Zobrazeno 1 - 5
of 5
pro vyhledávání: '"Ilya B. Novikov"'
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 3, p e1007583 (2020)
Functional non-coding (fnc)RNAs are nucleotide sequences of varied lengths, structures, and mechanisms that ubiquitously influence gene expression and translation, genome stability and dynamics, and human health and disease. Here, to shed light on th
Externí odkaz:
https://doaj.org/article/d19255fad83e4b10a3cfcdb700d83338
Autor:
Ilya B. Novikov, Tajhal Dayaram, Neha Parikh, Griff Weber, Angela D. Wilkins, Scott Spangler, Sam Regenbogen, Ying Chen, Linda Kato, Ana Lelescu, Shenghua Bao, Benjamin J. Bachman, Byung-Kwon Choi, Houyin Zhang, Anbu Karani Adikesavan, Curtis R. Pickering, Lawrence A. Donehower, Meena Nagarajan, Christie M. Buchovecky, Kenneth L. Scott, Jacques L. Labrie, Olivier Lichtarge, Sung Yun Jung, Peter J. Haas, Stephen K. Boyer
Publikováno v:
Proceedings of the National Academy of Sciences of the United States of America
Significance We adapted natural language processing to the biological literature and demonstrated end-to-end automated knowledge discovery by exploring subtle word connections. General text mining scanned 21 million publication abstracts and selected
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::77d9a167c44ea6895d38cb1e4365a2af
https://doi.org/10.1073/pnas.1806643115
https://doi.org/10.1073/pnas.1806643115
Publikováno v:
PLoS Computational Biology, Vol 16, Iss 3, p e1007583 (2020)
PLoS Computational Biology
PLoS Computational Biology
Functional non-coding (fnc)RNAs are nucleotide sequences of varied lengths, structures, and mechanisms that ubiquitously influence gene expression and translation, genome stability and dynamics, and human health and disease. Here, to shed light on th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5076c0f8c8239dc16008881a56652d2d
https://doi.org/10.1371/journal.pcbi.1007583
https://doi.org/10.1371/journal.pcbi.1007583
Autor:
Lawrence A. Donehower, Curtis R. Pickering, Anbu Karani Adikesavan, Ilya B. Novikov, Linda Kato, Christie M. Buchovecky, Meenakshi Nagarajan, Angela D. Wilkins, Shenghua Bao, Andreas Martin Lisewski, Benjamin J. Bachman, Ying Chen, Sam Regenbogen, Olivier Lichtarge, Sumit Bhatia, María E. Terrón-Díaz, Jacques Joseph Labrie, Griff Weber, Ana Lelescu, Peter J. Haas, Stephen K. Boyer, Scott Spangler, Houyin Zhang
Publikováno v:
KDD
We present KnIT, the Knowledge Integration Toolkit, a system for accelerating scientific discovery and predicting previously unknown protein-protein interactions. Such predictions enrich biological research and are pertinent to drug discovery and the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::3e0373c138188c155b045ce7e85d6e7e
https://doi.org/10.1145/2783258.2788609
https://doi.org/10.1145/2783258.2788609
Autor:
Novikov, Ilya B.1 (AUTHOR), Wilkins, Angela D.2 (AUTHOR), Lichtarge, Olivier2 (AUTHOR) lichtarge@bcm.edu
Publikováno v:
PLoS Computational Biology. 3/24/2020, Vol. 16 Issue 3, p1-28. 28p. 2 Color Photographs, 1 Diagram, 6 Graphs.