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Enabling Deep Geometric Learning On Cryo Em Maps Using Neural Representation
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Book Synopsis Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation by : Nathan Ranno
Download or read book Enabling Deep Geometric Learning on Cryo-EM Maps Using Neural Representation written by Nathan Ranno and published by . This book was released on 2021 with total page 44 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Deep geometric learning is intriguing for use in structure segmentation, but the native voxel format of cryo-EM maps is unsuitable as input to such methods. We present a novel data format called the neural cryo-EM map that accurately parameterizes cryo-EM maps and provides native, spatially continuous density and gradient data to serve as the basis for a graph-based interpretation of cryo-EM maps. Density values interpolated using the non-linear neural cryo-EM format are more accurate than conventional tri-linear interpolation. Our graph-based interpretations of 115 experimental cryo-EM maps from 1.15 to 4.0 Angstrom resolution provide high coverage of the underlying amino acid residue locations, while accuracy of nodes is correlated with resolution. The nodes of graphs created from atomic resolution maps (higher than 1.6 Angstrom) provide greater than 99% residue coverage as well as 85% full atomic coverage with a mean of 0.19 Angstrom root mean squared deviation (RMSD). Other graphs have a mean 84% residue coverage with less specificity of the nodes due to experimental noise and differences of density context at lower resolutions. Graphs created from atomic resolution maps may serve as input to downstream deep geometric learning applications and may be generalized to transform any 3D grid-based data format into non-linear, continuous, and differentiable format.
Book Synopsis Geometric Deep Learning by : Chu Wang
Download or read book Geometric Deep Learning written by Chu Wang and published by . This book was released on 2020 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "Advances in deep learning techniques have revolutionized computer vision research and have lead to unprecedented success in visual recognition tasks. As a result, many computer vision researchers are now engaged in developing neural architectures and loss functions to handle particular computer vision problems. However, most current neural architectures cannot easily handle 3D input data and this has lead to new interest in representation learning with deep architectures, but on 3D data formats.In an early development of this thesis, we worked on abstracting features from 2.5D point clouds, interpreted as a 2D colour image and depth map pair, thus enabling the use of well studied 2D neural networks. The community had overlooked the potential of deriving higher order representations from the depth map, which could grant invariance to rigid transformations. We proposed a principled method for transforming the 2.5D input data to higher order surface geometric feature maps, including surface normals and curvatures, and applied pretrained CNNs on these new modalities for geometric feature abstraction from the 2.5D input data. However, this approach did not directly allow for the handling of unorganized 3D input. It could only work on 2.5D point clouds where the points could be mapped to pixels in a 2D image. Therefore, we took a step in this direction by working on 3D mesh representation learning. We chose to model a 3D mesh using a graph comprised of rendered 2D views. In order to abstract a global representation of the 3D mesh from the constructed view graph, we proposed a novel recursive cluster-pooling aggregation algorithm. The proposed method demonstrated nontrivial improvements over related work at the time. The empirical results we reported on the ModelNet40 categorization task ranked in second place on the associated leaderboard.Despite their effectiveness, the above methods were not native 3D approaches in that they did not directly abstract features from unorganized 3D data. Thus we moved on to representation learning directly from unorganized point clouds, using spectral graph convolution on local point neighbourhoods. Here we first sampled local point neighbourhoods from the input cloud, and inside each fix sized neighbourhood, a local graph was constructed with each point as a node. Spectral graph convolution was carried out on each local graph, followed by the application of a cluster pooling algorithm to yield a single feature vector representing this neighbourhood. This method improved point set representation learning by incorporating structural features embedded via local graphs, and boosted performance in point set classification and segmentation benchmarks. However, the local graphs remained the same once constructed, and could not be adaptively learned during the training phase.In a complementary direction, research in attention mechanisms has demonstrated that it is beneficial to parametrize the graph structures in GCN-like models, where the adjacency matrix can be learned during training to further minimize the task loss. Despite the demonstrated boost over base models, these adaptive GCN variants rely solely on the task loss to carry out graph structure learning, and as a result, the learned graph structure is usually ad hoc. Motivated by the lack of interpretability in graph structure learning, in the fourth and final contribution of this thesis we propose to explicitly supervise the graphs in GCN-like neural networks, using a novel affinity mass loss. We aim to place emphasis on designated entries in the graph adjacency matrix, which are selected by a user-specified graph supervision target. We demonstrate the effectiveness of the proposed graph supervision method on visual attention networks and regular mini-batch training. In addition to the performance boost in visual recognition tasks, the graph structures learned with the affinity loss demonstrate a much higher degree of interpretability"--
