Results 61 to 70 of about 43,712,030 (248)

A Review of Recent Advancement in Integrating Omics Data with Literature Mining towards Biomedical Discoveries

International Journal of Genomics, 2017
In the past decade, the volume of “omics” data generated by the different high-throughput technologies has expanded exponentially. The managing, storing, and analyzing of this big data have been a great challenge for the researchers, especially when ...
Kalpana Raja, Matthew Patrick, Yilin Gao, Desmond Madu, Yuyang Yang, Lam C. Tsoi   +5 more
doaj   +1 more source

Automated Extraction of Multicomponent Alloy Data Using Large Language Models for Sustainable Design

Advanced Science, EarlyView.
A large language model (LLM) based pipeline is developed to automatically extract a comprehensive and accurate multicomponent alloy database from literature corpus. The extracted dataset is integrated with sustainability indicators to identify potential alloys that outperform existing industrial benchmark materials in terms of both performance and ...
Aravindan Kamatchi Sundaram, Mohit Chakraborty, Sai Mani Kumar Devathi, B. Pabitramohan Prusty, Rohit Batra   +4 more
wiley   +1 more source

Ontology-based document representation for biomedical information retrieval [PDF]

, 2007
In the current era of fast sequencing of entire genomes, more data is becoming available for analysis. This data analysis, in turn, leads to an increasing amount of scientfic publications.
Camous, Fabrice
core   +2 more sources

Mechanism‐Informed Language Modeling and Oxygenated 3D Screening Identify Berberine–Enzalutamide Synergy in Prostate Cancer Models

Advanced Science, EarlyView.
By integrating knowledge‐augmented artificial intelligence with an oxygen‐supplemented 3D screening platform, a synergistic interaction between berberine and enzalutamide is identified. The framework integrates compound mechanisms of action with disease‐relevant signaling context to prioritize candidate combinations and generate testable pathway‐based ...
Chih‐Hui Lo, Katie Shi, Lina Kafadarian, Alexandra Bermudez, Johnny Diaz, Liam Edwards, Yunqi Hong, Ziyi Chen, Hyeonji Hwang, Weihong Yan, Alan Levinson, Robert Damoiseaux, Cho‐Jui Hsieh, Tanya Stoyanova, Andrew S. Goldstein, Neil Y.C. Lin   +15 more
wiley   +1 more source

Figure text extraction in biomedical literature. [PDF]

PLoS ONE, 2011
Figures are ubiquitous in biomedical full-text articles, and they represent important biomedical knowledge. However, the sheer volume of biomedical publications has made it necessary to develop computational approaches for accessing figures.
Daehyun Kim, Hong Yu
doaj   +1 more source

Evolution of Physical Intelligence Across Scales

Advanced Intelligent Discovery, EarlyView.
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu, Tianyun Huang, Aming Li, Pengyu Lv, Tingting Qin, Wenhui Chen, Hui Wei, Huiling Duan   +7 more
wiley   +1 more source

Effective use of Latent Semantic Indexing and Computational Linguistics in Biological and Biomedical Applications

Frontiers in Physiology, 2013
Text mining is rapidly becoming an essential technique for the annotation and analysis of large biological data sets. Biomedical literature currently increases at a rate of several thousand papers per week, making automated information retrieval methods ...
Hongyu eChen, Bronwen eMartin, Caitlin M Daimon, Stuart eMaudsley   +3 more
doaj   +1 more source

Automating AI Discovery for Biomedicine Through Knowledge Graphs and Large Language Models Agents

Advanced Intelligent Discovery, EarlyView.
This work proposes a novel framework that automates biomedical discovery by integrating knowledge graphs with multiagent large language models. A biologically aligned graph exploration strategy identifies hidden pathways between biomedical entities, and specialized agents use this pathway to iteratively design AI predictors and wet‐lab validation ...
Naafey Aamer, Muhammad Nabeel Asim, Shan Munir, Andreas Dengel   +3 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

Cell Segmentation Beyond 2D—A Review of the State‐of‐the‐Art

Advanced Intelligent Discovery, EarlyView.
Cell segmentation underpins many biological image analysis tasks, yet most deep learning methods remain limited to 2D despite the inherently 3D nature of cellular processes. This review surveys segmentation approaches beyond 2D, comparing 2.5D and fully 3D methods, analyzing 31 models and 32 volumetric datasets, and introducing a unified reference ...
Fabian Schmeisser, Haseeb Muhammad, Junaid Younas, Gillian Lovell, Bianca Migliori, Andreas Dengel, Sheraz Ahmed   +6 more
wiley   +1 more source