Results 71 to 80 of about 114,572 (313)

Investigating transcription factor dynamics in health and disease using FRAP

FEBS Letters, EarlyView.
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj, Carolina Vazquez Garzon, Jose Joaquin Velasco, Janine N. Post   +3 more
wiley   +1 more source

Loose L1/2 regularised sparse representation for face recognition

IET Computer Vision, 2015
Sparse representation (or sparse coding) has been applied to deal with frontal face recognition. Two representative methods are the sparse representation‐based classification (SRC) and the collaborative representation‐based classification (CRC), in which
Dexing Zhong, Zichao Xie, Yanrui Li, Jiuqiang Han   +3 more
doaj   +1 more source

Weak Signal Detection Based on Combination of Sparse Representation and Singular Value Decomposition

Applied Sciences, 2022
Due to the inevitable acquisition system noise and strong background noise, it is often difficult to detect the features of weak signals. To solve this problem, sparse representation can effectively extract useful information according to the sparse ...
Huijie Ma, Shunming Li, Xianglian Li, Jiantao Lu   +3 more
doaj   +1 more source

Fast Kernel Sparse Representation [PDF]

2011 International Conference on Digital Image Computing: Techniques and Applications, 2011
Two efficient algorithms are proposed to seek the sparse representation on high-dimensional Hilbert space. By proving that all the calculations in Orthogonal Match Pursuit (OMP) are essentially inner-product combinations, we modify the OMP algorithm to apply the kernel-trick.
Hanxi Li, Yongsheng Gao 0001, Jun Sun
openaire   +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, Peyman Zarrineh, Nathnael T. Tuffa, Jigar H. Sheth, Sumitra Mohan, Mudassar Iqbal, Sankari Nagarajan   +6 more
wiley   +1 more source

Kernel difference maximisation-based sparse representation for more accurate face recognition

The Journal of Engineering, 2020
Most methods for sparse representation are designed to be used in the original space. However, their performance is not always satisfactory especially when training samples are limited.
Lian Wu, Wenbo Xu, Jianchuan Zhao, Zhongwei Cui, Yong Zhao   +4 more
doaj   +1 more source

Classification of music genres using sparse representations in overcomplete dictionaries [PDF]

, 2011
This paper presents a simple, but efficient and robust, method for music genre classification that utilizes sparse representations in overcomplete dictionaries.
Rusu, Cristian
core  

A sparse representation method for determining the optimal illumination directions in Photometric Stereo [PDF]

, 2013
The analysis of surface and texture details with the help of changes in illumination direction is a key task in 3D shape reconstruction either based on Photometric Stereo, Shape from Shading or Structured Light.
Petrou, Maria, Zafeiriou, S., Argyriou, Vasileios, Villarini, Barbara, Argyriou, V., Villarini, B., Zafeiriou, Stefanos, Petrou, M.   +7 more
core   +1 more source

Network divergence analysis identifies adaptive gene modules and two orthogonal vulnerability axes in pancreatic cancer

Molecular Oncology, EarlyView.
Tumors contain diverse cellular states whose behavior is shaped by context‐dependent gene coordination. By comparing gene–gene relationships across biological contexts, we identify adaptive transcriptional modules that reorganize into distinct vulnerability axes.
Brian Nelson, Lyanne Delgado‐Coka, Natalia Marchenko, Luisa F. Escobar‐Hoyos, Kenneth R. Shroyer, Alisa Yurovsky, Trey Ideker, Gábor Balázsi, Thomas MacCarthy, Scott Powers   +9 more
wiley   +1 more source

Analysis for sparse channel representation based on dictionary learning in massive MIMO systems

IET Communications
The accuracy analysis of dictionary sparse representation for channels in massive MIMO systems is a relatively unexplored field. Existing research has primarily focused on investigating the accuracy of dictionary sparse representation using simulation in
Qing‐Yang Guan
doaj   +1 more source