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DeepGOMeta for functional insights into microbial communities using deep learning-based protein function prediction.
Sci Rep
December 2024
KAUST Center of Excellence for Smart Health (KCSH), King Abdullah University of Science and Technology, Thuwal, 23955, Saudi Arabia.
Analyzing microbial samples remains computationally challenging due to their diversity and complexity. The lack of robust de novo protein function prediction methods exacerbates the difficulty in deriving functional insights from these samples. Traditional prediction methods, dependent on homology and sequence similarity, often fail to predict functions for novel proteins and proteins without known homologs.
View Article and Find Full Text PDFOptimizing VGG16 deep learning model with enhanced hunger games search for logo classification.
Sci Rep
December 2024
Department of Computer Science, Birzeit University, P.O. Box 14, Birzeit, West Bank, Palestine.
Accurate classification of logos is a challenging task in image recognition due to variations in logo size, orientation, and background complexity. Deep learning models, such as VGG16, have demonstrated promising results in handling such tasks. However, their performance is highly dependent on optimal hyperparameter settings, whose fine-tuning is both labor-intensive and time-consuming.
View Article and Find Full Text PDFNeutral drift upon threshold-like selection promotes variation in antibiotic resistance phenotype.
Nat Commun
December 2024
Michael Smith Laboratories, University of British Columbia, Vancouver, V6T 1Z4, BC, Canada.
Heritable phenotypic variation plays a central role in evolution by conferring rapid adaptive capacity to populations. Mechanisms that can explain genetic diversity by describing connections between genotype and organismal fitness have been described. However, the difficulty of acquiring comprehensive data on genotype-phenotype-environment relationships has hindered the efforts to explain how the ubiquitously observed phenotypic variation in populations emerges and is maintained.
View Article and Find Full Text PDFAccurate stacking engineering of MOF nanosheets as membranes for precise H sieving.
Nat Commun
December 2024
Beijing Key Laboratory for Membrane Materials and Engineering, Department of Chemical Engineering, Tsinghua University, Beijing, 100084, China.
Two-dimensional (2D) metal-organic framework (MOF) nanosheet membranes hold promise for exact molecular transfer due to their structural diversity and well-defined in-plane nanochannels. However, achieving precise regulation of stacking modes between neighboring nanosheets in membrane applications and understanding its influence on separation performance remains unrevealed and challenging. Here, we propose a strategy for accurately controlling the stacking modes of MOF nanosheets via linker polarity regulation.
View Article and Find Full Text PDFMultifunctional 2D FETs exploiting incipient ferroelectricity in freestanding SrTiO nanomembranes at sub-ambient temperatures.
Nat Commun
December 2024
Engineering Science and Mechanics, Penn State University, University Park, PA, USA.
Incipient ferroelectricity bridges traditional dielectrics and true ferroelectrics, enabling advanced electronic and memory devices. Firstly, we report incipient ferroelectricity in freestanding SrTiO nanomembranes integrated with monolayer MoS to create multifunctional devices, demonstrating stable ferroelectric order at low temperatures for cryogenic memory devices. Our observation includes ultra-fast polarization switching (~10 ns), low switching voltage (<6 V), over 10 years of nonvolatile retention, 100,000 endurance cycles, and 32 conductance states (5-bit memory) in SrTiO-gated MoS transistors at 15 K and up to 100 K.
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