Results 61 to 70 of about 1,216,046 (262)

A network approach for low dimensional signatures from high throughput data

Scientific Reports, 2022
One of the main objectives of high-throughput genomics studies is to obtain a low-dimensional set of observables—a signature—for sample classification purposes (diagnosis, prognosis, stratification).
Nico Curti, Giuseppe Levi, Enrico Giampieri, Gastone Castellani, Daniel Remondini   +4 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

K-means clustering based filter feature selection on high dimensional data

IJAIN (International Journal of Advances in Intelligent Informatics), 2016
With hundreds or thousands of features in high dimensional data, computational workload is challenging. In classification process, features which do not contribute significantly to prediction of classes, add to the computational workload.
Dewi Pramudi Ismi, Shireen Panchoo, Murinto Murinto   +2 more
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

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

Low-dimensional embeddings of high-dimensional data

CoRR
Large collections of high-dimensional data have become nearly ubiquitous across many academic fields and application domains, ranging from biology to the humanities. Since working directly with high-dimensional data poses challenges, the demand for algorithms that create low-dimensional representations, or embeddings, for data visualization ...
Cyril de Bodt, Alex Diaz-Papkovich, Michael Bleher, Kerstin Bunte, Corinna Coupette, Sebastian Damrich, Enrique Fita Sanmartin, Fred A. Hamprecht, Emoke-Ágnes Horvát, Dhruv Kohli, Smita Krishnaswamy, John A. Lee 0001, Boudewijn P. F. Lelieveldt, Leland McInnes, Ian T. Nabney, Maximilian Noichl, Pavlin G. Policar, Bastian Rieck, Guy Wolf, Gal Mishne, Dmitry Kobak   +20 more
openaire   +5 more sources

Fitting High-Dimensional Copulae to Data [PDF]

, 2011
This paper make an overview of the copula theory from a practical side. We consider different methods of copula estimation and different Goodness-of-Fit tests for model selection. In the GoF section we apply Kolmogorov-Smirnov and Cramer-von-Mises type tests and calculate power of these tests under different assumptions.
openaire   +4 more sources

High-dimensional data

Journal of the National Science Foundation of Sri Lanka, 2016
This paper provides a brief introduction to high-dimensional data, a form of ‘Big Data’, and gives an overview of several data analysis concepts and techniques that could be used to explore and analyse such data. An example that involves genomics data from several Sri Lankan and United Kingdom oral cancer patients is used to illustrate the methods.
Dhammika Amaratunga, Javier Cabrera
openaire   +2 more sources

Dual Query: Practical Private Query Release for High Dimensional Data

The Journal of Privacy and Confidentiality, 2017
We present a practical, differentially private algorithm for answering a large number of queries on high dimensional datasets. Like all algorithms for this task, ours necessarily has worst-case complexity exponential in the dimension of the data. However,
Marco Gaboardi, Emilio Jesús Gallego Arias, Justin Hsu, Aaron Roth, Zhiwei Steven Wu   +4 more
doaj   +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