Results 41 to 50 of about 3,413,435 (251)
Symbolic Versus Associative Learning [PDF]
Cognitive Science, 2010 AbstractRamscar and colleagues (2010, this volume) describe the “feature‐label‐order” (FLO) effect on category learning and characterize it as a constraint on symbolic learning. I argue that FLO is neither a constraint on symbolic learning in the sense of “learning elements of a symbol system” (instead, it is an effect on nonsymbolic, association ...
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Molecular Oncology, EarlyView.Etoposide induces DNA damage, activating p53‐dependent apoptosis via caspase‐3/7, which cleaves PARP1. Dammarenediol II enhances this apoptotic pathway by suppressing O‐GlcNAc transferase activity, further decreasing O‐GlcNAcylation. The reduction in O‐GlcNAc levels boosts p53‐driven apoptosis and influences the Akt/GSK3β/mTOR signaling pathway ...
Jaehoon Lee +8 more
wiley +1 more source
Tumor mutational burden as a determinant of metastatic dissemination patterns
Molecular Oncology, EarlyView.This study performed a comprehensive analysis of genomic data to elucidate whether metastasis in certain organs share genetic characteristics regardless of cancer type. No robust mutational patterns were identified across different metastatic locations and cancer types.
Eduardo Candeal +4 more
wiley +1 more source
Associative Learning: Hebbian Flies [PDF]
Current Biology, 2005 Fruit flies can learn to associate an odor with an aversive stimulus, such as a shock. New findings indicate that disrupting the expression of N-methyl-D-aspartate (NMDA) receptors in flies impairs olfactory conditioning. The findings provide support for a critical role for NMDA receptors in associative learning.
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Maths Apps index #maths4us Project Report [PDF]
, 2013 This report provides an overview of the Maths Apps index project led by the Association for Learning Technology (ALT) as part of the maths4us initiative during 2012 ...
ALT, ALT
core
Libraries and Student Retention
, 2016 Mick Williams presented the workshop “Libraries and Student Retention” at the June 2015 Association of Christian Librarians Conference. This article of the same name encapsulates key points that were shared during the workshop’s PowerPoint presentation ...
Williams, Mick
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Molecular Oncology, EarlyView.To integrate multiple transcriptomics data with severe batch effects for identifying MB subtypes, we developed a novel and accurate computational method named RaMBat, which leveraged subtype‐specific gene expression ranking information instead of absolute gene expression levels to address batch effects of diverse data sources.
Mengtao Sun, Jieqiong Wang, Shibiao Wan
wiley +1 more source
Subtype‐specific enhancer RNAs define transcriptional regulators and prognosis in breast cancers
Molecular Oncology, EarlyView.This study employed machine learning methodologies to perform the subtype‐specific classification of RNA‐seq data sets, which are mapped on enhancers from TCGA‐derived breast cancer patients. Their integration with gene expression (referred to as ProxCReAM eRNAs) and chromatin accessibility profiles has the potential to identify lineage‐specific and ...
Aamena Y. Patel +6 more
wiley +1 more source
Learning of Human-like Algebraic Reasoning Using Deep Feedforward Neural Networks
, 2017 There is a wide gap between symbolic reasoning and deep learning. In this research, we explore the possibility of using deep learning to improve symbolic reasoning.
Cai, Cheng-Hao +3 more
core +1 more source
Molecular Oncology, EarlyView.Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source