Results 201 to 210 of about 43,440 (267)

A comparison of machine learning and Bayesian modelling for molecular serotyping. [PDF]

BMC Genomics, 2017
Newton R, Wernisch L.
europepmc   +1 more source

Livestock Multi‐Omics Integration: A Systematic Framework From Statistical Association to Causal Interpretation

Advanced Science, EarlyView.
A three‐tier livestock multi‐omics framework resolves four typical analytical pitfalls. Moving from statistical association through machine learning preprocessing to triple‐modal causal inference, it converts omics results into genomic selection and gene editing strategies to achieve One Health, underpinned by multi‐omics data, multimodal sequencing ...
Jiying Wen, Zhongyu Wang, Jieping Huang, Fen Li, Ningbo Chen, Yun Ma   +5 more
wiley   +1 more source

Canonical Antibodies Adopt Distinct Binding Modes to Recognize Viral Glycan Shields

Advanced Science, EarlyView.
Canonical Y‐shaped antibodies recognize viral glycan shields through adaptive Fab assembly states shaped by glycan organization and somatic hypermutation. Structural analyses ofbroadly neutralizing antibodies VRC35 and VRC36 across glycoproteins of HIV‐1, influenza, SARS‐CoV‐2, and Lassa viruses reveal distinct Fab assembly states, spanning monovalent,
Jiaxuan Cheng, Evan M. Cale, Amirabbas Maghsoudi, Matthew S. Sutton, Nancy S. Longo, Rebecca A. Gillespie, Lingshu Wang, Ivan Kosik, Sue Chong, Atsuhiro Yasuhara, Tatsiana Bylund, Arne Schön, Prabhanshu Tripathi, Yaroslav Tsybovsky, Haotian Lei, Nicholas C. Morano, Allison B. Lupatkin, Abraham J. Morton, Zabrina C. Lang, Jordan E. Becker, Isabella R. Frascilla, Myungjin Lee, Ning Li, Cuiping Liu, Ryan S. Roark, Chen‐Hsiang Shen, I‐Ting Teng, David J. Van Wazer, Danyi Wang, Lingyuan Wu, Goran Ahlsen, Mike Castro, Haijuan Du, Michael J. Ernandes, Tiansheng Li, Bob C. Lin, Mark K. Louder, Krisha McKee, Jonah S. Merriam, Sijy O'Dell, Li Ou, Sergei Pletnev, David Prikryl, Qi Qiu, Sarah Rubin, Mallika Sastry, Stephen D. Schmidt, Asif Shajahan, Andrea R. Shiakolas, Sanjay Srivatsan, Baoshan Zhang, Qiong Zhou, Mark Connors, Jason G. Gall, Yicheng Guo, Rick K. Huang, Yaoxing Huang, Richard A. Koup, Q. Paula Lei, John R. Mascola, Reda Rawi, Leonid Serebryannyy, Lawrence Shapiro, Zizhang Sheng, David D. Ho, Patrick C. Wilson, Jonathan W. Yewdell, Theodore C. Pierson, Masaru Kanekiyo, Nicole A. Doria‐Rose, Peter D. Kwong, Tongqing Zhou   +71 more
wiley   +1 more source

Bayesian Modelling of Induced Responses and Neuronal Rhythms. [PDF]

Brain Topogr, 2019
Pinotsis DA, Loonis R, Bastos AM, Miller EK, Friston KJ.   +4 more
europepmc   +1 more source

Unveiling the Uncharted Potential of 2D Materials in Li/Na–S Batteries: A Paradigm Shift From Graphene

Advanced Science, EarlyView.
This review explores emerging 2D materials beyond graphene, including graphdiyne, phosphorene, borophene, siloxene, MBene, antimonene, and germanene for Li/Na–S batteries. It analyzes their roles as sulfur hosts, metallic anode protectors, separators, and electrolyte fillers, emphasizing polysulfide suppression, dendrite inhibition, and interfacial ...
Naveen Kumar T. R, Xuebing Zhu, Yao‐Jie Lei, Lei Zhang, Hua Kun Liu, Weihong Lai, Guoxiu Wang, Yun‐Xiao Wang   +7 more
wiley   +1 more source

Bowhead: Bayesian modelling of cell velocity during concerted cell migration. [PDF]

PLoS Comput Biol, 2018
Engel M, Longden J, Ferkinghoff-Borg J, Robin X, Saginc G, Linding R.   +5 more
europepmc   +1 more source

Terahertz Channel Modeling, Estimation and Localization in RIS‐Assisted Systems

Advanced Electronic Materials, EarlyView.
Reconfigurable intelligent surfaces have become a recent intensive research focus. Based on practical applications, channel strategies for RIS‐assisted terahertz wireless communication systems are categorized into three different types: channel modeling, channel estimation, and channel localization.
Hongjing Wang, Weipeng Wang, Xuan Cong, Shiyu Wang, Gao Li, Sen Gong, Lin Huang, Hongxin Zeng, Yaxin Zhang, Ziqiang Yang   +9 more
wiley   +1 more source

Emerging Memory and Device Technologies for Hardware‐Accelerated Model Training and Inference

Advanced Electronic Materials, EarlyView.
This review investigates the suitability of various emerging memory technologies as compute‐in‐memory hardware for artificial intelligence (AI) applications. Distinct requirements for training‐ and inference‐centric computing are discussed, spanning device physics, materials, and system integration.
Yoonho Cho, Dae‐won Kim, Yujin Kim, Jung‐Heum Na, Yuwon Jeong, Dong‐Yeop Lee, Shinhyun Choi   +6 more
wiley   +1 more source

Bayesian modelling of a hepatitis A outbreak in men who have sex with men in Sydney, Australia, 1991/1992. [PDF]

Epidemiol Infect, 2019
Zhang XS, Charlett A.
europepmc   +1 more source