Results 201 to 210 of about 5,698,498 (295)

A Small Sample Recognition Model for Poisonous and Edible Mushrooms based on Graph Convolutional Neural Network. [PDF]

Comput Intell Neurosci, 2022
Zhu L, Pan X, Wang X, Haito F.
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

MLGCN-Driver: a cancer driver gene identification method based on multi-layer graph convolutional neural network. [PDF]

BMC Bioinformatics
Wei PJ, Zhou J, Cao RF, Ding Y, Yue Z, Zheng CH.   +5 more
europepmc   +1 more source

LABAMPsGCN: A framework for identifying lactic acid bacteria antimicrobial peptides based on graph convolutional neural network. [PDF]

Front Genet, 2022
Sun TJ, Bu HL, Yan X, Sun ZH, Zha MS, Dong GF.   +5 more
europepmc   +1 more source

AS‐pHopt: An Optimal pH Prediction Model Enhanced by Active Site of Enzymes

Advanced Intelligent Discovery, EarlyView.
To address the low accuracy of enzyme optimal pH (pHopt) prediction, this study develops active site‐based pHopt (AS‐pHopt), a prediction model enhanced by active site information and pseudo‐label prediction. Integrating key structural and physicochemical features affecting enzyme pHopt, AS‐pHopt uses Evolutionary Scale Modeling (ESM)‐2 with active ...
Wenxiang Song, Xinmin Li, Hongbo Yu, Le Xiong, Guixia Liu, Weihua Li, Yun Tang   +6 more
wiley   +1 more source

Graph Convolutional Neural Network-Enabled Frontier Molecular Orbital Prediction: A Case Study with Neurotransmitters and Antidepressants. [PDF]

J Chem Inf Model
Monsia R, Gundry SC, Mohr ML, Smith MA, Bhattacharyya S, Hati S.   +5 more
europepmc   +1 more source

Spatial Attention-Based 3D Graph Convolutional Neural Network for Sign Language Recognition. [PDF]

Sensors (Basel), 2022
Al-Hammadi M, Bencherif MA, Alsulaiman M, Muhammad G, Mekhtiche MA, Abdul W, Alohali YA, Alrayes TS, Mathkour H, Faisal M, Algabri M, Altaheri H, Alfakih T, Ghaleb H.   +13 more
europepmc   +1 more source

Deep Learning–Based Extraction of Promising Material Groups and Common Features from High‐Dimensional Data: A Case of Optical Spectra of Inorganic Crystals

Advanced Intelligent Discovery, EarlyView.
We report a novel interpretation method for deep learning models based on feature extraction and clustering. Applying this method to an atomistic line graph neural network (ALIGNN) model trained on optical absorption spectra of 2,681 inorganic compounds obtained from first‐principles calculations, we successfully identify key factors underlying ...
Akira Takahashi, Yu Kumagai, Arata Takamatsu, Fumiyasu Oba   +3 more
wiley   +1 more source

Schizophrenia recognition based on three-dimensional adaptive graph convolutional neural network. [PDF]

Sci Rep
Yin G, Yuan J, Chen Y, Guo G, Shi D, Wang L, Zhao Z, Zhao Y, Zhang M, Dong Y, Wang B, Tan S.   +11 more
europepmc   +1 more source

A survey of field programmable gate array (FPGA)-based graph convolutional neural network accelerators: challenges and opportunities. [PDF]

PeerJ Comput Sci, 2022
Li S, Tao Y, Tang E, Xie T, Chen R.
europepmc   +1 more source