Results 101 to 110 of about 212,260 (313)

ZNF33B Promotes Japanese Encephalitis Virus Infection by Regulating the Stability of M6A‐Modified Trim25 to Control the Autophagy Process

Advanced Science, EarlyView.
Upon JEV infection, ZNF33B recruits METTL14 to stabilize the METTL3‐METTL14 m6A methyltransferase complex, leading to increased m6A modification of host transcripts, including Trim25 mRNA. ZNF33B selectively binds m6A‐modified sites on Trim25 mRNA and accelerates its decay, resulting in reduced TRIM25 protein abundance.
Jian Du, Chunwei Li, Jiyuan Luo, Huizhi Zhang, Jinyan Zhang, Suya Wang, Huanchun Chen, Hongli Xu, Xiangmin Li, Ping Qian   +9 more
wiley   +1 more source

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity

, 2016
Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods.
Lin Tao (4236), Yu Zong Chen (113383), Zhe Chen (196097), Cheng Zhang (70708), Xiao Feng Li (304777), Shuang Li (146392), Xian Zeng (451364), Feng Zhu (685), Jing Yu Xu (2951868), Peng Zhang (2071), Chu Qin (115759), Ying Hong Li (2951862), Shang Ying Chen (2951865)   +12 more
core   +1 more source

Study on the Influence of Emotion and Fatigue on Cognitive Function During Simulated Flight Based on ERP Technology

Journal of Integrative Neuroscience
Background: Pilots often experience mental fatigue during task performance, accompanied by fluctuations in positive (e.g., joy) and negative (e.g., tension) emotions.
Ruikai Zhao, Pengyan Zhou, Jinhan Liu, Yixuan Guan, Jiacheng Qian, Jiayi Bao   +5 more
doaj   +1 more source

Identification of novel CDK2 inhibitors by a multistage virtual screening method based on SVM, pharmacophore and docking model

Journal of Enzyme Inhibition and Medicinal Chemistry, 2020
Cyclin-dependent kinase 2 (CDK2) is the family of Ser/Thr protein kinases that has emerged as a highly selective with low toxic cancer therapy target. A multistage virtual screening method combined by SVM, protein-ligand interaction fingerprints (PLIF ...
Jing-Wei Liang, Ming-Yang Wang, Shan Wang, Shi-Long Li, Wan-Qiu Li, Fan-Hao Meng   +5 more
doaj   +1 more source

Real‐Time and Non‐Invasive Detection of Respiratory Viral Infections Using an Intelligent Odor Monitoring System (IOMS)

Advanced Science, EarlyView.
An intelligent odor monitoring system integrates an IVC animal model, gas sensor array, real‐time resistance readout, and machine‐learning analysis to continuously monitor infection‐associated odor changes. The platform captures longitudinal sensor responses, distinguishes infected from healthy states, and supports early‐stage respiratory viral ...
Yajie Shen, Weifeng Yuan, Long Li, Yucheng Zheng, Kenan Liu, Hegeng Li, Hua‐Yao Li, Yongliang Zhao, Binzhou Ying, Lanpeng Guo, Wenjian Zhang, Shu‐Ming Kuo, Zirui Zhang, Yufan Deng, Bohan Yin, Zhaocheng Luo, Ke Xu, Huan Liu   +17 more
wiley   +1 more source

Least 1-Norm SVMs: a new SVM variant between standard and LS-SVMs [PDF]

, 2010
This is an electronic version of the paper presented at the 18th European Symposium on Artificial Neural Networks, held in Bruges on 2010 Least Squares Support Vector Machines (LS-SVMs) were proposed by replacing the inequality constraints inherent to L1-SVMs with equality constraints. So far this idea has only been suggested for a least
Jorge López Lázaro, José R. Dorronsoro   +1 more
openaire   +1 more source

Selecting Features with SVM [PDF]

, 2013
A common problem with feature selection is to establish how many features should be retained at least so that important information is not lost. We describe a method for choosing this number that makes use of Support Vector Machines. The method is based on controlling an angle by which the decision hyperplane is tilt due to feature selection ...
Jacek Rzeniewicz, Julian Szymanski
openaire   +1 more source

Prediction of Structural Stability of Layered Oxide Cathode Materials: Combination of Machine Learning and Ab Initio Thermodynamics

Advanced Energy Materials, EarlyView.
In this work, we developed a phase‐stability predictor by combining machine learning and ab initio thermodynamics approaches, and identified the key factors determining the favorable phase for a given composition. Specifically, a lower TM ionic potential, higher Na content, and higher mixing entropy favor the O3 phase.
Liang‐Ting Wu, Milica Zdravković, Dijana Milosavljević, Konstantin Köster, Olivier Guillon, Jyh‐Chiang Jiang, Payam Kaghazchi   +6 more
wiley   +1 more source

Parallelizing support vector machines for scalable image annotation

, 2011
This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Machine learning techniques have facilitated image retrieval by automatically classifying and annotating images with keywords.
Alham, Nasullah Khalid
core  

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source