2019 Research in the Capitol

Presentation Type

Open Access Poster Presentation

Keywords

Fluorescence microscopy; Biomolecules;

Abstract

Single-Molecule studies use advanced microscopy techniques to view biomolecules, such as proteins and DNA, individually. On a slide, fluorescently-labeled molecules are immobilized and imaged using lasers, and the patterns of fluorescence can give important information about the interactions of multiple molecules. To extract this information, advanced, customizable data analysis tools must be created. The first goal is to create a method to robustly normalize (correct for brightness) single-channel fluorescence data. The second goal is to extend pattern recognition of binding order to multi-state and multi-channel binding patterns. The KERA 3.0 suite links creative pattern-recognition and normalization techniques with the abilities of exiting idealization software to extract this information from previously intractable data. This allows researchers to study protein complexes, their inhibitors, and their mechanisms, more holistically and more efficiently.

Start Date

1-4-2019 11:00 AM

End Date

1-4-2019 2:30 AM

Event Host

University Honors Programs, Iowa Regent Universities

Faculty Advisor

Seyed Tabei

Department

Department of Physics

File Format

application/pdf

Available for download on Thursday, April 02, 2020

Share

COinS
 
Apr 1st, 11:00 AM Apr 1st, 2:30 AM

Novel Data Analysis Methods in Multi-Channel and Multi-State Binding Experiments

Single-Molecule studies use advanced microscopy techniques to view biomolecules, such as proteins and DNA, individually. On a slide, fluorescently-labeled molecules are immobilized and imaged using lasers, and the patterns of fluorescence can give important information about the interactions of multiple molecules. To extract this information, advanced, customizable data analysis tools must be created. The first goal is to create a method to robustly normalize (correct for brightness) single-channel fluorescence data. The second goal is to extend pattern recognition of binding order to multi-state and multi-channel binding patterns. The KERA 3.0 suite links creative pattern-recognition and normalization techniques with the abilities of exiting idealization software to extract this information from previously intractable data. This allows researchers to study protein complexes, their inhibitors, and their mechanisms, more holistically and more efficiently.