Book Synopsis Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images by : Todor Kirilov Avramov
Download or read book Deep Learning for Validating Resolution and Detecting Secondary Structure Elements of Proteins in 3D Cryo-electron Microscopy Images written by Todor Kirilov Avramov and published by . This book was released on 2019 with total page 130 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Ion Channel Structure and Drug Discovery Accelerated by Cryo-EM by : Shujia Zhu
Download or read book Ion Channel Structure and Drug Discovery Accelerated by Cryo-EM written by Shujia Zhu and published by Frontiers Media SA. This book was released on 2022-11-30 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis The Resolution Revolution: Recent Advances In cryoEM by :
Download or read book The Resolution Revolution: Recent Advances In cryoEM written by and published by Academic Press. This book was released on 2016-08-26 with total page 488 pages. Available in PDF, EPUB and Kindle. Book excerpt: cryoEM, a new volume in the Methods in Enzymology series, continues the legacy of this premier serial with quality chapters authored by leaders in the field. This volume covers research methods and new developments in recording images, the creation, evaluation and validation of 3D maps from the images, model building into maps and refinement of the resulting atomic structures, and applications of essentially single particle methods to helical structures and to sub-tomogram averaging. Continues the legacy of this premier serial with quality chapters authored by leaders in the field Covers research methods that determine the structures of biological molecules, a vital step for understanding their function Contains the technical developments underpinning the advances of cryoEM and captures the exciting insights that have resulted
Download or read book 3D Shape Analysis written by Hamid Laga and published by John Wiley & Sons. This book was released on 2019-01-07 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: An in-depth description of the state-of-the-art of 3D shape analysis techniques and their applications This book discusses the different topics that come under the title of "3D shape analysis". It covers the theoretical foundations and the major solutions that have been presented in the literature. It also establishes links between solutions proposed by different communities that studied 3D shape, such as mathematics and statistics, medical imaging, computer vision, and computer graphics. The first part of 3D Shape Analysis: Fundamentals, Theory, and Applications provides a review of the background concepts such as methods for the acquisition and representation of 3D geometries, and the fundamentals of geometry and topology. It specifically covers stereo matching, structured light, and intrinsic vs. extrinsic properties of shape. Parts 2 and 3 present a range of mathematical and algorithmic tools (which are used for e.g., global descriptors, keypoint detectors, local feature descriptors, and algorithms) that are commonly used for the detection, registration, recognition, classification, and retrieval of 3D objects. Both also place strong emphasis on recent techniques motivated by the spread of commodity devices for 3D acquisition. Part 4 demonstrates the use of these techniques in a selection of 3D shape analysis applications. It covers 3D face recognition, object recognition in 3D scenes, and 3D shape retrieval. It also discusses examples of semantic applications and cross domain 3D retrieval, i.e. how to retrieve 3D models using various types of modalities, e.g. sketches and/or images. The book concludes with a summary of the main ideas and discussions of the future trends. 3D Shape Analysis: Fundamentals, Theory, and Applications is an excellent reference for graduate students, researchers, and professionals in different fields of mathematics, computer science, and engineering. It is also ideal for courses in computer vision and computer graphics, as well as for those seeking 3D industrial/commercial solutions.
Book Synopsis Deep Learning in Biology and Medicine by : Davide Bacciu
Download or read book Deep Learning in Biology and Medicine written by Davide Bacciu and published by World Scientific Publishing Europe Limited. This book was released on 2021 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Biology, medicine and biochemistry have become data-centric fields for which Deep Learning methods are delivering groundbreaking results. Addressing high impact challenges, Deep Learning in Biology and Medicine provides an accessible and organic collection of Deep Learning essays on bioinformatics and medicine. It caters for a wide readership, ranging from machine learning practitioners and data scientists seeking methodological knowledge to address biomedical applications, to life science specialists in search of a gentle reference for advanced data analytics.With contributions from internationally renowned experts, the book covers foundational methodologies in a wide spectrum of life sciences applications, including electronic health record processing, diagnostic imaging, text processing, as well as omics-data processing. This survey of consolidated problems is complemented by a selection of advanced applications, including cheminformatics and biomedical interaction network analysis. A modern and mindful approach to the use of data-driven methodologies in the life sciences also requires careful consideration of the associated societal, ethical, legal and transparency challenges, which are covered in the concluding chapters of this book.
