Dong Si

Dong Si
Old Dominion University | ODU · Department of Computer Science

PhD

About

57
Publications
9,266
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961
Citations
Introduction
My research interests include 3D image processing, feature detection, pattern recognition, modeling & simulation, machine learning and bioinformatics. I am currently working on the problem of protein structure detection from 3D cryo-EM images.
Additional affiliations
September 2010 - present
Old Dominion University
Position
  • Research Assistant

Publications

Publications (57)
Conference Paper
Secondary structure element (SSE) identification from volumetric protein density maps is critical for de-novo backbone structure derivation in electron cryo-microscopy (cryoEM). Although multiple methods have been developed to detect SSE from the density maps, accurate detection either need use intervention or carefully adjusting various parameters...
Conference Paper
Although many electron density maps have been produced into the medium resolutions, it is still challenging to derive the atomic structure from such volumetric data. Current methods primarily rely on the availability of an existing atomic structure for fitting or a homologous template structure for modeling. In the process of developing a template-...
Article
The accuracy of the secondary structure element (SSE) identification from volumetric protein density maps is critical for de-novo backbone structure derivation in electron cryo-microscopy (cryoEM). It is still challenging to detect the SSE automatically and accurately from the density maps at medium resolutions (∼5-10 Å). We present a machine learn...
Preprint
Full-text available
Motivation: With the advancement of deep learning, researchers have increasingly proposed computational methods based on deep learning techniques to predict protein function. However, many of these methods treat protein function prediction as a multi-label classification problem, often overlooking the long-tail distribution of functional labels (i....
Article
The goal of protein structure refinement is to enhance the precision of predicted protein models, particularly at the residue level of the local structure. Existing refinement approaches primarily rely on physics, whereas molecular simulation methods are resource-intensive and time-consuming. In this study, we employ deep learning methods to extrac...
Article
Full-text available
The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein–nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9–2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase wit...
Article
Full-text available
Understanding the protein structures is invaluable in various biomedical applications, such as vaccine development. Protein structure model building from experimental electron density maps is a time-consuming and labor-intensive task. To address the challenge, machine learning approaches have been proposed to automate this process. Currently, the m...
Preprint
Full-text available
The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein/nucleic-acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: E. coli beta-galactosidase with inhibit...
Preprint
Full-text available
Identification of protein-ligand binding sites is one of the most challenging tasks in drug discovery and design. Recent advances in machine learning community, particularly deep learning, inspired considerable research into deep learning-based methods for protein ligand binding site prediction (PLBP) and have achieved promising results. However on...
Article
Motivation In recent years, the end-to-end deep learning method for single-chain protein structure prediction has achieved high accuracy. For example, the state-of-the-art method AlphaFold, developed by Google, has largely increased the accuracy of protein structure predictions to near experimental accuracy in some of the cases. At the same time, t...
Preprint
Full-text available
Understanding the structures of proteins has numerous applications, such as vaccine development. It is a slow and labor-intensive task to manually build protein structures from experimental electron density maps, therefore, machine learning approaches have been proposed to automate this process. However, most of the experimental maps are not atomic...
Preprint
Full-text available
Motivation The goal of protein structure refinement is to enhance the precision of predicted protein models, particularly at the residue level of the local structure. Existing refinement approaches primarily rely on physics, whereas molecular simulation methods are resource-intensive and time-consuming. In this study, we employ deep learning method...
Article
Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model buildin...
Article
The study of macromolecular structures has expanded our understanding of the amazing cell machinery and such knowledge has changed how the pharmaceutical industry develops new vaccines in recent years. Traditionally, x-ray crystallography has been the main method for structure determination, however, cryogenic electron microscopy (cryo-EM) has incr...
Preprint
Full-text available
Cryo-electron microscopy (cryo-EM) allows a macromolecular structure such as protein-DNA/RNA complexes to be reconstructed in a three-dimensional coulomb potential map. The structural information of these macromolecular complexes forms the foundation for understanding the molecular mechanism including many human diseases. However, the model buildin...
Article
Full-text available
Background Advances in imagery at atomic and near-atomic resolution, such as cryogenic electron microscopy (cryo-EM), have led to an influx of high resolution images of proteins and other macromolecular structures to data banks worldwide. Producing a protein structure from the discrete voxel grid data of cryo-EM maps involves interpolation into the...
