Grant: Discovery Grants Program - Individual
York University
$39,000.00
Inference and Model Building for Vision-based Estimation of Transmissive Objects
EF 2022-23
Résumé
This proposal seeks to further the state of the art in the field of computer vision and image processing, with the goal of expanding and reinforcing the use of imaging modalities in our understanding of the world. Images are a rich source of information which are readily captured in many scenarios. The ability to process these images and extract meaning from them is the key goal of computer vision. The long-term objective of this proposal and the PI's research program in general is the theoretical and practical development of models which enable the estimation of properties of the world from images. One such problem is the estimation of detailed 3D structure of transmissive objects. Imaging and reconstruction of such objects arises in a range of domains including: optical imaging of translucent objects like clouds, glass, water or smoke, x-ray imaging of humans and animals for medical purposes, and transmission electron imaging or materials and biological specimens.The objectives of this proposal focus on transmission electron imaging with the aim to build new methods for electron cryomicroscopy (cryo-EM). Specific problems relating to the estimation of the 3D structure of biological molecules such as proteins and viruses from cryo-EM images are considered. Cryo-EM is a rapidly emerging method for experimental structure determination of biological molecules. The function of DNA has sometimes been explained by analogy as the source code of life. Continuing this analogy, proteins and viruses are the compiled programs which take the form of molecular machines that “execute life” at a cellular level. Determining the 3D structures of these machines and understanding how they work is not only of fundamental scientific interest, it is also critical in the understanding of disease and the development of novel drugs and treatments.The research proposed here would advance the state-of-the-art and have significant impacts on cryo-EM and consequently on many aspects of science and medicine both within Canada and around the world. By improving the reliability and resolution of estimation structures, the methods proposed here would form the basis for rapid structure determination methods which could be used to more quickly develop new drugs which would be less likely to have unexpected side-effects. They would also allow scientists to study never before seen mechanisms in the cell as the motion of these molecular machines could be captured directly.
Programme
Discovery Grants Program - Individual
Bénéficiaire
Emplacement
Ontario, Canada
Type de bénéficiaire
Academia
Type
Grant
Source
NSERC's Awards Data
Tel que publié
Application id
RGPIN-2017-05638
Name nom
Brubaker, Marcus
Department département
Computer Science and Engineering - Computer Science and Engineering
Organization id
38
Institution établissement
York University
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2022
Competition year année de concours
2017
Award amount
39000
Program id
RGPIN
Program name en
Discovery Grants Program - Individual
Program name fr
Programme de subventions à la découverte - individuelles
Group en
DISCOVERY RESEARCH
Group fr
RECHERCHE AXÉE SUR LA DÉCOUVERTE
Committee code
1507
Committee name en
Computer Science
Committee name fr
Sciences informatiques
Area of application code
1200
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Advancement of knowledge
Area of application fr
Avancement des connaissances
Research subject code
2600
Research subject group en
Robotics
Research subject group fr
Robotique
Research subject en
Robotics
Research subject fr
Robotique
Installment
inst:5
Partie
1
Nb partie
6
Application title
Inference and Model Building for Vision-based Estimation of Transmissive Objects
Application summary
This proposal seeks to further the state of the art in the field of computer vision and image processing, with the goal of expanding and reinforcing the use of imaging modalities in our understanding of the world. Images are a rich source of information which are readily captured in many scenarios. The ability to process these images and extract meaning from them is the key goal of computer vision. The long-term objective of this proposal and the PI's research program in general is the theoretical and practical development of models which enable the estimation of properties of the world from images. One such problem is the estimation of detailed 3D structure of transmissive objects. Imaging and reconstruction of such objects arises in a range of domains including: optical imaging of translucent objects like clouds, glass, water or smoke, x-ray imaging of humans and animals for medical purposes, and transmission electron imaging or materials and biological specimens.The objectives of this proposal focus on transmission electron imaging with the aim to build new methods for electron cryomicroscopy (cryo-EM). Specific problems relating to the estimation of the 3D structure of biological molecules such as proteins and viruses from cryo-EM images are considered. Cryo-EM is a rapidly emerging method for experimental structure determination of biological molecules. The function of DNA has sometimes been explained by analogy as the source code of life. Continuing this analogy, proteins and viruses are the compiled programs which take the form of molecular machines that “execute life” at a cellular level. Determining the 3D structures of these machines and understanding how they work is not only of fundamental scientific interest, it is also critical in the understanding of disease and the development of novel drugs and treatments.The research proposed here would advance the state-of-the-art and have significant impacts on cryo-EM and consequently on many aspects of science and medicine both within Canada and around the world. By improving the reliability and resolution of estimation structures, the methods proposed here would form the basis for rapid structure determination methods which could be used to more quickly develop new drugs which would be less likely to have unexpected side-effects. They would also allow scientists to study never before seen mechanisms in the cell as the motion of these molecular machines could be captured directly.