Book Synopsis Deep Learning for the Life Sciences by : Bharath Ramsundar
Download or read book Deep Learning for the Life Sciences written by Bharath Ramsundar and published by O'Reilly Media. This book was released on 2019-04-10 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning has already achieved remarkable results in many fields. Now it’s making waves throughout the sciences broadly and the life sciences in particular. This practical book teaches developers and scientists how to use deep learning for genomics, chemistry, biophysics, microscopy, medical analysis, and other fields. Ideal for practicing developers and scientists ready to apply their skills to scientific applications such as biology, genetics, and drug discovery, this book introduces several deep network primitives. You’ll follow a case study on the problem of designing new therapeutics that ties together physics, chemistry, biology, and medicine—an example that represents one of science’s greatest challenges. Learn the basics of performing machine learning on molecular data Understand why deep learning is a powerful tool for genetics and genomics Apply deep learning to understand biophysical systems Get a brief introduction to machine learning with DeepChem Use deep learning to analyze microscopic images Analyze medical scans using deep learning techniques Learn about variational autoencoders and generative adversarial networks Interpret what your model is doing and how it’s working
Book Synopsis Three-Dimensional Electron Microscopy of Macromolecular Assemblies by : Frank Joachim
Download or read book Three-Dimensional Electron Microscopy of Macromolecular Assemblies written by Frank Joachim and published by Elsevier. This book was released on 1996-01-24 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Three-Dimensional Electron Microscopy of Macromolecular Assemblies is the first systematic introduction to single-particle methods of reconstruction. It covers correlation alignment, classification, 3D reconstruction, restoration, and interpretation of the resulting 3D images in macromolecular assemblies. It will be an indispensable resource for newcomers to the field and for all using or adopting these methods. Key Features* Presents methods that offer an alternative to crystallographic techniques for molecules that cannot be crystallized* Describes methods that have been instrumental in exploring the three-dimensional structure of* the nuclear pore complex* the calcium release channel;* the ribosome* chaperonins
Book Synopsis Machine Learning Meets Quantum Physics by : Kristof T. Schütt
Download or read book Machine Learning Meets Quantum Physics written by Kristof T. Schütt and published by Springer Nature. This book was released on 2020-06-03 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: Designing molecules and materials with desired properties is an important prerequisite for advancing technology in our modern societies. This requires both the ability to calculate accurate microscopic properties, such as energies, forces and electrostatic multipoles of specific configurations, as well as efficient sampling of potential energy surfaces to obtain corresponding macroscopic properties. Tools that can provide this are accurate first-principles calculations rooted in quantum mechanics, and statistical mechanics, respectively. Unfortunately, they come at a high computational cost that prohibits calculations for large systems and long time-scales, thus presenting a severe bottleneck both for searching the vast chemical compound space and the stupendously many dynamical configurations that a molecule can assume. To overcome this challenge, recently there have been increased efforts to accelerate quantum simulations with machine learning (ML). This emerging interdisciplinary community encompasses chemists, material scientists, physicists, mathematicians and computer scientists, joining forces to contribute to the exciting hot topic of progressing machine learning and AI for molecules and materials. The book that has emerged from a series of workshops provides a snapshot of this rapidly developing field. It contains tutorial material explaining the relevant foundations needed in chemistry, physics as well as machine learning to give an easy starting point for interested readers. In addition, a number of research papers defining the current state-of-the-art are included. The book has five parts (Fundamentals, Incorporating Prior Knowledge, Deep Learning of Atomistic Representations, Atomistic Simulations and Discovery and Design), each prefaced by editorial commentary that puts the respective parts into a broader scientific context.
Book Synopsis What Video Games Have to Teach Us About Learning and Literacy. Second Edition by : James Paul Gee
Download or read book What Video Games Have to Teach Us About Learning and Literacy. Second Edition written by James Paul Gee and published by Macmillan. This book was released on 2014-12-02 with total page 233 pages. Available in PDF, EPUB and Kindle. Book excerpt: Cognitive Development in a Digital Age James Paul Gee begins his classic book with "I want to talk about video games–yes, even violent video games–and say some positive things about them." With this simple but explosive statement, one of America's most well-respected educators looks seriously at the good that can come from playing video games. This revised edition expands beyond mere gaming, introducing readers to fresh perspectives based on games like World of Warcraft and Half-Life 2. It delves deeper into cognitive development, discussing how video games can shape our understanding of the world. An undisputed must-read for those interested in the intersection of education, technology, and pop culture, What Video Games Have to Teach Us About Learning and Literacy challenges traditional norms, examines the educational potential of video games, and opens up a discussion on the far-reaching impacts of this ubiquitous aspect of modern life.
Book Synopsis Protein-Nucleic Acid Interactions by : Phoebe A. Rice
Download or read book Protein-Nucleic Acid Interactions written by Phoebe A. Rice and published by Royal Society of Chemistry. This book was released on 2008-05-22 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides both in-depth background and up-to-date information in this area. The chapters are organized by general themes and principles, written by experts who illustrate topics with current findings. Topics covered include: - the role of ions and hydration in protein-nucleic acid interactions - transcription factors and combinatorial specificity - indirect readout of DNA sequence - single-stranded nucleic acid binding proteins - nucleic acid junctions and proteins, - RNA protein recognition - recognition of DNA damage. It will be a key reference for both advanced students and established scientists wishing to broaden their horizons.
