Results 61 to 70 of about 90,813 (262)

The structural and content aspects of abstracts versus bodies of full text journal articles are different

BMC Bioinformatics, 2010
Background An increase in work on the full text of journal articles and the growth of PubMedCentral have the opportunity to create a major paradigm shift in how biomedical text mining is done.
Roeder Christophe, Verspoor Karin, Johnson Helen L, Cohen K Bretonnel, Hunter Lawrence E   +4 more
doaj   +1 more source

Engineering Osteoimmune Responses with Functionalized Orthopedic Implants for Post‐Operative Osteosarcoma Treatment

Advanced Science, EarlyView.
Osteosarcoma is the most common primary bone tumor with limited treatment options and a terrible prognosis. This review provides a comprehensive summary of the recent development of osteoimmunomodulatory implants for post‐operative osteosarcoma treatment, of which the potential utility in evoking durable anti‐osteosarcoma immunity and accelerating bone
Yilong Dong, Lingshuang Wang, Hui Zhang, Menghuan Li, Zhong Luo, Yan Hu, Chunyuan Cai   +6 more
wiley   +1 more source

Using a search engine-based mutually reinforcing approach to assess the semantic relatedness of biomedical terms. [PDF]

PLoS ONE, 2013
BACKGROUND: Determining the semantic relatedness of two biomedical terms is an important task for many text-mining applications in the biomedical field.
Yi-Yu Hsu, Hung-Yu Chen, Hung-Yu Kao
doaj   +1 more source

Functional Mapping of Neurodevelopmental Disease Pathways to Key Neurodevelopmental Processes Represented in the Developmental Neurotoxicity In Vitro Testing Battery

Advanced Science, EarlyView.
Human‐relevant methods are essential for modern chemical safety assessment. This study helps define the capabilities and boundaries of an in vitro testing battery for developmental neurotoxicity by exploring its biological applicability domain. By linking neurodevelopmental disease‐related pathways to key neurodevelopmental processes, the work enhances
Eliska Kuchovska, Kristina Bartmann, Georgea Raad, Mats Schade, Luiz Ladeira, Arif Dönmez, Jördis Klose, Nicolai Görts, Denis Polozij, Lynn‐Christin Saborowski, Farina Bendt, Bernard Staumont, Liesbet Geris, Katharina Koch, Ellen Fritsche   +14 more
wiley   +1 more source

OGER++: hybrid multi-type entity recognition

Journal of Cheminformatics, 2019
Background We present a text-mining tool for recognizing biomedical entities in scientific literature. OGER++ is a hybrid system for named entity recognition and concept recognition (linking), which combines a dictionary-based annotator with a corpus ...
Lenz Furrer, Anna Jancso, Nicola Colic, Fabio Rinaldi   +3 more
doaj   +1 more source

Integrating Spatial Proteogenomics in Cancer Research

Advanced Science, EarlyView.
Xx xx. ABSTRACT Background: Spatial proteogenomics marks a paradigm shift in oncology by integrating molecular analysis with spatial information from both spatial proteomics and other data modalities (e.g., spatial transcriptomics), thereby unveiling tumor heterogeneity and dynamic changes in the microenvironment.
Yida Wang, Yang Wu, Feng Zhang, Parthiban Periasamy, Haiyue You, Denise Goh, Rachel Elizabeth Ann Fincham, Xin Ning, Danping Wu, Lu Liu, Ying Jiang, Zhiwen Qian, Joe Yeong, Yan Zhang   +13 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

Literature Mining of Disease Associated Noncoding RNA in the Omics Era

Molecules, 2022
Noncoding RNAs (ncRNA) are transcripts without protein-coding potential that play fundamental regulatory roles in diverse cellular processes and diseases.
Jian Fan
doaj   +1 more source

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

Infectious Disease Ontology [PDF]

, 2009
Technological developments have resulted in tremendous increases in the volume and diversity of the data and information that must be processed in the course of biomedical and clinical research and practice.
A Bresell, A Djebbari, A Doms, A Ruttenberg, A Valouev, AC Yu, B Grinde, B Smith, B Smith, B Smith, B Smith, B Zhang, BR Zeeberg, C Medigue, C Rosse, C Schonbach, C Wolting, CA Schurink, CH Kim, D Huang, D Pisanelli, DA Natale, DL Buckeridge, DL Buckeridge, DL Rubin, DL Rubin, DP Hill, E Camon, F Baader, G Grumbling, H Tveit, HM Muller, I Spasic, J Bard, J Chabalier, J Kohler, JA Blake, JA Lee, JD Osborne, JM Cherry, K Thursky, KL Rickard, KM Coonan, LT Detwiler, M Brameier, M Coleman, M Rajapakse, MF Ochs, N Guarino, N Tiffin, NC Ide, O Bodenreider, O Bodenreider, PL Whetzel, R Cornet, SA Racunas, SE Baranzini, SL Pestotnik, TG Veenema, V Sintchenko, W Ceusters, W Ceusters, W Ceusters   +62 more
core   +3 more sources