國立虎尾科技大學 |

Computational Methods for Multi-Scale Biological Imaging and Modeling.

紀錄類型:	書目-語言資料,手稿 : Monograph/item
正題名/作者:	Computational Methods for Multi-Scale Biological Imaging and Modeling./
作者:	Li, Po-Nan.
面頁冊數:	1 online resource (167 pages)
附註:	Source: Dissertations Abstracts International, Volume: 84-05, Section: B.
Contained By:	Dissertations Abstracts International84-05B.
標題:	Mathematics. -
電子資源:	click for full text (PQDT)
ISBN:	9798357504913

Computational Methods for Multi-Scale Biological Imaging and Modeling.
Li, Po-Nan.

Computational Methods for Multi-Scale Biological Imaging and Modeling. - 1 online resource (167 pages)

Source: Dissertations Abstracts International, Volume: 84-05, Section: B.

Thesis (Ph.D.)--Stanford University, 2022.

Includes bibliographical references

Advances of microscopic technologies and imaging instrumentation have enabled several major discoveries in biology, many of which would have been impossible without the assistance of computational techniques. On the other hand, while the resulting images carry abundance of information for human eyes, even more insights might be revealed by using advanced analysis or images-based modeling, which are made possible by computational approaches. In this dissertation, we demonstrate how computational methods can assist biological studies with multi-scale tools by presenting a series of projects that utilize computational tools to enhance, make use of, or extract information from images. We first propose a computational imaging method that is capable of combining diffraction and lens-based images to deliver images with higher resolution. We then discuss how a diffusion-reaction model can help us reveal the extraordinary capacity of nutrient acquisition of surface layers, a family of crystalline proteins that are found in many bacteria and most of archaea. Finally, we report a machine learning pipeline that can build an atomic protein model into a cryogenic electron microscopy map in a fraction of a minute. Taken together, these methods demonstrate how the interplay of imaging, modeling and machine learning can enable new discoveries for structural biology, and pave paths toward more automatic and efficient structure determination.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798357504913Subjects--Topical Terms:

527692
Mathematics.
Index Terms--Genre/Form:

554714
Electronic books.

Computational Methods for Multi-Scale Biological Imaging and Modeling.
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