Book Synopsis Single-particle Cryo-EM of Biological Macromolecules by : GLAESER
Download or read book Single-particle Cryo-EM of Biological Macromolecules written by GLAESER and published by Biophysical Society. This book was released on 2021-05-19 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: This edited book is written for students, postdocs and established investigators who want to enter the field of single-particle cryo-EM. This is a recently developed method to determine high-resolution structures of biological macromolecules. A major strength is the fact that cryo-EM does not require prior crystallization of protein complexes. It is especially well suited for larger complexes and molecular machines. This book, provides a comprehensive, accessible and authoritative introduction to the field. It covers all necessary background, ranging from the underlying concepts to practical aspects such as specimen preparation, data-collection, data analysis, and the final validation of results. Key features Written for students, postdocs and established investigators who want to enter the field of single-particle cryo-EM Provides a comprehensive, accessible and authoritative introduction to the field of high-resolution structure analysis by single-article cryo-EM Covers all necessary background, ranging from the underlying concepts to practical aspects such as specimen preparation, data-collection, data analysis, and the final validation of results Authors of individual sections of this book have been recruited from among the most authoritative leaders in each topic
Book Synopsis Visualizing Chemistry by : National Research Council
Download or read book Visualizing Chemistry written by National Research Council and published by National Academies Press. This book was released on 2006-06-01 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: Scientists and engineers have long relied on the power of imaging techniques to help see objects invisible to the naked eye, and thus, to advance scientific knowledge. These experts are constantly pushing the limits of technology in pursuit of chemical imagingâ€"the ability to visualize molecular structures and chemical composition in time and space as actual events unfoldâ€"from the smallest dimension of a biological system to the widest expanse of a distant galaxy. Chemical imaging has a variety of applications for almost every facet of our daily lives, ranging from medical diagnosis and treatment to the study and design of material properties in new products. In addition to highlighting advances in chemical imaging that could have the greatest impact on critical problems in science and technology, Visualizing Chemistry reviews the current state of chemical imaging technology, identifies promising future developments and their applications, and suggests a research and educational agenda to enable breakthrough improvements.
Book Synopsis Cellular Electron Microscopy by : J. Richard McIntosh
Download or read book Cellular Electron Microscopy written by J. Richard McIntosh and published by Elsevier. This book was released on 2011-09-02 with total page 878 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in the imaging technique electron microscopy (EM) have improved the method, making it more reliable and rewarding, particularly in its description of three-dimensional detail. Cellular Electron Microscopy will help biologists from many disciplines understand modern EM and the value it might bring to their own work. The book’s five sections deal with all major issues in EM of cells: specimen preparation, imaging in 3-D, imaging and understanding frozen-hydrated samples, labeling macromolecules, and analyzing EM data. Each chapter was written by scientists who are among the best in their field, and some chapters provide multiple points of view on the issues they discuss. Each section of the book is preceded by an introduction, which should help newcomers understand the subject. The book shows why many biologists believe that modern EM will forge the link between light microscopy of live cells and atomic resolution studies of isolated macromolecules, helping us toward the goal of an atomic resolution understanding of living systems. Updates the numerous technological innovations that have improved the capabilities of electron microscopy Provides timely coverage of the subject given the significant rise in the number of biologists using light microscopy to answer their questions and the natural limitations of this kind of imaging Chapters include a balance of "how to", "so what" and "where next", providing the reader with both practical information, which is necessary to use these methods, and a sense of where the field is going
Book Synopsis Computational Neuroanatomy by : Giorgio A. Ascoli
Download or read book Computational Neuroanatomy written by Giorgio A. Ascoli and published by Springer Science & Business Media. This book was released on 2002-07-01 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: In Computational Neuroanatomy: Principles and Methods, the path-breaking investigators who founded the field review the principles and key techniques available to begin the creation of anatomically accurate and complete models of the brain. Combining the vast, data-rich field of anatomy with the computational power of novel hardware, software, and computer graphics, these pioneering investigators lead the reader from the subcellular details of dendritic branching and firing to system-level assemblies and models.
Download or read book cryoEM written by Tamir Gonen and published by Humana. This book was released on 2021-12-28 with total page 350 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume details the most up-to-date cryo-EM techniques from leading researchers. Chapters are organized into four parts with emphasis on electron cryotomography, single particle analysis, and the crystal based cryo-EM methods of 2D electron crystallography, and MicroED for the study of 3D crystals. Written in the highly successful Methods in Molecular Biology series format, chapters include introductions to their respective topics, application details for both the expert and non-expert reader, and tips on troubleshooting and avoiding known pitfalls. Authoritative and cutting-edge, CryoEM: Methods and Protocols aims to serve as an excellent resource on cryo-EM and can serve as the foundation for new researchers to this growing field in structural biology.
