Results 41 to 50 of about 15,514 (261)

Genetic Diagnosis and Discovery Enabled by Large Language Models

Advanced Science, EarlyView.
We demonstrate that large language models (LLMs) can facilitate genetic diagnosis and discovery. LLMs were used to solve four types of genetic problems of sequentially increased complexity. An LLM‐based pipeline could analyze genetic variants in the genomic sequences of human hearing loss or rare genetic disease patients and assist in identifying ...
Tao Tu, Khaled Saab, Weida Liu, Zhouqing Fang, Zhuanfen Cheng, Svetolik Spasic, Maja Djurisic, Hiroaki Mohri, Wenlong Ren, Anil Palepu, Juraj Gottweis, Alan Karthikesalingam, Kavita Kulkarni, Annalisa Pawlosky, Devon Bonner, Elijah Kravets, Shruti Marwaha, Hector R. Mendez, Matthew T. Wheeler, Jonathan A. Bernstein, Undiagnosed Diseases Network, Cheng‐Yu Tsai, Chen‐Chi Wu, Konstantina M. Stankovic, Vivek Natarajan, Gary Peltz   +25 more
wiley   +1 more source

Ontology patterns for the representation of quality changes of cells in time

Journal of Biomedical Semantics, 2019
Background Cell tracking experiments, based on time-lapse microscopy, have become an important tool in biomedical research. The goal is the reconstruction of cell migration patterns, shape and state changes, and, comprehensive genealogical information ...
Patryk Burek, Nico Scherf, Heinrich Herre   +2 more
doaj   +1 more source

MicrobeDiscover: A Knowledge Graph–Enabled AI Framework for Identifying Microbes for Inorganic Nanomaterial Biosynthesis

Advanced Science, EarlyView.
Microbial synthesis of nanomaterials (NMs) is eco‐friendly, but the screening of microorganisms is limited by inefficient traditional methods (currently only involving∽400 microorganisms/90 NMs). We propose AI framework MicrobeDiscover, integrating a knowledge graph of microbe‐NM interactions.
Ludi Wang, Hexing Han, Yufeng Liu, Zhiyuan Ning, Yujie Ma, Haidan Wang, Jinling Xu, Qiansheng Huang, Wenjuan Cui, Yuanchun Zhou, Yang Gao, Bin Wang, Yi Du   +12 more
wiley   +1 more source

Web Ontology Language (OWL)

, 2014
Web Ontology Language (OWL) is a core world wide web consortium [W3C] standard Knowledge representation language for the Semantic Web.
Sengupta, Kunal, Hitzler, Pascal
openaire   +2 more sources

Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy

Advanced Science, EarlyView.
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu, Mengtao Sun, Lusheng Li, Jieqiong Wang, Shibiao Wan   +4 more
wiley   +1 more source

Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model

Advanced Science, EarlyView.
Understanding protein sequence–function relationships remains challenging due to poorly defined motifs and limited residue‐level annotations. An annotation‐agnostic framework is introduced that segments protein sequences into “protein words” using attention patterns from protein language models.
Hedi Chen, Jingrui Zhong, Xiaochun Zhang, Jingke Chen, Lin Guo, Xiaoliang Xiong, Xiaonan Zhang, Xiangyu Liu, Bailong Xiao, Boxue Tian   +9 more
wiley   +1 more source

Research on the Rough Extension of Ontology Description Language of SWRL

Journal of Electrical and Computer Engineering, 2016
Although ontology has strong ability to express knowledge, it is difficult to express uncertain or imprecise information using the language of ontology. In order to improve the ability to express uncertain information, this paper extends the Semantic Web
Xian-kun Zhang, Xin-ya Gao, Qian Zhang, Jia Jia   +3 more
doaj   +1 more source

SDQO AND SFO, ONTOLOGIES FOR SPATIAL DATA QUALITY ASSESSMENT [PDF]

The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2019
Spatial quality assessment is based on the conformance of data to its specifications or fitness for users’ purpose. These specifications and the users’ purposes include the rules and constraints that a dataset should comply with. Assessing the compliance
C. Yilmaz, C. Comert, D. Yildirim
doaj   +1 more source

Multimodal Wearable Biosensing Meets Multidomain AI: A Pathway to Decentralized Healthcare

Advanced Science, EarlyView.
Multimodal biosensing meets multidomain AI. Wearable biosensors capture complementary biochemical and physiological signals, while cross‐device, population‐aware learning aligns noisy, heterogeneous streams. This Review distills key sensing modalities, fusion and calibration strategies, and privacy‐preserving deployment pathways that transform ...
Chenshu Liu, Haolin Fan, Minwoo Kim, Tong Zhou, Pinyi Yang, Lingdi Zhao, Yiran Wang, Ziyuan Che, Chia‐Wei Liu, Bingbing Li, Yangzhi Zhu   +10 more
wiley   +1 more source

Collaborating with transnational families: Learning from the experiences of family caretakers, educators, psychologists, and spiritual leaders in Honduras

American Journal of Community Psychology, EarlyView.
Abstract This manuscript centers on the experiences of caretakers of minors in Honduran transnational families (TNFs) in which one or both parents emigrated, and of the schoolteachers, professional psychologists, and spiritual leaders working with these families.
Marco Gemignani, Yolanda Hernández‐Albújar, Nerea Larrinaga‐Bidegain   +2 more
wiley   +1 more source