Geometric Learning of Biomolecular Structure- [electronic resource]
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Geometric Learning of Biomolecular Structure- [electronic resource]
- 자료유형
- 학위논문파일 국외
- 최종처리일시
- 20240214101306
- ISBN
- 9798379869656
- DDC
- 006
- 서명/저자
- Geometric Learning of Biomolecular Structure - [electronic resource]
- 발행사항
- [S.l.]: : Stanford University., 2021
- 발행사항
- Ann Arbor : : ProQuest Dissertations & Theses,, 2021
- 형태사항
- 1 online resource(98 p.)
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-01, Section: B.
- 주기사항
- Advisor: Dror, Ron;Altman, Russ;Kundaje, Anshul.
- 학위논문주기
- Thesis (Ph.D.)--Stanford University, 2021.
- 사용제한주기
- This item must not be sold to any third party vendors.
- 초록/해제
- 요약The shape of a macromolecule such as a protein, RNA, or DNA, is intrinsically linked to its biological function. Better reasoning about these shapes may unlock new scientific discoveries in human health and open a path towards the rational design of novel medicines and materials. I demonstrate the potential of machine learning in this area by discussing the design of a new class of neural networks that are geometric in nature: they exploit the three-dimensional arrangement of atoms-thereby modeling the underlying physical processes of molecular structure-to generalize to new and unseen molecules. These results point to machine learning as an area of great promise for structural biology.
- 일반주제명
- Carbon.
- 일반주제명
- Neural networks.
- 일반주제명
- Symmetry.
- 일반주제명
- Design.
- 일반주제명
- Amino acids.
- 일반주제명
- Information processing.
- 일반주제명
- Engineering.
- 일반주제명
- Biology.
- 일반주제명
- Interfaces.
- 일반주제명
- Statistics.
- 기타저자
- Stanford University.
- 기본자료저록
- Dissertations Abstracts International. 85-01B.
- 기본자료저록
- Dissertation Abstract International
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
