Results 101 to 110 of about 77,177 (314)

Leveraging 3D Molecular Spatial Visual Information and Multi‐Perspective Representations for Drug Discovery

Advanced Science, EarlyView.
A deep learning framework called MolVisGNN is proposed to fuse 3D molecular visual information of drugs with multi‐source features, which proves the importance of 3D molecular visual information of drugs and the advancedness of this model in the field of drug discovery, and provides a reference for how to more comprehensively express small molecule ...
Zimai Zhang, Xi Zhou, Yujie Qi, Xiaobo Zhu, Xun Deng, Feng Tan, Yuan Huang, Lun Hu, Zhuhong You, Pengwei Hu   +9 more
wiley   +1 more source

Leveraging Machine Learning to Analyze Semantic User Interactions in Visual Analytics

Information
In the field of visualization, understanding users’ analytical reasoning is important for evaluating the effectiveness of visualization applications.
Dong Hyun Jeong, Bong Keun Jeong, Soo Yeon Ji   +2 more
doaj   +1 more source

A Visualisation Dashboard for Contested Collective Intelligence Learning Analytics to Improve Sensemaking of Group Discussion

RIED: Revista Iberoamericana de Educación a Distancia, 2019
The skill to take part in and to contribute to debates is important for informal and formal learning. Especially when addressing highly complex issues, it can be difficult to support learners participating in effective group discussion, and to stay ...
Thomas Daniel Ullmann, Anna De Liddo, Michelle Bachler   +2 more
doaj   +1 more source

Geospatial Ontology Development and Semantic Analytics

Transactions in GIS, 2006
Geospatial ontology development and semantic knowledge discovery addresses the need for modeling, analyzing and visualizing multimodal information, and is unique in offering integrated analytics that encompasses spatial, temporal and thematic dimensions of information and knowledge. The comprehensive ability to provide integrated analysis from multiple
Arpinar, I. Budak, Ramakrishnan, Cartic, Azami, Molly, Sheth, Amit P., Usery, E. Lynn, Kwan, Mei-Po   +5 more
openaire   +5 more sources

Structuring visual exploratory analysis of skill demand

, 2018
The analysis of increasingly large and diverse data for meaningful interpretation and question answering is handicapped by human cognitive limitations. Consequently, semi-automatic abstraction of complex data within structured information spaces becomes ...
A.-S. Dadzie, Brooke, Cunningham, Davenport, E.M. Sibarani, Einsfeld, Elia, Ellis, Gehl, Granville, Harper, Heer, Hervás, I. Novalija, Inselberg, Keim, Khobreh, Kulyk, Liu, Munzner, Nielsen, S. Scerri, Sacha, Sibarani, Strawn, Terblanche, Tominski, Turkay, Ware, Welter, Wowczko   +30 more
core   +1 more source

SpaBalance: Balanced Learning for Efficient Spatial Multi‐Omics Decoding

Advanced Science, EarlyView.
SpaBalance is a computational framework that harmonizes multi‐omics learning via gradient equilibrium and dual‐stream feature decomposition, achieving superior clustering accuracy, biological interpretability, and scalable integration of three or more spatial omics modalities.
Yingbo Cui, Yong Zhao, Canqun Yang, Tao Tang, Xiangke Liao, Hongyu Zhang, Huiying Zhao, Zheng Wang, Yuansong Zeng   +8 more
wiley   +1 more source

Semantic Video Analytics Framework using SpinalXNet for Crowd Management in Large Public Events [PDF]

ITM Web of Conferences
In recent years, crowd management (CM) in large public events, such as concerts, sports gatherings, and festivals, has become increasingly critical for ensuring safety and preventing accidents.
P Shreedevi, Mohana H.S., Nazim Abdul Sattar Khalid, Kumar S Pradeep, Dhandayuthapani V Bala   +4 more
doaj   +1 more source

Distributed Semantic Analytics Using the SANSA Stack

, 2017
A major research challenge is to perform scalable analysis of large-scale knowledge graphs to facilitate applications like link prediction, knowledge base completion and reasoning. Analytics methods which exploit expressive structures usually do not scale well to very large knowledge bases, and most analytics approaches which do scale horizontally (i.e.
Jens Lehmann, Simon Bin, Gezim Sejdiu, Ivan Ermilov, Hajira Jabeen, Patrick Westphal, Lorenz Bühmann, Muhammad Saleem, Axel-Cyrille Ngonga Ngomo, Axel-Cyrille Ngonga Ngomo, Claus Stadler, Nilesh Chakraborty   +11 more
openaire   +2 more sources

Knowledge Graph for Methane Selective Conversion: Revisiting and Predicting Product Selectivity and Methane Conversion

Advanced Science, EarlyView.
With the help of large language models, deep neural network learning, and kinetic calculation, a knowledge graph prediction of prior research in methane conversion is conducted. This knowledge graph provides a comprehensive understanding of the relationships among catalyst materials, catalytic performance, and reaction conditions, providing guidance ...
Boyu Xu, Gaoyang Li, Bohan Wang, Jiawei Bian, Hui Pan, Yulin Min, Guodong Qi, Jun Xu, Feng Deng, Feng Ju, Hao Ling, Zhendong Wang   +11 more
wiley   +1 more source

A Forward Genetics Strategy for High‐Throughput Gene Identification via Precise Image‐Based Phenotyping of an Indexed EMS Mutant Library

Advanced Science, EarlyView.
The GeneHunter‐Gene‐Level Association (GH‐GLA) pipeline enables high‐throughput gene identification in an indexed EMS population of wheat cultivar KN9204. It identifies 5905 trait‐associated wheat genes and validates key regulators of kernel weight and spikelet architecture via gene editing and haplotype analysis.
Haojie Wang, Fujun Sun, Zeyu Shi, Yufeng Yang, Yi Ding, Tengteng Zhang, Caihong Zhao, Jingzhong Xie, Yaqian Zhang, Caihua Li, Wenqiang Tang, Junming Li, Xigang Liu, Shusong Zheng, Ni Jiang, Fei He, Shuzhi Zheng   +16 more
wiley   +1 more source