the law enforcement community. In previous studies, methods based on liquid chromatography-tandem mass spectrometry shotgun proteomics have been propos
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c8236494754ed91cc4f55d0270a6c7af
https://pubmed.ncbi.nlm.nih.gov/31490662
https://pubmed.ncbi.nlm.nih.gov/31490662
Autor:
Brooke L. Deatherage Kaiser, Eric D. Merkley, David S. Wunschel, Natalie C. Heller, Kristin H. Jarman, Sarah C. Jenson, Samuel H. Payne, Janine R. Hutchison
Publikováno v:
Journal of proteome research. 17(9)
Bottom-up proteomics is increasingly being used to characterize unknown environmental, clinical, and forensic samples. Proteomics-based bacterial identification typically proceeds by tabulating peptide "hits" (i.e., confidently identified peptides) a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::bfe5598b044c7e4bd68b1aabb4203967
https://pubmed.ncbi.nlm.nih.gov/30109807
https://pubmed.ncbi.nlm.nih.gov/30109807