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Despite its wide usage in biological databases and applications, the role of the gene ontology (GO) in network analysis is usually limited to functional annotation of genes or gene sets with auxiliary information on correlations ignored. Here, we report on new capabilities of VisANT--an integrative software platform for the visualization, mining, analysis and modeling of the biological networks--which extend the application of GO in network visualization, analysis and inference. The new VisANT functions can be classified into three categories. (i) Visualization: a new tree-based browser allows visualization of GO hierarchies. GO terms can be easily dropped into the network to group genes annotated under the term, thereby integrating the hierarchical ontology with the network. This facilitates multi-scale visualization and analysis. (ii) Flexible annotation schema: in addition to conventional methods for annotating network nodes with the most specific functional descriptions available, VisANT also provides functions to annotate genes at any customized level of abstraction. (iii) Finding over-represented GO terms and expression-enriched GO modules: two new algorithms have been implemented as VisANT plugins. One detects over-represented GO annotations in any given sub-network and the other finds the GO categories that are enriched in a specified phenotype or perturbed dataset. Both algorithms take account of network topology (i.e. correlations between genes based on various sources of evidence). VisANT is freely available at http://visant.bu.edu.
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http://dx.doi.org/10.1093/nar/gkp406 | DOI Listing |
Fluids Barriers CNS
September 2025
Department of Medical Sciences, Neurology, Uppsala University, Uppsala, Sweden.
Background: Idiopathic normal pressure hydrocephalus (iNPH) predominantly manifests with gait disturbances, yet clinical assessments are vulnerable to confirmation bias, particularly post-shunt surgery. Blinded video evaluations are a method to enhance objectivity in gait assessment, but their reliability has never been systematically investigated. The aim was to evaluate the inter-rater reliability of blinded gait assessments in iNPH patients and to investigate how these assessments correlate with the Hellström iNPH scale and patient-reported health status following shunt surgery.
View Article and Find Full Text PDFLipids Health Dis
September 2025
Department of Gastroenterology, Weifang People's Hospital, The First Affiliated Hospital of Shandong Second Medical University, 151 Guangwen Street, Weifang, Shandong, 261000, China.
Background: Current scoring systems for hypertriglyceridaemia-induced acute pancreatitis (HTG-AP) severity are few and lack reliability. The present work focused on screening predicting factors for HTG-SAP, then constructing and validating the visualization model of HTG-AP severity by combining relevant metabolic indexes.
Methods: Between January 2020 and December 2024, retrospective clinical information for HTG-AP inpatients from Weifang People's Hospital was examined.
BMC Musculoskelet Disord
September 2025
Department of Clinical Sciences at Danderyds Hospital, Department of Orthopedic Surgery, Karolinska Institutet, Stockholm, 182 88, Sweden.
Background: This study evaluates the accuracy of an Artificial Intelligence (AI) system, specifically a convolutional neural network (CNN), in classifying elbow fractures using the detailed 2018 AO/OTA fracture classification system.
Methods: A retrospective analysis of 5,367 radiograph exams visualizing the elbow from adult patients (2002-2016) was conducted using a deep neural network. Radiographs were manually categorized according to the 2018 AO/OTA system by orthopedic surgeons.
Metabolomics
September 2025
Toxalim (Research Centre in Food Toxicology), Université de Toulouse, INRAE, ENVT, INP-Purpan, UPS, Toulouse, France.
Introduction: Initially developed for transcriptomics data, pathway analysis (PA) methods can introduce biases when applied to metabolomics data, especially if input parameters are not chosen with care. This is particularly true for exometabolomics data, where there can be many metabolic steps between the measured exported metabolites in the profile and internal disruptions in the organism. However, evaluating PA methods experimentally is practically impossible when the sample's "true" metabolic disruption is unknown.
View Article and Find Full Text PDFGeroscience
September 2025
Department of Neurology, Albert Einstein College of Medicine, Bronx, NY, USA.
Cognitive decline is common in multiple sclerosis (MS), although neural mechanisms are not fully understood. The objective was to investigate the impact of mild cognitive impairment (MCI) on the relationship between resting state functional connectivity (RSFC) and cognitive function in older adults with multiple sclerosis (OAMS) and age matched healthy controls. Participants underwent magnetic resonance imaging (MRI) scans and cognitive assessments.
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