Results 141 to 150 of about 8,286,998 (397)

Gauge field corrections to 11-dimensional supergravity via dimensional reduction [PDF]

, 2017
Using the fact that eleven-dimensional supergravity yields type IIA supergravity under dimensional reduction on a circle, we determine higher-derivative terms of 11-dimensional supergravity including the $ R^4 $, $ ({\partial {F_4}})^2 R^2 $ and $ ({\partial {F_4}})^4 $ terms.
arxiv   +1 more source

Dimensionality Reduction Algorithms on High Dimensional Datasets

Emitter: International Journal of Engineering Technology, 2014
Classification problem especially for high dimensional datasets have attracted many researchers in order to find efficient approaches to address them. However, the classification problem has become very complicatedespecially when the number of possible ...
Iwan Syarif
doaj   +3 more sources

Thermal proteome profiling and proteome analysis using high‐definition mass spectrometry demonstrate modulation of cholesterol biosynthesis by next‐generation galeterone analog VNPP433‐3β in castration‐resistant prostate cancer

Molecular Oncology, EarlyView.
Elevated level of cholesterol is positively correlated to prostate cancer development and disease severity. Cholesterol‐lowering drugs, such as statins, are demonstrated to inhibit prostate cancer. VNPP433‐3β interrupts multiple signaling and metabolic pathways, including cholesterol biosynthesis, AR‐mediated transcription of several oncogenes, mRNA 5′
Retheesh S. Thankan, Elizabeth Thomas, Mehari M. Weldemariam, Puranik Purushottamachar, Weiliang Huang, Maureen A. Kane, Yuji Zhang, Nicholas Ambulos, Bi‐Dar Wang, David Weber, Vincent C. O. Njar   +10 more
wiley   +1 more source

A Visual Interaction Framework for Dimensionality Reduction Based Data Exploration [PDF]

arXiv, 2018
Dimensionality reduction is a common method for analyzing and visualizing high-dimensional data. However, reasoning dynamically about the results of a dimensionality reduction is difficult. Dimensionality-reduction algorithms use complex optimizations to reduce the number of dimensions of a dataset, but these new dimensions often lack a clear relation ...
arxiv  

Elucidating prognostic significance of purine metabolism in colorectal cancer through integrating data from transcriptomic, immunohistochemical, and single‐cell RNA sequencing analysis

Molecular Oncology, EarlyView.
Low expression of five purine metabolism‐related genes (ADSL, APRT, ADCY3, NME3, NME6) was correlated with poor survival in colorectal cancer. Immunohistochemistry analysis showed that low NME3 (early stage) and low ADSL/NME6 (late stage) levels were associated with high risk.
Sungyeon Kim, Myunghee Kang, Soyeon Jeong, Jisup Kim, Kyoung Oh Kim, Won‐Suk Lee, Jeong‐Heum Baek, Jung Ho Kim, Seungyoon Nam   +8 more
wiley   +1 more source

Exploration of heterogeneity and recurrence signatures in hepatocellular carcinoma

Molecular Oncology, EarlyView.
This study leveraged public datasets and integrative bioinformatic analysis to dissect malignant cell heterogeneity between relapsed and primary HCC, focusing on intercellular communication, differentiation status, metabolic activity, and transcriptomic profiles.
Wen‐Jing Wu, Jianchao Wang, Fuqing Chen, Xuefeng Wang, Bin Lan, Ruyi Fu, Hong Wen, Fangfang Chen, Wei Hong, Tian‐Yu Tang, Ying He, Gang Chen, Jianyin Zhou, Hai‐Long Piao, Di Chen, Shu‐Yong Lin   +15 more
wiley   +1 more source

Dimensionality Reduction via Multiple Locality-Constrained Graph Optimization

IEEE Access, 2018
In recent years, graph-based dimensionality reduction methods became increasingly more significant since they have been successfully applied in various computer vision and machine learning problems.
Caixia Zheng, Rui Zhao, Fucong Liu, Jun Kong, Jianzhong Wang, Chao Bi, Yugen Yi   +6 more
doaj   +1 more source

A large‐scale retrospective study in metastatic breast cancer patients using circulating tumour DNA and machine learning to predict treatment outcome and progression‐free survival

Molecular Oncology, EarlyView.
There is an unmet need in metastatic breast cancer patients to monitor therapy response in real time. In this study, we show how a noninvasive and affordable strategy based on sequencing of plasma samples with longitudinal tracking of tumour fraction paired with a statistical model provides valuable information on treatment response in advance of the ...
Emma J. Beddowes, Mario Ortega Duran, Solon Karapanagiotis, Alistair Martin, Meiling Gao, Riccardo Masina, Ramona Woitek, James Tanner, Fleur Tippin, Justine Kane, Jonathan Lay, Anja Brouwer, Stephen‐John Sammut, Suet‐Feung Chin, Davina Gale, Dana W. Y. Tsui, Sarah‐Jane Dawson, Nitzan Rosenfeld, Maurizio Callari, Oscar M. Rueda, Carlos Caldas   +20 more
wiley   +1 more source

Nonlinear Dimensionality Reduction

Computer Vision, 2021
P. Fua
semanticscholar   +1 more source

Escape from TGF‐β‐induced senescence promotes aggressive hallmarks in epithelial hepatocellular carcinoma cells

Molecular Oncology, EarlyView.
Chronic TGF‐β exposure drives epithelial HCC cells from a senescent state to a TGF‐β resistant mesenchymal phenotype. This transition is characterized by the loss of Smad3‐mediated signaling, escape from senescence, enhanced invasiveness and metastatic potential, and upregulation of key resistance modulators such as MARK1 and GRM8, ultimately promoting
Minenur Kalyoncu, Dilara Demirci, Sude Eris, Bengisu Dayanc, Ece Cakiroglu, Merve Basol, Merve Uysal, Gulcin Cakan‐Akdogan, Fang Liu, Mehmet Ozturk, Gökhan Karakülah, Serif Senturk   +11 more
wiley   +1 more source