Article
Full-text available
The N-degron pathway targets proteins that bear a destabilizing residue at the N terminus for proteasome-dependent degradation1. In yeast, Ubr1—a single-subunit E3 ligase—is responsible for the Arg/N-degron pathway2. How Ubr1 mediates the initiation of ubiquitination and the elongation of the ubiquitin chain in a linkage-specific manner through a s...
Article
Motivation: The Estimation of Model Accuracy problem is a cornerstone problem in the field of Bioinformatics. As of CASP14, there are 79 global QA methods, and a minority of 39 residue-level QA methods with very few of them working on protein complexes. Here, we introduce ZoomQA, a novel, single-model method for assessing the accuracy of a tertiar...
Article
With new developments in biomedical technology, it is now a viable therapeutic treatment to alter genes with techniques like CRISPR. At the same time, it is increasingly cheaper to do whole genome sequencing, resulting in rapid advancement in gene therapy and editing in precision medicine. Thus, understanding the current industry and academic appli...
Article
Cryo‐electron microscopy (cryo‐EM) has become a major experimental technique to determine the structures of large protein complexes and molecular assemblies, as evidenced by the 2017 Nobel Prize. Although cryo‐EM has been drastically improved to generate high‐resolution three‐dimensional maps that contain detailed structural information about macro...
Preprint
Full-text available
Advances in imagery at atomic and near-atomic resolution, such as cryogenic electron microscopy (cryo-EM), have led to an influx of high resolution images of proteins and other macromolecular structures to data banks worldwide. Producing a protein structure from the discrete voxel grid data of cryo-EM maps involves interpolation into the continuous...
Preprint
Full-text available
Cryo-electron microscopy (cryo-EM) has become a major experimental technology to determine the structures of large protein complexes and molecular assemblies, as evidenced by the 2017 Nobel Prize. Although cryo-EM has been drastically improved to generate high-resolution three-dimensional (3D) maps that contain detailed structural information about...
Article
Full-text available
This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of cur...
Preprint
Full-text available
Motivation It has been a challenge for biologists to determine 3D shapes of proteins from a linear chain of amino acids and understand how proteins carry out life’s tasks. Experimental techniques, such as X-ray crystallography or Nuclear Magnetic Resonance, are time-consuming. This highlights the importance of computational methods for protein stru...
Article
Full-text available
Significance Electron cryomicroscopy (cryo-EM), a 2017 Nobel prize-awarded technology, provides direct 3D maps of macromolecules and explains the shape and interactions of protein complexes such as SARS-CoV-2 viral proteins and human cell receptors. This understanding can be combined with detailed structural information gathered using other technol...
Preprint
Full-text available
Information about the macromolecular structure of viral protein complexes such as SARS-CoV-2, and the related cellular and molecular mechanisms can assist the search for vaccines and drug development processes. To obtain such structural information, we present DeepTracer, a fully automatic deep learning-based method for de novo multi-chain protein...
Preprint
Full-text available
This paper describes outcomes of the 2019 Cryo-EM Map-based Model Metrics Challenge sponsored by EMDataResource (www.emdataresource.org). The goals of this challenge were (1) to assess the quality of models that can be produced using current modeling software, (2) to check the reproducibility of modeling results from different software developers a...
Article
Full-text available
Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on all but the most pristine density maps (<2.5 Å resolution). Here we introduce a deep learning model t...
Preprint
Full-text available
Motivation Accurately determining the atomic structure of proteins represents a fundamental problem in the field of structural bioinformatics. A solution would be significant as protein structure information could be utilized in the medical field, e.g. in the development of vaccines for new viruses. This paper focuses on predicting the protein stru...
Article
Correctly predicting the complex three-dimensional structure of a protein from its sequence would allow for a superior understanding of the function of specific proteins with many applications. We propose a novel method aimed to tackle a crucial step in the protein prediction problem, assessing the quality of generated predictions. Unlike tradition...
Conference Paper
Recent advances in cryo-EM have made it possible to create protein density maps with a near-atomic resolution. This has contributed to its wide popularity, resulting in a rapidly growing number of available cryo-EM density maps. In order to computationally process them, an electron density threshold level is required which defines a lower bound for...
Preprint
Full-text available
Recent advances in cryo-EM have made it possible to create protein density maps with a near-atomic resolution. This has contributed to its wide popularity, resulting in a rapidly growing number of available cryo-EM density maps. In order to computationally process them, an electron density threshold level is required which defines a lower bound for...
Article
Full-text available
