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| http://dx.doi.org/10.1177/07067437221078411 | DOI Listing |
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Proximity to Practice: The Role of Technology in the Next Era of Assessment.
Perspect Med Educ
December 2024
Faculty of Education, Queen's University, Canada.
The integration of technology into health professions assessment has created multiple possibilities. In this paper, we focus on the challenges and opportunities of integrating technologies that are used during clinical activities or that are completed by raters after a clinical encounter. In focusing on technologies that are more proximal to practice, we identify tradeoffs with different data collection approaches.
View Article and Find Full Text PDFMSA clustering enhances AF-Multimer's ability to predict conformational landscapes of protein-protein interactions.
Bioinform Adv
December 2024
Laboratory of Experimental Biophysics, Center for Advanced Technologies, Tashkent, 100174, Uzbekistan.
Motivation: Understanding the conformational landscape of protein-ligand interactions is critical for elucidating the binding mechanisms that govern these interactions. Traditional methods like molecular dynamics (MD) simulations are computationally intensive, leading to a demand for more efficient approaches. This study explores how multiple sequence alignment (MSA) clustering enhance AF-Multimer's ability to predict conformational landscapes, particularly for proteins with multiple conformational states.
View Article and Find Full Text PDFProtomix: a Python package for H-NMR metabolomics data preprocessing.
Bioinform Adv
November 2024
Laboratory of Molecular Science and Engineering, Åbo Akademi University, Henrikinkatu 2, Turku 20500, Finland.
Motivation: NMR-based metabolomics is a field driven by technological advancements, necessitating the use of advanced preprocessing tools. Despite this need, there is a remarkable scarcity of comprehensive and user-friendly preprocessing tools in Python. To bridge this gap, we have developed Protomix-a Python package designed for metabolomics research.
View Article and Find Full Text PDFSurfR: Riding the wave of RNA-seq data with a comprehensive bioconductor package to identify surface protein-coding genes.
Bioinform Adv
December 2024
Center for Omics Sciences, IRCCS San Raffaele Scientific Institute, Milan 20132, Italy.
Motivation: Proteins at the cell surface connect signaling networks and largely determine a cell's capacity to communicate and interact with its environment. In particular, variations in transcriptomic profiles are often observed between healthy and diseased cells, leading to distinct sets of cell-surface proteins. For these reasons, cell-surface proteins may act as biomarkers for the detection of cells of interest in tissues or body fluids, are often the target of pharmaceutical agents, and hold significant promise in the clinical practice for diagnosis, prognosis, treatment development, and evaluation of therapy response.
View Article and Find Full Text PDFNeural mass modeling for the masses: Democratizing access to whole-brain biophysical modeling with FastDMF.
Netw Neurosci
December 2024
Institucio Catalana de la Recerca i Estudis Avancats (ICREA), Barcelona, Spain.
Different whole-brain computational models have been recently developed to investigate hypotheses related to brain mechanisms. Among these, the Dynamic Mean Field (DMF) model is particularly attractive, combining a biophysically realistic model that is scaled up via a mean-field approach and multimodal imaging data. However, an important barrier to the widespread usage of the DMF model is that current implementations are computationally expensive, supporting only simulations on brain parcellations that consider less than 100 brain regions.
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