The increased complexity of HIV-1 genetic heterogeneity raises the issue for reliable classification and analysis of these sequences. Until now, bootscanning analysis has been the main method used for the analysis of potential HIV-1 intersubtype recombinants. We show evidence that in some cases of complex recombinants, where three or more segments with discordant phylogenetic signal may exist in protease (PR) and partial reverse transcriptase (RT) region, Bayesian scanning provides a clearer picture than bootscanning plots about the boundaries of potential recombination. Thus, a recently developed Bayesian scanning tool can facilitate the analysis and classification of HIV-1 mosaic sequences.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1016/j.meegid.2004.07.006 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Enhancing land feature classification with the BTR Extractor: A novel software package for high-accuracy analysis of aerial laser scan data.
MethodsX
June 2025
Department of Remote Sensing and GIS, Science and Research Branch, Islamic Azad University, Tehran, Iran.
The semi-automatic and automatic extraction of land features such as buildings, trees, and roads using aerial laser scan data is crucial in land use change studies and urban management. This research introduces the "BTR" extractor, a novel software package designed to enhance classification accuracy of phenomena identified in the super points obtained from aerial laser scanners. Our method focuses on:-Comparing classification methods using airborne laser scanning data.
View Article and Find Full Text PDFAssociation of Blood Pressure and Retinal Nerve Fiber Layer Rates of Thinning in Patients with Moderate to Advanced Glaucoma.
Ophthalmol Glaucoma
January 2025
Glaucoma Division, Stein Eye Institute, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, California. Electronic address:
Purpose: Investigate the influence of baseline blood pressure (BP) on retinal nerve fiber layer (RNFL) rates of change (RoC) in glaucoma patients with central damage or moderate to severe disease.
Design: Prospective cohort study.
Participants: 110 eyes with ≥4 RNFL optical coherence tomography scans and ≥2 years of follow-up.
Explainable artificial intelligence with UNet based segmentation and Bayesian machine learning for classification of brain tumors using MRI images.
Sci Rep
January 2025
Department of Electronics, Information and Communication Engineering, Kangwon National University, Samcheok, Republic of Korea.
Detecting brain tumours (BT) early improves treatment possibilities and increases patient survival rates. Magnetic resonance imaging (MRI) scanning offers more comprehensive information, such as better contrast and clarity, than any alternative scanning process. Manually separating BTs from several MRI images gathered in medical practice for cancer analysis is challenging and time-consuming.
View Article and Find Full Text PDFThe feasibility of the adult age estimation 3D-CBCT method on ancient human remains.
J Forensic Odontostomatol
December 2024
Laboratory of Personal Identification and Forensic Morphology, Department of Health Sciences, University of Florence, Florence, Italy.
The age estimation of skeletal remains still represents a central issue not only for the reconstruction of the so-called "biological profile," but mostly for the palaeodemographic investigation. This research aims at verifying the feasibility of the adult age estimation method developed on living people by Pinchi et al. (2015 and 2018), for estimating the age at the death of 37 subjects from ancient populations found in two different Italian necropolis of archaeological interest (Mont'e Prama and Florence, X-IX century B.
View Article and Find Full Text PDFDiscovering prominent differences in structural and functional connectomes using a multinomial stochastic block model.
Netw Neurosci
December 2024
Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark.
Understanding the differences between functional and structural human brain connectivity has been a focus of an extensive amount of neuroscience research. We employ a novel approach using the multinomial stochastic block model (MSBM) to explicitly extract components that characterize prominent differences across graphs. We analyze structural and functional connectomes derived from high-resolution diffusion-weighted MRI and fMRI scans of 250 Human Connectome Project subjects, analyzed at group connectivity level across 50 subjects.
View Article and Find Full Text PDFWant 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!