Results 111 to 120 of about 14,363,927 (258)
The Relationship of Study and Learning approaches with Students’ Academic Achievement in Rafsanjan University of Medical Sciences [PDF]
Introduction: Most experts consider learning approach as the fundamental basis of learning dividing it into two parts of deep learning approach and surface learning approach.
Effat Shahrabadi +2 more
doaj
This review focuses on the role of autophagy and mitophagy in maintaining pancreatic β‐cell function and homeostasis. We discuss how genetic defects affecting these pathways contribute to the development of type 1, type 2, monogenic, and gestational diabetes. We further explore their potential as therapeutic targets. Created in BioRender.
Yunkyeong Lee +2 more
wiley +1 more source
The Influence of the Deep Learning Approach on Students' Physics Learning Outcomes
This study aims to analyze the effect of a Deep Learning approach combined with Problem-Based Learning (PBL) on students' physics learning outcomes regarding the topic of the First Law of Thermodynamics. The urgency of this research is based on students'
Dina Suardin +5 more
doaj +1 more source
Ligand‐dependent transcriptional heterogeneity in cell cycle gene expression delays G1/S entry
EGF and HRG induce distinct G1/S progression programs in ErbB2‐amplified BT474 breast cancer cells. Despite activating the potent ErbB2–ErbB3 heterodimer, HRG does not accelerate cell‐cycle entry. Instead, EGF promotes earlier restriction‐point passage via ERK–FOS signaling, whereas HRG activates the AKT–MYC axis, driving transcriptional heterogeneity ...
Ririn Rahmala Febri +5 more
wiley +1 more source
Emerging experimental and computational methods for studying redox‐regulated structural transitions
Redox reactions can reshape proteins and alter how they behave in cells, with important consequences for health and disease. This review explores emerging experimental and computational approaches for discovering these redox‐sensitive protein switches, revealing their structural effects, and predicting their behavior, opening new opportunities to ...
Tasneem Rass +2 more
wiley +1 more source
Illustration of the deep brain stimulation approach.
Illustration of the deep brain stimulation approach.
Ping Liang (30204) +5 more
core +1 more source
Synergistic perspectives—How single‐molecule biophysics complement biochemical understanding
In this review, we discuss how ensemble biochemistry and single‐molecule approaches are complementary, outline commonly used single‐molecule techniques, and illustrate their relevance through two representative case studies: chromatin organization by SMC complexes and pathway choice during DNA double‐strand break repair.
Sara De Bragança +2 more
wiley +1 more source
Data envelopment analysis of clinics with sparse data: fuzzy clustering approach [PDF]
This paper presents a method for utilizing Data Envelopment Analysis (DEA) with sparse input and output data using fuzzy clustering concepts. DEA, a methodology to assess relative technical efficiency of production units is susceptible to missing data ...
Ben-Arieh, David, Gullipalli, Deep Kumar
core
TG-DGM: Clustering Brain Activity using a Temporal Graph Deep Generative Mode
Spatiotemporal graphs are a natural representation of dynamic brain activity derived from functional magnetic imaging (fMRI) data. Previous works, however, tend to ignore time dynamics of the brain and focus on static graphs.
Simeon Emilov Spasov +5 more
core
How do genomes gain new functional parts? In eukaryotes, which tend to evolve under weak selection, much of the genome is junk. Palazzo and Qiu borrow the logic of Markov chains to show how non‐functional DNA becomes functional through the appearance of intermediate states, which arise due to epistasis, buffering, and biochemical messiness, allowing ...
Alexander F. Palazzo, Yi Qiu
wiley +1 more source

