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Biology has been transformed by the rapid development of computing and the concurrent rise of data-rich approaches such as, omics or high-resolution imaging. However, there is a persistent computational skills gap in the biomedical research workforce. Inherent limitations of classroom teaching and institutional core support highlight the need for accessible ways for researchers to explore developments in computational biology. An analysis of the Scripps Research Genomics Core revealed increases in the total number and diversity of experiments: the share of experiments other than bulk RNA- or DNA-sequencing increased from 34% to 60% within 10 years, requiring more tailored computational analyses. These challenges were tackled by forming a volunteer-led affinity group of approximately 300 academic biomedical researchers interested in computational biology, referred to as the Computational Biology and Bioinformatics (CBB) affinity group. This adaptive group has provided continuing education and networking opportunities through seminars, workshops, and coding sessions while evolving along with the needs of its members. A survey of CBB's impact confirmed the group's events increased the members' exposure to computational biology educational and research events (79% respondents) and networking opportunities (61% respondents). Thus, volunteer-led affinity groups may be a viable complement to traditional institutional resources for enhancing the application of computing in biomedical research.
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http://dx.doi.org/10.1371/journal.pcbi.1013453 | DOI Listing |
Haematologica
September 2025
Division of Hematopathology, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, NY; Multiparametric In Situ Imaging (MISI) Laboratory, Department of Pathology and Laboratory Medicine, Weill Cornell Medicine, New York.
Not available.
View Article and Find Full Text PDFHaematologica
September 2025
Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX.
Not available.
View Article and Find Full Text PDFArterioscler Thromb Vasc Biol
September 2025
Vascular Biology Program, Boston Children's Hospital and Harvard Medical School, MA (K. Cui, B.Z., B.W., S.E.-B., A.V., H.C.).
Background: Atherosclerosis is a chronic inflammatory disease characterized by the accumulation of lipid-laden foam cells and plaques within the arterial wall. Dysfunctional vascular smooth muscle cells (VSMCs), fibroblasts, endothelial cells, and macrophages contribute to disease progression. Here, we report that macrophage-specific expression of epsins, highly conserved endocytic adaptor proteins involved in clathrin-mediated endocytosis, accelerates atherosclerosis in Western diet-fed mice.
View Article and Find Full Text PDFF1000Res
September 2025
Cambridge Centre for Proteomics, Department of Biochemistry, University of Cambridge, Cambridge, CB2 1QR, UK.
Background: Subcellular localisation is a determining factor of protein function. Mass spectrometry-based correlation profiling experiments facilitate the classification of protein subcellular localisation on a proteome-wide scale. In turn, static localisations can be compared across conditions to identify differential protein localisation events.
View Article and Find Full Text PDFJ Am Chem Soc
September 2025
Institute for Molecules and Materials, Radboud University, Heyendaalseweg 135, 6525 AJ Nijmegen, The Netherlands.
Non-hydrogenative para-hydrogen-induced polarization (nhPHIP) has proven a powerful tool for the enhanced NMR detection of several classes of metabolites in complex mixtures. Particularly, compounds carrying an α-amino acid motif have been previously detected and quantified in biological samples and natural extracts at submicromolar concentrations using 2D nhPHIP NMR spectroscopy. This technique is here applied for the first time in a semi-targeted metabolomics NMR study on urine from patients suffering from Pyridoxine-Dependent Epilepsy (PDE), currently diagnosed by the presence of dilute unique biomarkers.
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