Small angle X-ray scattering (SAXS), an increasingly popular method for structural analysis of biological macromolecules in solution, is often hampered by inherent sample polydispersity. We developed an all-in-one system combining in-line sample component separation with parallel biophysical and SAXS characterization of the separated components. The system coupled to an automated data analysis pipeline provides a novel tool to study difficult samples at the P12 synchrotron beamline (PETRA-3, EMBL/DESY, Hamburg).
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5377070 | PMC |
http://dx.doi.org/10.1038/srep10734 | DOI Listing |
Bioinform Adv
November 2024
Laboratory of Molecular Science and Engineering, Åbo Akademi University, Henrikinkatu 2, Turku 20500, Finland.
Motivation: NMR-based metabolomics is a field driven by technological advancements, necessitating the use of advanced preprocessing tools. Despite this need, there is a remarkable scarcity of comprehensive and user-friendly preprocessing tools in Python. To bridge this gap, we have developed Protomix-a Python package designed for metabolomics research.
View Article and Find Full Text PDFApplications in engineering biology increasingly share the need to run operations on very large numbers of biological samples. This is a direct consequence of the application of good engineering practices, the limited predictive power of current computational models and the desire to investigate very large design spaces in order to solve the hard, important problems the discipline promises to solve. Automation has been proposed as a key component for running large numbers of operations on biological samples.
View Article and Find Full Text PDFJ Mol Biol
December 2024
Laboratory of Viral Diseases, National Institute of Allergy and Infectious Diseases, Bethesda, MD, USA. Electronic address:
The Papilloma Virus Episteme (PaVE) https://pave.niaid.nih.
View Article and Find Full Text PDFSci Rep
December 2024
The National Institute of Horticultural Research, ul. Pomologiczna 18, 96-100, Skierniewice, Poland.
The aim of this research is to create an automated system for identifying soil microorganisms at the genera level based on raw microscopic images of monocultural colonies grown in laboratory environment. The examined genera are: Fusarium, Trichoderma, Verticillium, Purpureolicillium and Phytophthora. The proposed pipeline deals with unprocessed microscopic images, avoiding additional sample marking or coloration.
View Article and Find Full Text PDFSci Rep
December 2024
GIN, IMN-UMR5293, CEA, CNRS, Université de Bordeaux, Bordeaux, France.
Cerebral microbleeds (CMB) represent a feature of cerebral small vessel disease (cSVD), a prominent vascular contributor to age-related cognitive decline, dementia, and stroke. They are visible as spherical hypointense signals on T2*- or susceptibility-weighted magnetic resonance imaging (MRI) sequences. An increasing number of automated CMB detection methods being proposed are based on supervised deep learning (DL).
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!