Results 61 to 70 of about 9,277,012 (302)

Molecular bases of circadian magnesium rhythms across eukaryotes

FEBS Letters, EarlyView.
Circadian rhythms in intracellular [Mg2+] exist across eukaryotic kingdoms. Central roles for Mg2+ in metabolism suggest that Mg2+ rhythms could regulate daily cellular energy and metabolism. In this Perspective paper, we propose that ancestral prokaryotic transport proteins could be responsible for mediating Mg2+ rhythms and posit a feedback model ...
Helen K. Feord, Gerben van Ooijen
wiley   +1 more source

Data‐driven discovery of gene expression markers distinguishing pediatric acute lymphoblastic leukemia subtypes

Molecular Oncology, EarlyView.
This study investigates gene expression differences between two major pediatric acute lymphoblastic leukemia (ALL) subtypes, B‐cell precursor ALL, and T‐cell ALL, using a data‐driven approach consisting of biostatistics and machine learning methods. Following analysis of a discovery dataset, we find a set of 14 expression markers differentiating the ...
Mona Nourbakhsh, Nikola Tom, Anna Schrøder Lassen, Helene Brasch Lind Petersen, Ulrik Kristoffer Stoltze, Karin Wadt, Kjeld Schmiegelow, Matteo Tiberti, Elena Papaleo   +8 more
wiley   +1 more source

Neural Network Operations and Susuki-Trotter evolution of Neural Network States

, 2018
It was recently proposed to leverage the representational power of artificial neural networks, in particular Restricted Boltzmann Machines, in order to model complex quantum states of many-body systems [Science, 355(6325), 2017].
Dunjko, Vedran, Freitas, Nahuel, Morigi, Giovanna   +2 more
core   +1 more source

Machine learning for identifying liver and pancreas cancers through comprehensive serum glycopeptide spectra analysis: a case‐control study

Molecular Oncology, EarlyView.
This study presents a novel AI‐based diagnostic approach—comprehensive serum glycopeptide spectra analysis (CSGSA)—that integrates tumor markers and enriched glycopeptides from serum. Using a neural network model, this method accurately distinguishes liver and pancreatic cancers from healthy individuals.
Motoyuki Kohjima, Yuko Takami, Ken Kawabe, Kazuhiro Tanabe, Chihiro Hayashi, Mikio Mikami, Tetsuya Kusumoto   +6 more
wiley   +1 more source

Using Burstiness for Network Applications Classification

Journal of Computer Networks and Communications, 2019
Network traffic classification is a vital task for service operators, network engineers, and security specialists to manage network traffic, design networks, and detect threats.
Hussein Oudah, Bogdan Ghita, Taimur Bakhshi, Abdulrahman Alruban, David J. Walker   +4 more
doaj   +1 more source

Prediction of battery charging process based on aggregation neural network

The Journal of Engineering, 2022
An online sequence extreme learning machine neural network prediction model based on sample aggregation method (AOSELM) is proposed, which is used to solve the prediction of the charging process of lead‐acid batteries.
Shuo Sun, Jun‐zhong Sun, Zhan‐lu Yang, Zhi‐yong Zhou, Yi‐yang Ding   +4 more
doaj   +1 more source

Two phase learning technique in modular neural network for pattern classification of handwritten Hindi alphabets

Machine Learning with Applications, 2021
Modular neural network overcomes the problem of monolithic structures of artificial neural networks. Generally modular neural network is an integration of smaller sub complete neural network models.
Manu Pratap Singh, Gunjan Singh
doaj   +1 more source

Decrypting cancer's spatial code: from single cells to tissue niches

Molecular Oncology, EarlyView.
Spatial transcriptomics maps gene activity across tissues, offering powerful insights into how cancer cells are organised, switch states and interact with their surroundings. This review outlines emerging computational, artificial intelligence (AI) and geospatial approaches to define cell states, uncover tumour niches and integrate spatial data with ...
Cenk Celik, Shi Pan, Eloise Withnell, Hou Wang Lam, Maria Secrier   +4 more
wiley   +1 more source

A data mining approach using cortical thickness for diagnosis and characterization of essential tremor

Scientific Reports, 2017
Essential tremor (ET) is one of the most prevalent movement disorders. Being that it is a common disorder, its diagnosis is considered routine. However, misdiagnoses may occur regularly.
J. Ignacio Serrano, Juan P. Romero, Ma Dolores del Castillo, Eduardo Rocon, Elan D. Louis, Julián Benito-León   +5 more
doaj   +1 more source

Active intellectual property protection for deep neural networks through stealthy backdoor and users’ identities authentication [PDF]

, 2022
Mingfu Xue, Shichang Sun, Yushu Zhang, Jian Wang, Weiqiang Liu   +4 more
openalex   +1 more source