Molecular Complexity to Biosignatures: A Machine Learning Pipeline that Connects Mass Spectrometry to Molecular Synthesis and Reaction Networks
- ADS bibcode
- 2022AGUFM.P25A..75G
- year
- 2022
- Listed Authors
- Gong, Jian
- Bell, Aaron C.
- Gebhard, Timothy
- Hastings, Jaden J. A.
- Baydin, Atılım Güneş
- Warren-Rhodes, Kimberly
- Phillips, Michael
- Fricke, Matthew
- Cabrol, Nathalie A.
- Sandford, Scott A.
- Mascaro, Massimo
- Listed Institutions
- Massachusetts Institute of Technology, Cambridge, United States
- Insight Edge Inc., Tokyo-to, Japan
- Max Planck Institute for Intelligent Systems, Tübingen, Germany
- Weill Cornell Medicine, New York, United States
- University of Oxford, Oxford, United Kingdom
- SETI Institute Mountain View, Mountain View, United States
- Applied Physics Laboratory Johns Hopkins, Laurel, United States
- University of New Mexico, Albuquerque, United States
- SETI Institute, Mountain View, United States
- NASA Ames Research Center, Moffett Field, United States
- Google, Mountain View, United States
Linked Authors [?]
Linked Institutions