Hybrid Electron Microscopy Normal Mode Analysis graphical interface and protocol.

J Struct Biol

IMPMC, Sorbonne Universités - CNRS UMR 7590, UPMC Univ Paris 6, MNHN, IRD UMR 206, 75005 Paris, France. Electronic address:

Published: November 2014

This article presents an integral graphical interface to the Hybrid Electron Microscopy Normal Mode Analysis (HEMNMA) approach that was developed for capturing continuous motions of large macromolecular complexes from single-particle EM images. HEMNMA was shown to be a good approach to analyze multiple conformations of a macromolecular complex but it could not be widely used in the EM field due to a lack of an integral interface. In particular, its use required switching among different software sources as well as selecting modes for image analysis was difficult without the graphical interface. The graphical interface was thus developed to simplify the practical use of HEMNMA. It is implemented in the open-source software package Xmipp 3.1 (http://xmipp.cnb.csic.es) and only a small part of it relies on MATLAB that is accessible through the main interface. Such integration provides the user with an easy way to perform the analysis of macromolecular dynamics and forms a direct connection to the single-particle reconstruction process. A step-by-step HEMNMA protocol with the graphical interface is given in full details in Supplementary material. The graphical interface will be useful to experimentalists who are interested in studies of continuous conformational changes of macromolecular complexes beyond the modeling of continuous heterogeneity in single particle reconstruction.

Download full-text PDF

Source
http://dx.doi.org/10.1016/j.jsb.2014.09.005DOI Listing

Publication Analysis

Top Keywords

graphical interface
24
hybrid electron
8
electron microscopy
8
microscopy normal
8
normal mode
8
mode analysis
8
interface
8
macromolecular complexes
8
graphical
6
analysis
4

Similar Publications

Objective: The application of artificial intelligence (AI)-based clinical decision support systems (CDSS) in the healthcare domain is still limited. End-users' difficulty understanding how the outputs of opaque black AI models are generated contributes to this. It is still unknown which explanations are best presented to end users and how to design the interfaces they are presented in (explanation user interface, XUI).

View Article and Find Full Text PDF

Microbiome studies aim to answer the following questions: which organisms are in the sample and what is their impact on the patient or the environment? To answer these questions, investigators have to perform comparative analyses on their classified sequences based on the collected metadata, such as treatment, condition of the patient, or the environment. The integrity of sequences, classifications, and metadata is paramount for the success of such studies. Still, the area of data management for the preliminary study results appears to be neglected.

View Article and Find Full Text PDF

MixDeR: A SNP mixture deconvolution workflow for forensic genetic genealogy.

Forensic Sci Int Genet

January 2025

National Bioforensic Analysis Center, National Biodefense Analysis and Countermeasures Center, Operated by Battelle National Biodefense Institute for the US. Department of Homeland Security Science and Technology Directorate, 8300 Research Plaza, Fort Detrick, MD 21702, USA. Electronic address:

The generation of forensic DNA profiles consisting of single nucleotide polymorphisms (SNPs) is now being facilitated by wider adoption of next-generation sequencing (NGS) methods in casework laboratories. At the same time, and in part because of this advance, there is an intense focus on the generation of SNP profiles from evidentiary specimens for so-called forensic or investigative genetic genealogy (FGG or IGG) applications. However, FGG methods are constrained by the algorithms for genealogical database searches, which were designed for use with single-source profiles, and the fact that many forensic samples are mixtures.

View Article and Find Full Text PDF

HemaScope: A Tool for Analyzing Single-cell and Spatial Transcriptomics Data of Hematopoietic Cells.

Genomics Proteomics Bioinformatics

January 2025

Shanghai Institute of Hematology, State Key Laboratory of Medical Genomics, National Research Center for Translational Medicine at Shanghai, Research Unit of Hematologic Malignancies Genomics and Translational Research of Chinese Academy of Medical Sciences, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China.

Single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics (ST) techniques hold great value in evaluating the heterogeneity and spatial characteristics of hematopoietic cells within tissues. These two techniques are highly complementary, with scRNA-seq offering single-cell resolution and ST retaining spatial information. However, there is an urgent demand for well-organized and user-friendly toolkits capable of handling single-cell and spatial information.

View Article and Find Full Text PDF

Purpose: Paraneoplastic syndromes (PNS) are a group of rare disorders triggered by an immune response to malignancy, characterized by diverse neurological, muscular, and systemic symptoms. This study aims to leverage machine learning to develop a predictive model for cancer diagnosis in patients with paraneoplastic autoantibodies.

Methods: Demographic data included age and sex, and presenting symptoms were recorded.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!