Results 171 to 180 of about 157,658 (286)

Biomedical text mining for research rigor and integrity: tasks, challenges, directions. [PDF]

Brief Bioinform, 2018
Kilicoglu H.
europepmc   +1 more source

Computational analysis to assess hemodynamic forces in descending thoracic aortic aneurysms

The Journal of Physiology, EarlyView.
Abstract figure legend Left: Pre‐processing. First, we perform the segmentation of the Computer Tomography angiorgraphy (angio‐CT) scans of a healthy patient, obtaining the surface of a healthy thoracic aorta with a Type III aortic arch. Then, we build nine ideal configurations with Descending Thoracic Aortic Aneurysm (DTAA), varying the aortic arch ...
Francesca Duca, Daniele Bissacco, Luca Crugnola, Chiara Faitini, Maurizio Domanin, Francesco Migliavacca, Santi Trimarchi, Christian Vergara   +7 more
wiley   +1 more source

Applications of large‐scale artificial intelligence models in bioinformatics

Quantitative Biology, Volume 14, Issue 2, June 2026.
Abstract Large‐scale artificial intelligence (AI) models can mine potential patterns from massive amounts of data and provide more accurate analyses. This capability has enabled its gradual application in various areas of bioinformatics. However, few reviews have comprehensively summarized the applications of different types of large‐scale AI models in
Mingjing Li, Qichen Shang, Ziyang Dong, Zhixuan You, Le Zhang, Ming Xiao   +5 more
wiley   +1 more source

Large language models for bioinformatics

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract With the rapid advancements in large language model technology and the emergence of bioinformatics‐specific language models (BioLMs), there is a growing need for a comprehensive analysis of the current landscape, computational characteristics, and diverse applications.
Wei Ruan, Yanjun Lyu, Jing Zhang, Jiazhang Cai, Peng Shu, Yang Ge, Yao Lu, Shang Gao, Yue Wang, Peilong Wang, Lin Zhao, Tao Wang, Yufang Liu, Luyang Fang, Ziyu Liu, Zhengliang Liu, Yiwei Li, Zihao Wu, Junhao Chen, Hanqi Jiang, Yi Pan, Zhenyuan Yang, Jingyuan Chen, Shizhe Liang, Wei Zhang, Terry Ma, Yuan Dou, Jianli Zhang, Xinyu Gong, Qi Gan, Yusong Zou, Zebang Chen, Yuanxin Qian, Shuo Yu, Jin Lu, Kenan Song, Xianqiao Wang, Andrea Sikora, Gang Li, Xiang Li, Quanzheng Li, Yingfeng Wang, Lu Zhang, Yohannes Abate, Lifang He, Wenxuan Zhong, Rongjie Liu, Chao Huang, Wei Liu, Ye Shen, Ping Ma, Hongtu Zhu, Yajun Yan, Dajiang Zhu, Tianming Liu   +54 more
wiley   +1 more source

MFCN‐DDI: Capsule network based on multimodal feature for multitype drug–drug interaction prediction

Quantitative Biology, Volume 14, Issue 1, March 2026.
Abstract Precise prediction of drug–drug interactions (DDIs) is essential for pharmaceutical research and clinical applications to minimize adverse reactions, optimize therapies, and reduce costs. However, existing methods still face challenges in effectively integrating multidimensional drug features and fully utilizing edge features in molecular ...
Jiayi Lu, Yingying Jiang, Yuhan Fu, Mengdi Nan, Qing Ren, Jie Gao   +5 more
wiley   +1 more source

Edge Computing in Healthcare Using Machine Learning: A Systematic Literature Review

WIREs Data Mining and Knowledge Discovery, Volume 16, Issue 1, March 2026.
Three key parts of our review. This review examines recent research on integrating machine learning with edge computing in healthcare. It is structured around three key parts: the demographic characteristics of the selected studies; the themes, tools, motivations, and data sources; and the key limitations, challenges, and future research directions ...
Amir Mashmool, Giorgio Delzanno, Hamid Saadatfar, Aakash Ahmad, Rainer Koschke, Roohallah Alizadehsani, U. Rajendra Acharya, Daniele D'Agostino   +7 more
wiley   +1 more source

Making the Old New Again Through the Process of Recombinant Innovation

Journal of Product Innovation Management, Volume 43, Issue 2, Page 290-312, March 2026.
ABSTRACT Academic Summary Recombinant innovation—the process through which atypical and unexpected combinations of knowledge generate novel outcomes—is a critical driver of organizational distinctiveness and market transformation. While prior research has focused on firm‐ and industry‐level mechanisms, less attention has been given to multilevel ...
Vittoria Magrelli, Josip Kotlar, Alfredo De Massis, Federico Frattini, Antonio Messeni Petruzzelli   +4 more
wiley   +1 more source

Deformation Prediction of 4D‐Printed Active Composite Structures Based on Data Mining

Advanced Science, Volume 13, Issue 7, 3 February 2026.
A curvature‐driven sequence point generation (CSPG) algorithm based on data mining is proposed to predict the deformation of double‐layer voxelized composite structures of arbitrary lengths. In addition, the CSPG algorithm is applied to predict the deformation of 2D and 3D structures assembled from beam elements, and its effectiveness is validated ...
Mengtao Wang, Yifan Xu, Zaiyang Liu, Hidemitsu Furukawa, Zhongkui Wang, Ren Xu, Lin Meng   +6 more
wiley   +1 more source

Development of Dimethylsulfonium Probes for Broad Profiling of Methyllysine Reader Proteins

Advanced Science, Volume 13, Issue 9, 13 February 2026.
Development of oligoglycine‐based dimethylsulfonium probes for unbiased crosslinking to methyllysine readers. The general probe facilitates profiling of site‐specific methyllysine readers, evaluation of selectivity and activity of reader inhibitors, and global profiling of methyllysine readers.
Jinyu Yang, Yihang Xiao, Yingxiao Gao, Mingxuan Wu   +3 more
wiley   +1 more source

Named Entity Recognition Models for Machine Learning Interatomic Potentials: A User‐Centric Approach to Knowledge Extraction from Scientific Literature

Advanced Intelligent Discovery, Volume 2, Issue 1, February 2026.
Named entity recognition pipeline for knowledge extraction from scientific literature. Machine learning interatomic potential (MLIP) is an emerging technique that has helped achieve molecular dynamics simulations with unprecedented balance between efficiency and accuracy. Recently, the body of MLIP literature has been growing rapidly, which propels the
Bowen Zheng, Grace X. Gu
wiley   +1 more source