Results 61 to 70 of about 3,487,202 (255)

Dimensionality Reduction in Gene Expression Data Sets

IEEE Access, 2019
Dimensionality reduction is used in microarray data analysis to enhance prediction quality, reduce computing time, and construct more robust models.
Jovani Taveira De Souza, Antonio Carlos De Francisco, Dayana Carla De Macedo   +2 more
doaj   +1 more source

Autophagy and mitophagy in pancreatic β‐cell homeostasis and their involvement in diabetes pathophysiology

FEBS Letters, EarlyView.
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, Mingming Tong, Anna L. Gloyn   +2 more
wiley   +1 more source

Formation-Controlled Dimensionality Reduction [PDF]

Dimensionality reduction represents the process of generating a low dimensional representation of high dimensional data. Motivated by the formation control of mobile agents, we propose a nonlinear dynamical system for dimensionality reduction. The system
Jung, Yoon Mo, Jeong, Taeuk, Lee, Euntack   +2 more
core   +3 more sources

Non‐linear dimensionality reduction using fuzzy lattices

IET Computer Vision, 2013
The proposed method is based on extraction of non‐linearity from the nearest neighbourhood elements of image. To detect non‐linearity, relation between the nearest neighbourhood elements of the image, have been expressed in terms of Gaussian membership ...
Rajiv Kapoor, Rashmi Gupta
doaj   +1 more source

Partial depletion of plasminogen activator inhibitor‐1 decreases subcutaneous fat cell hypertrophy and liver cholesterol in high‐fat‐fed female mice

FEBS Letters, EarlyView.
Obesity raises blood levels of PAI‐1, a protein linked to metabolic dysfunction‐associated steatotic liver disease in people with obesity. In female mice fed a high‐fat diet, partially lowering PAI‐1 led to smaller subcutaneous fat cells and lower liver cholesterol, without changing body weight or insulin sensitivity.
Claudia E. Ramirez Bustamante, Robert Sharp, Pradip K. Saha, Elizabeth S. Anaya, Elizabeth L. Lieu, Evelyn L. de Groot, Pooja Patel, Mi Jeong Heo, Aaron R. Cox, Kang Ho Kim, Sean M. Hartig   +10 more
wiley   +1 more source

Morphological mapping for non‐linear dimensionality reduction

IET Computer Vision, 2015
Recently, much research has been carried out on dimensionality reduction techniques that summarise a large set of features into a smaller set, leading to much less redundancy.
Rajiv Kapoor, Rashmi Gupta
doaj   +1 more source

Emerging experimental and computational methods for studying redox‐regulated structural transitions

FEBS Letters, EarlyView.
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, Dana Reichmann, Gábor Erdős   +2 more
wiley   +1 more source

PCA-based dimensionality reduction for face recognition

, 2021
PCA-based dimensionality reduction for face ...
MI Afjal (15370294), MR Islam (9872390), MA Mamun (15370474), MA Marjan (15370279), MD PALASH UDDIN (13098606)   +4 more
core  

Classification, dimensionality reduction, and maximally discriminatory visualization of a multicentre 1H-MRS database of brain tumors [PDF]

, 2008
The combination of an Artificial Neural Network classifier, a feature selection process, and a novel linear dimensionality reduction technique that provides a data projection for visualization and which preserves completely the class discrimination ...
Arús, Carles, Paulo J. G. Lisboa, Julià Sapé, Margarida, Romero Merino, Enrique, Alfredo Vellido, Vellido Alcacena, Alfredo, Enrique Romero, Lisboa, Paulo J.G., Margarida Julià-Sapé, Carles Arús   +9 more
core   +1 more source

Synergistic perspectives—How single‐molecule biophysics complement biochemical understanding

FEBS Letters, EarlyView.
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, Eline L. Jansen, Jorine M. Eeftens   +2 more
wiley   +1 more source