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Computational biology and bioinformatics is an interdisciplinary field that develops and applies computational methods to analyse large collections of biological data, such as genetic sequences, cell populations or protein samples, to make new predictions or discover new biology. The computational methods used include analytical methods, mathematical modelling and simulation.
Multicellular modeling is increasingly being used to understand biological systems. SimuCell3D is a tool that allows mechanically realistic simulations, using the deformable cell model, to be developed and run.
Vision–language models can be trained to read cardiac ultrasound images with implications for improving clinical workflows, but additional development and validation will be required before such models can replace humans.
Skeletal muscle is a highly heterogenous tissue that comprises multiple cell types. Leveraging single-cell and single-nucleus experiments, we systematically mapped the cellular and molecular changes across different skeletal muscle compartments with age. We identify neuromuscular-junction accessory nuclei that may be pivotal in mitigating denervation and uncovered differences between myofiber and myonucleus aging.
A randomized controlled trial showed that following a personalized dietary program led to significant improvements in cardiometabolic and gut health as well as reductions in body weight compared to following standard dietary advice according to US Department of Agriculture guidelines.
A GWAS finds genetic link in ABCC9 gene affecting vocal pitch in both Mandarin and Icelandic speakers, suggesting a shared genetic influence on human vocal systems across populations.
There is a need to determine circadian time in gene expression datasets. Here, authors built tauFisher, a pipeline that predicts circadian time labels from single transcriptomic samples. tauFisher will be useful for determining body clock time in circadian medicine and for research.
This study presents a machine learning model that accurately predicts seasonal antigenic changes of influenza A H3N2 using genetic data. The model’s predictions can aid influenza surveillance, vaccine strain selection, and public health management.
Multicellular modeling is increasingly being used to understand biological systems. SimuCell3D is a tool that allows mechanically realistic simulations, using the deformable cell model, to be developed and run.
Vision–language models can be trained to read cardiac ultrasound images with implications for improving clinical workflows, but additional development and validation will be required before such models can replace humans.