Functional genomics techniques based on next-generation sequencing provide new avenues for studying host responses to viral infections at multiple levels, including transcriptional and translational processes and chromatin organization. This chapter provides an overview on the computational integration of multiple types of "omics" data on lytic herpes simplex virus 1 (HSV-1) infection. It summarizes methods developed and applied in two publications that combined 4sU-seq for studying de novo transcription, ribosome profiling for investigating active translation, RNA-seq of subcellular RNA fractions for determining subcellular location of transcripts, and ATAC-seq for profiling chromatin accessibility genome-wide. These studies revealed an unprecedented disruption of transcription termination in HSV-1 infection resulting in widespread read-through transcription beyond poly(A) sites for most but not all host genes. This impacts chromatin architecture by increasing chromatin accessibility selectively in downstream regions of affected genes. In this way, computational integration of multi-omics data identified novel and unsuspected mechanisms at play in lytic HSV-1 infection.
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JMIR Med Inform
January 2025
INSERM U1064, CR2TI - Center for Research in Transplantation and Translational Immunology, Nantes University, 30 Bd Jean Monnet, Nantes, 44093, France, 33 2 40 08 74 10.
Precision medicine involves a paradigm shift toward personalized data-driven clinical decisions. The concept of a medical "digital twin" has recently become popular to designate digital representations of patients as a support for a wide range of data science applications. However, the concept is ambiguous when it comes to practical implementations.
View Article and Find Full Text PDFBMC Pulm Med
January 2025
Department of Respiratory Medicine, Faculty of Life Sciences, Kumamoto University, Kumamoto 1-1-1 Honjo, Chuo-ku, 860-8556, Japan.
Background: Fibrotic types of interstitial lung abnormalities seen on high-resolution computed tomography scans, characterised by traction bronchiolectasis/bronchiectasis with or without honeycombing, are predictors of progression and poor prognostic factors of interstitial lung abnormalities. There are no reports on the clinical characteristics of fibrotic interstitial lung abnormalities on high-resolution computed tomography scans. Therefore, we aimed to examine these clinical characteristics and clarify the predictive factors of fibrotic interstitial lung abnormalities on high-resolution computed tomography scans.
View Article and Find Full Text PDFBMC Bioinformatics
January 2025
Department of Surgery, Shanghai Key Laboratory of Gastric Neoplasms, Shanghai Institute of Digestive Surgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Background: Single-cell RNA sequencing (scRNA-seq) has transformed biological research by offering new insights into cellular heterogeneity, developmental processes, and disease mechanisms. As scRNA-seq technology advances, its role in modern biology has become increasingly vital. This study explores the application of deep learning to single-cell data clustering, with a particular focus on managing sparse, high-dimensional data.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Electrical Engineering, City University of Hong Kong, Hong Kong SAR, China.
Analog In-memory Computing (IMC) has demonstrated energy-efficient and low latency implementation of convolution and fully-connected layers in deep neural networks (DNN) by using physics for computing in parallel resistive memory arrays. However, recurrent neural networks (RNN) that are widely used for speech-recognition and natural language processing have tasted limited success with this approach. This can be attributed to the significant time and energy penalties incurred in implementing nonlinear activation functions that are abundant in such models.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmaceutics, College of Pharmacy, King Saud University, PO Box 2457, Riyadh, 11451, Saudi Arabia.
Prostate cancer presents a major health issue, with its progression influenced by intricate molecular factors. Notably, the interplay between miRNAs and changes in transcriptomic patterns is not fully understood. Our study seeks to bridge this knowledge gap, employing computational techniques to explore how miRNAs and transcriptomic alterations jointly regulate the development of prostate cancer.
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