Physical Sciences and Mathematics Commons^™

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

Computer Science Theses & Dissertations

Understanding the structures of biological macromolecules is highly important as they are closely associated with cellular functionalities. Comprehending the precise organization of 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 …

Highly Accurate Fragment Library For Protein Fold Recognition, Wessam Elhefnawy

Computer Science Theses & Dissertations

Proteins play a crucial role in living organisms as they perform many vital tasks in every living cell. Knowledge of protein folding has a deep impact on understanding the heterogeneity and molecular functions of proteins. Such information leads to crucial advances in drug design and disease understanding. Fold recognition is a key step in the protein structure discovery process, especially when traditional computational methods fail to yield convincing structural homologies. In this work, we present a new protein fold recognition approach using machine learning and data mining methodologies.

First, we identify a protein structural fragment library (Frag-K) composed of a …

Deep Learning For Segmentation Of 3d Cryo-Em Images, Devin Reid Haslam

Computer Science Theses & Dissertations

Cryo-electron microscopy (cryo-EM) is an emerging biophysical technique for structural determination of protein complexes. However, accurate detection of secondary structures is still challenging when cryo-EM density maps are at medium resolutions (5-10 Å). Most existing methods are image processing methods that do not fully utilize available images in the cryo-EM database. In this paper, we present a deep learning approach to segment secondary structure elements as helices and β-sheets from medium- resolution density maps. The proposed 3D convolutional neural network is shown to detect secondary structure locations with an F1 score between 0.79 and 0.88 for six simulated test cases. …

New Methods To Improve Protein Structure Modeling, Maha Abdelrasoul

Computer Science Theses & Dissertations

Proteins are considered the central compound necessary for life, as they play a crucial role in governing several life processes by performing the most essential biological and chemical functions in every living cell. Understanding protein structures and functions will lead to a significant advance in life science and biology. Such knowledge is vital for various fields such as drug development and synthetic biofuels production.

Most proteins have definite shapes that they fold into, which are the most stable state they can adopt. Due to the fact that the protein structure information provides important insight into its functions, many research efforts …

A Computational Framework For Learning From Complex Data: Formulations, Algorithms, And Applications, Wenlu Zhang

Computer Science Theses & Dissertations

Many real-world processes are dynamically changing over time. As a consequence, the observed complex data generated by these processes also evolve smoothly. For example, in computational biology, the expression data matrices are evolving, since gene expression controls are deployed sequentially during development in many biological processes. Investigations into the spatial and temporal gene expression dynamics are essential for understanding the regulatory biology governing development. In this dissertation, I mainly focus on two types of complex data: genome-wide spatial gene expression patterns in the model organism fruit fly and Allen Brain Atlas mouse brain data. I provide a framework to explore …

Machine Learning Methods For Brain Image Analysis, Ahmed Fakhry

Computer Science Theses & Dissertations

Understanding how the brain functions and quantifying compound interactions between complex synaptic networks inside the brain remain some of the most challenging problems in neuroscience. Lack or abundance of data, shortage of manpower along with heterogeneity of data following from various species all served as an added complexity to the already perplexing problem. The ability to process vast amount of brain data need to be performed automatically, yet with an accuracy close to manual human-level performance. These automated methods essentially need to generalize well to be able to accommodate data from different species. Also, novel approaches and techniques are becoming …

Efficient Algorithms For Prokaryotic Whole Genome Assembly And Finishing, Abhishek Biswas

Computer Science Theses & Dissertations

De-novo genome assembly from DNA fragments is primarily based on sequence overlap information. In addition, mate-pair reads or paired-end reads provide linking information for joining gaps and bridging repeat regions. Genome assemblers in general assemble long contiguous sequences (contigs) using both overlapping reads and linked reads until the assembly runs into an ambiguous repeat region. These contigs are further bridged into scaffolds using linked read information. However, errors can be made in both phases of assembly due to high error threshold of overlap acceptance and linking based on too few mate reads. Identical as well as similar repeat regions can …

Computational Development For Secondary Structure Detection From Three-Dimensional Images Of Cryo-Electron Microscopy, Dong Si

Computer Science Theses & Dissertations

Electron cryo-microscopy (cryo-EM) as a cutting edge technology has carved a niche for itself in the study of large-scale protein complex. Although the protein backbone of complexes cannot be derived directly from the medium resolution (5-10 Å) of amino acids from three-dimensional (3D) density images, secondary structure elements (SSEs) such as alpha-helices and beta-sheets can still be detected. The accuracy of SSE detection from the volumetric protein density images is critical for ab initio backbone structure derivation in cryo-EM. So far it is challenging to detect the SSEs automatically and accurately from the density images at these resolutions. This dissertation …

Improving Structural Features Prediction In Protein Structure Modeling, Ashraf Yaseen

Computer Science Theses & Dissertations

Proteins play a vital role in the biological activities of all living species. In nature, a protein folds into a specific and energetically favorable three-dimensional structure which is critical to its biological function. Hence, there has been a great effort by researchers in both experimentally determining and computationally predicting the structures of proteins.

The current experimental methods of protein structure determination are complicated, time-consuming, and expensive. On the other hand, the sequencing of proteins is fast, simple, and relatively less expensive. Thus, the gap between the number of known sequences and the determined structures is growing, and is expected to …

Modeling Stem Cell Population Dynamics, Samiur Arif

Computer Science Theses & Dissertations

Because of the stochastic nature of biological systems, mathematical and computational modeling approaches have become more acceptable to experimentalists and clinicians in recent years as contributing to new understandings of complicated cell mechanisms and tissue physiology. Indeed, even single cell or small tissue samples are complex dynamic systems that adapt to environmental challenges in space and time which is poorly understood. Mathematical models and computer simulations can explain and uncover unknown aspects of cell behavior and tissue functions. Models based on key biological mechanisms can give interesting insights and formulate predictions that cannot be derived from physical experiments or statistical …

De Novo Protein Structure Modeling From Cryoem Data Through A Dynamic Programming Algorithm In The Secondary Structure Topology Graph, Kamal H. Al Nasr

Computer Science Theses & Dissertations

Proteins are the molecules carry out the vital functions and make more than the half of dry weight in every cell. Protein in nature folds into a unique and energetically favorable 3-Dimensional (3-D) structure which is critical and unique to its biological function. In contrast to other methods for protein structure determination, Electron Cryorricroscopy (CryoEM) is able to produce volumetric maps of proteins that are poorly soluble, large and hard to crystallize. Furthermore, it studies the proteins in their native environment. Unfortunately, the volumetric maps generated by current advances in CryoEM technique produces protein maps at medium resolution about (~5 …

Biological Networks: Modeling And Structural Analysis, Emad Y. Ramadan

Computer Science Theses & Dissertations

Biological networks are receiving increased attention due to their importance in understanding life at the cellular level. There exist many different kinds of biological networks, and different models have been proposed for them. In this dissertation we focus on suitable network models for representing experimental data on protein interaction networks and protein complex networks (protein complexes are groups of proteins that associate to accomplish some function in the cell), and to design algorithms for exploring such networks. Our goal is to enable biologists to identify the general principles that govern the organization of protein-protein interaction networks and protein complex networks. …