Tracing and segmentation of molecular patterns in 3-dimensional
  cryo-et/em density maps through algorithmic image processing and deep
  learning-based techniques
Salim Sazzed
Understanding the structures of biological macromolecules is highly important
as they are closely associated with cellular functionalities. Comprehending the
precise organization actin filaments is crucial because they form the dynamic
cytoskeleton, which offers structural support to cells and connects the cell's
interior with its surroundings. However, determining the precise organization
of actin filaments is challenging due to the poor quality of cryo-electron
tomography (cryo-ET) images, which suffer from low signal-to-noise (SNR) ratios
and the presence of missing wedge, as well as diverse shape characteristics of
actin filaments. To address these formidable challenges, the primary component
of this dissertation focuses on developing sophisticated computational
techniques for tracing actin filaments. In particular, three novel
methodologies have been developed: i) BundleTrac, for tracing bundle-like actin
filaments found in Stereocilium, ii) Spaghetti Tracer, for tracing filaments
that move individually with loosely cohesive movements, and iii) Struwwel
Tracer, for tracing randomly orientated actin filaments in the actin network.
The second component of the dissertation introduces a convolutional neural
network (CNN) based segmentation model to determine the location of protein
secondary structures, such as helices and beta-sheets, in medium-resolution
(5-10 Angstrom) 3-dimensional cryo-electron microscopy (cryo-EM) images. This
methodology later evolved into a tool named DeepSSETracer. The final component
of the dissertation presents a novel algorithm, cylindrical fit measure, to
estimate image structure match at helix regions in medium-resolution cryo-EM
images. Overall, my dissertation has made significant contributions to
addressing critical research challenges in structural biology by introducing
various computational methods and tools.