In microarray data analysis, traditional methods that focus on single genes are increasingly replaced by methods that analyse functional units corresponding to biochemical pathways, as these are considered to offer more insight into gene expression and disease associations. However, the development of robust pipelines to relate genotypic functional modules to disease phenotypes through known molecular interactions is still at its early stages. In this article we first discuss methodologies that employ groups of genes in disease classification tasks that aim to link gene expression patterns with disease outcome. Then we present a pathway-based approach for disease classification through a mathematical programming model based on hyper-box principles. Association rules derived from the model are extracted and discussed with respect to pathway-specific molecular patterns related to the disease. Overall, we argue that the use of gene sets corresponding to disease-relevant pathways is a promising route to uncover expression-to-phenotype relations in disease classification and we illustrate the potential of hyper-box classification in assessing the predictive power of functional pathways and uncover the effect of specific genes in the prediction of disease phenotypes.
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http://dx.doi.org/10.1016/j.mbs.2014.09.005 | DOI Listing |
Mol Biol Rep
January 2025
Advanced Centre for Plant Virology, Division of Plant Pathology, ICAR-Indian Agricultural Research Institute, New Delhi, 110012, India.
Background: Sugarcane is cultivated globally and affected by more than 125 pathogens, which lead to various plant diseases. In recent years, high-throughput sequencing (HTS)-based genome analyses have been broadly adopted for the discovery of both characterized and un-characterized viruses from plant samples. In this study, the HTS data of sugarcane pooled sample retrieved from sequence read archive (SRA) were de novo re-assembled using CLC Genomic Workbench.
View Article and Find Full Text PDFArch Gynecol Obstet
January 2025
Department of Congenital Cardiac Surgery, IRCCS Policlinico San Donato, 20097, San Donato, Milan, Italy.
Objectives: Congenital thoracic masses (CTMs) are suspected in presence of solid or cystic thoracic lesions at ultrasound. The common typical fetal CTMs encompass: hyperechogenic lung lesions such as congenital pulmonary airway malformation (CPAM), broncopulmonary sequestration (PS) and congenital high airway obstruction syndrome (CHAOS); less common solid thoracic masses are mediastinal/pericardial tumors as rhabdomyoma and teratoma. The aim of our study is to gather the available evidence on cases of atypical CTMs of difficult classification, for which the diagnosis remains often uncertain.
View Article and Find Full Text PDFOsteoporos Int
January 2025
Academy for Engineering and Technology, Fudan University, Shanghai, China.
Unlabelled: This study utilized deep learning for bone mineral density (BMD) prediction and classification using biplanar X-ray radiography (BPX) images from Huashan Hospital Medical Checkup Center. Results showed high accuracy and strong correlation with quantitative computed tomography (QCT) results. The proposed models offer potential for screening patients at a high risk of osteoporosis and reducing unnecessary radiation and costs.
View Article and Find Full Text PDFElife
January 2025
Institute for Infectious Diseases and Infection Control, Jena University Hospital, Jena, Germany.
Given the rapid cross-country spread of SARS-CoV-2 and the resulting difficulty in tracking lineage spread, we investigated the potential of combining mobile service data and fine-granular metadata (such as postal codes and genomic data) to advance integrated genomic surveillance of the pandemic in the federal state of Thuringia, Germany. We sequenced over 6500 SARS-CoV-2 Alpha genomes (B.1.
View Article and Find Full Text PDFMusculoskeletal Care
March 2025
Department of Rheumatology, Karamanoğlu Mehmetbey University, Karaman, Turkey.
Introduction: Fibromyalgia (FM) is a chronic syndrome characterised by widespread pain, fatigue, and symptoms such as sleep disturbances, cognitive impairment, and mood disorders. FM prevalence is notably higher among systemic lupus erythematosus (SLE) patients compared with the general population, often leading to diagnostic challenges. Misinterpreting FM as SLE activity can result in overtreatment.
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