Results 51 to 60 of about 595,263 (265)

Deep learning in bioinformatics

Turkish Journal of Biology, 2023
Deep learning is a powerful machine learning technique that can learn from large amounts of data using multiple layers of artificial neural networks. This paper reviews some applications of deep learning in bioinformatics, a field that deals with analyzing and interpreting biological data. We first introduce the basic concepts of deep learning and then
YOUSEF, Malik, ALLMER, Jens
openaire   +2 more sources

Microbiome‐blood–brain barrier interactions in aging — mechanisms and therapeutic potential

FEBS Letters, EarlyView.
Aging reshapes the gut microbiome (↓SCFA‐producing commensals; ↑pro‐inflammatory outputs), shifting circulating metabolites (↓SCFAs; ↑LPS, ↑TMAO, ↑PAA) that act at the BBB to increase nonspecific transcytosis, alter transport, and promote astrocyte reactivity, heightening brain vulnerability.
Daniel Cuervo‐Zanatta, Hari Baskar Balasubramanian, Amir Pasokh, Marietta Zille   +3 more
wiley   +1 more source

Improved multiscale attention based deep learning approach for automated sugarcane leaf disease detection using BSRI data

Scientific Reports
Early and accurate detection of sugarcane leaf diseases is critical for improving crop productivity and reducing economic losses in the agricultural sector.  Timely interventions enable sustainable crop management and better resource use.
Jannatul Mauya, Ruhul Amin, Md. Imam Hossain, Sabba Ruhi, Md. Shamim Reza   +4 more
doaj   +1 more source

Structure‐forward targeting of claudins with synthetic binders

FEBS Letters, EarlyView.
Claudins form the paracellular barriers between epithelial and endothelial tissues at tight junctions and are targets for molecular binders with the goal of modulating barrier permeability. Claudin‐binding molecules are relevant in drug delivery or in altering claudin interactions with disease‐causing proteins.
Alex J. Vecchio
wiley   +1 more source

Deep Learning With DAGs

SSRN Electronic Journal
Social science theories often postulate systems of causal relationships among variables, which are commonly represented using directed acyclic graphs (DAGs). As non-parametric causal models, DAGs require no assumptions about the functional form of the hypothesized relationships.
Sourabh Balgi, Adel Daoud, Jose M. Peña, Geoffrey T. Wodtke, Jesse Zhou   +4 more
openaire   +3 more sources

Development of a Japanese polygenic risk score model for amyloid-β PET imaging in Alzheimer’s disease

Alzheimer’s Research & Therapy
Background The use of polygenic risk scores (PRS) for predicting disease risk in Japanese populations, particularly for dementia and related phenotypes, remains markedly unexplored.
Misato Kaishima, Junichi Ito, Kentaro Takahashi, Kenji Tai, Junro Kuromitsu, Shogyoku Bun, Daisuke Ito   +6 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

Deep learning for genomics [PDF]

Nature Genetics, 2018
Application of deep learning to genomic datasets is an exciting area that is rapidly developing and is primed to revolutionize genome analysis. We embrace the potential that deep learning holds for understanding genome biology, and we encourage further advances in this area, extending to all aspects of genomics research.
openaire   +2 more sources

Identification and characterization of intracerebral hemorrhage events in elderly veterans with alzheimer’s disease in the veterans affairs healthcare system

Scientific Reports
Cerebral amyloid angiopathy (CAA) and hypertensive (HTN) small vessel disease are causes of spontaneous intracerebral hemorrhage (ICH). We identified ICH rates in patients with all-cause mild cognitive impairment (MCI) or Alzheimer’s disease (AD), and ...
Peter J. Morin, Vanesa C. Andreu Arasa, Ying Wang, Joel Reisman, Dan Berlowitz, Wen Hu, Raymond Zhang, Babak Haji, Ran Gao, Amir Abbas Tahami Monfared, Quanwu Zhang, Weiming Xia   +11 more
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