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Krait2: a versatile software for microsatellite investigation, visualization and marker development.
BMC Genomics
January 2025
Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Sichuan Province and Ministry of Education, Southwest Minzu University, Chengdu, 610225, China.
Background: Microsatellites are highly polymorphic repeat sequences ubiquitously interspersed throughout almost all genomes which are widely used as powerful molecular markers in diverse fields. Microsatellite expansions play pivotal roles in gene expression regulation and are implicated in various neurological diseases and cancers. Although much effort has been devoted to developing efficient tools for microsatellite identification, there is still a lack of a powerful tool for large-scale microsatellite analysis.
View Article and Find Full Text PDFA vision model for automated frozen tuna processing.
Sci Rep
January 2025
School of Food and Pharmacy, Zhejiang Ocean University, Zhoushan, 316022, People's Republic of China.
Accurate and rapid segmentation of key parts of frozen tuna, along with precise pose estimation, is crucial for automated processing. However, challenges such as size differences and indistinct features of tuna parts, as well as the complexity of determining fish poses in multi-fish scenarios, hinder this process. To address these issues, this paper introduces TunaVision, a vision model based on YOLOv8 designed for automated tuna processing.
View Article and Find Full Text PDFLigand interaction landscape of transcription factors and essential enzymes in E. coli.
Cell
January 2025
Program in Bioinformatics, Boston University, Boston, MA 02215, USA; Department of Molecular Genetics, University of Toronto, Toronto, ON M5S 1A8, Canada; Center for Network Systems Biology, Boston University, Boston, MA 02218, USA; Department of Chemistry, Boston University, Boston, MA 02215, USA; Department of Chemical Physiology and Biochemistry, Division of Oncological Sciences, Knight Cancer Institute, Oregon Health and Science University, Portland, OR, USA. Electronic address:
Knowledge of protein-metabolite interactions can enhance mechanistic understanding and chemical probing of biochemical processes, but the discovery of endogenous ligands remains challenging. Here, we combined rapid affinity purification with precision mass spectrometry and high-resolution molecular docking to precisely map the physical associations of 296 chemically diverse small-molecule metabolite ligands with 69 distinct essential enzymes and 45 transcription factors in the gram-negative bacterium Escherichia coli. We then conducted systematic metabolic pathway integration, pan-microbial evolutionary projections, and independent in-depth biophysical characterization experiments to define the functional significance of ligand interfaces.
View Article and Find Full Text PDFPharmacological, computational, and mechanistic insights into triptolide's role in targeting drug-resistant cancers.
Naunyn Schmiedebergs Arch Pharmacol
January 2025
Research and Enterprise, University of Cyberjaya, Persiaran Bestari, Cyber 11, 63000, Cyberjaya, Selangor, Malaysia.
As a promising candidate for tackling drug-resistant cancers, triptolide, a diterpenoid derived from the Chinese medicinal plant Tripterygium wilfordii, has been developed. This review summarizes potential antitumor activities, including the suppression of RNA polymerase II, the suppression of heat shock proteins (HSP70 and HSP90), and the blockade of NF-kB signalling. Triptolide is the first known compound to target cancer cells specifically but spare normal cells, and it has success in treating cancers that are difficult to treat, including pancreatic, breast, and lung cancers.
View Article and Find Full Text PDFLigand-Conditioned Side Chain Packing for Flexible Molecular Docking.
J Chem Theory Comput
January 2025
State Key Laboratory of Physical Chemistry of Solid Surfaces and Fujian Provincial Key Laboratory of Theoretical and Computational Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, P. R. China.
Molecular docking is a crucial technique for elucidating protein-ligand interactions. Machine learning-based docking methods offer promising advantages over traditional approaches, with significant potential for further development. However, many current machine learning-based methods face challenges in ensuring the physical plausibility of generated docking poses.
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