Quality Assessment (QA) plays an important role in protein structure prediction. Traditional multimodel QA method usually suffer from searching databases or comparing with other models for making predictions, which usually fail when the poor quality models dominate the model pool. We propose a novel protein single-model QA method which is built on...
Article
Full-text available
Cryo-electron microscopy (cryo-EM) is becoming the imaging method of choice for determining protein structures. Many atomic structures have been resolved based on an exponentially growing number of published three-dimensional (3D) high resolution cryo-EM density maps. However, the resolution value claimed for the reconstructed 3D density map has be...
Preprint
Full-text available
Cryo-electron microscopy (cryo-EM) has become a leading technology for determining protein structures. Recent advances in this field have allowed for atomic resolution. However, predicting the backbone trace of a protein has remained a challenge on all but the most pristine density maps (< 2.5Å resolution). Here we introduce a deep learning model t...
Preprint
Full-text available
AI recently shows great promise in the field of bioinformatics, such as protein structure prediction. The Critical Assessment of protein Structure Prediction (CASP) is a nationwide experiment that takes place biannually, which centered around analyzing the best current systems for predicting protein tertiary structures. In this paper, we research o...
Chapter
Cryo-electron microscopy is a technique that is capable of producing high quality three-dimensional density maps of proteins. The identification of secondary structures from within these proteins is important to help understand the protein’s overall structure and function. One of the more commonly found secondary structures is the \(\beta \) barrel...
Chapter
Every business deals with employees who voluntarily resign, retire, or are let go. In other words, they have employee turnover. Employee turnover, also known as attrition can be detrimental if highly valued employees decide to leave at an unexpected time. This paper aims to find the employee(s) that are most at risk of attrition by first identifyin...
Article
Cryo-electron microscopy (cryo-EM) is a technique that produces three-dimensional density maps of large protein complexes. This allows for the study of the structure of these proteins. Identifying the secondary structures within proteins is vital to understanding the overall structure and function of the protein. The [Formula: see text]-barrel is o...
Conference Paper
Cryo-electron microscopy (Cryo-EM) is a technique that produces three-dimensional density maps of large protein complexes and enables the study of the interactions and structures of those molecules. Identifying the secondary structures (α-helices and β-sheets) located in proteins using density maps is vital in identifying and matching the backbone...
Article
Full-text available
Cryo-electron microscopy (cryo-EM) has produced density maps of various resolutions. Although α -helices can be detected from density maps at 5–8 Å resolutions, β -strands are challenging to detect at such density maps due to close-spacing of β -strands. The variety of shapes of β -sheets adds the complexity of β -strands detection from density map...
Article
Major secondary structure elements such as α helices and β sheets can be computationally detected from cryoelectron microscopy (cryo-EM) density maps with medium resolutions of 5–10 Å. However, a critical piece of information for modeling atomic structures is missing, because there are no tools to detect β strands from cryo-EM maps at medium resolu...
Article
A β-sheet is composed of multiple β-strands that are stabilized by inter-strand hydrogen bonds. It has been discovered that a β-sheet is right-handed twisted. We have developed a geometrical method to investigate the relationship between the twist of a β-sheet and the orientations of β-strand traces. The results from forty-one β-sheets suggest that...
Conference Paper
Electron cryo-microscopy (Cryo-EM) technique produces 3-dimensional (3D) density images of proteins. When resolution of the images is not high enough to resolve the molecular details, it is challenging for image processing methods to enhance the molecular features. β-barrel is a particular structure feature that is formed by multiple β-strands in a...
Article
Full-text available
De novo protein modeling approaches utilize 3-dimensional (3D) images derived from electron cryomicroscopy (CryoEM) experiments. The skeleton connecting two secondary structures such as α-helices represent the loop in the 3D image. The accuracy of the skeleton and of the detected secondary structures are critical in De novo modeling. It is importan...
Article
Cryo-electron Microscopy (cryoEM) is an advanced imaging technique that produces volume maps at different resolutions. This technique is capable of visualizing large molecular complexes such as viruses and ribosomes. At the medium resolutions, such as 5 to 10Å, the location and orientation of the secondary structure elements (SSEs) can be computati...
Article
Cryo-electron Microscopy (cryoEM) is an important biophysical technique that produces 3-dimensional (3D) images at different resolutions. De novo modeling is becoming a promising approach to derive the atomic structure of proteins from the cryoEM 3D images at medium resolutions. Distance measurement along a thin skeleton in the 3D image is an impor...
Article
Full-text available
The determination of the secondary structure topology is a critical step in deriving the atomic structure from the protein density map obtained from electron cryo-microscopy technique. This step often relies on the matching of two sources of information. One source comes from the secondary structures detected from the protein density map at the med...

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