Results 121 to 130 of about 1,302,763 (303)
Relation Extraction : A Survey
With the advent of the Internet, large amount of digital text is generated everyday in the form of news articles, research publications, blogs, question answering forums and social media. It is important to develop techniques for extracting information automatically from these documents, as lot of important information is hidden within them.
Pawar, Sachin +2 more
openaire +2 more sources
This study reveals how the mitochondrial protein Slm35 is regulated in Saccharomyces cerevisiae. The authors identify stress‐responsive DNA elements and two upstream open reading frames (uORFs) in the 5′ untranslated region of SLM35. One uORF restricts translation, and its mutation increases Slm35 protein levels and mitophagy.
Hernán Romo‐Casanueva +5 more
wiley +1 more source
CourseKG: An Educational Knowledge Graph Based on Course Information for Precision Teaching
With the rapid development of advanced technologies, such as artificial intelligence and deep learning, educational informatization has entered a new era. However, the explosion of information has brought numerous challenges.
Ying Li +5 more
doaj +1 more source
In situ molecular organization and heterogeneity of the Legionella Dot/Icm T4SS
We present a nearly complete in situ model of the Legionella Dot/Icm type IV secretion system, revealing its central secretion channel and identifying new components. Using cryo‐electron tomography with AI‐based modeling, our work highlights the structure, variability, and mechanism of this complex nanomachine, advancing understanding of bacterial ...
Przemysław Dutka +11 more
wiley +1 more source
Information Extraction from Multi-Domain Scientific Documents: Methods and Insights
The rapid growth of scientific literature necessitates effective information extraction. However, existing methods face significant challenges, particularly when applied to multi-domain documents and low-resource languages.
Tatiana Batura +5 more
doaj +1 more source
Exploring Automatically Perturbed Natural Language Explanations in Relation Extraction [PDF]
Wanyun Cui, Xingran Chen
openalex +1 more source
Cell wall target fragment discovery using a low‐cost, minimal fragment library
LoCoFrag100 is a fragment library made up of 100 different compounds. Similarity between the fragments is minimized and 10 different fragments are mixed into a single cocktail, which is soaked to protein crystals. These crystals are analysed by X‐ray crystallography, revealing the binding modes of the bound fragment ligands.
Kaizhou Yan +5 more
wiley +1 more source
At low cell density, SETDB1 and YAP1 accumulate in the nucleus. As cell density increases, the Hippo pathway is gradually activated, and SETDB1 is associated with increased YAP1 phosphorylation. At high cell density, phosphorylated YAP1 is sequestered in the cytoplasm, while SETDB1 becomes polyubiquitinated and degraded by the ubiquitin–proteasome ...
Jaemin Eom +3 more
wiley +1 more source
Unsupervised Open Relation Extraction
The paper describes an approach to open relation extraction based on unsupervised machine learning. The state-of-the-art methods for extracting semantic relations are analyzed. The algorithm of automatic open relation extraction using statistical, syntactic and contextual information is proposed.
Tarasenko, Yaroslav, Petrasova, Svitlana
openaire +1 more source
Bone metastasis in prostate cancer (PCa) patients is a clinical hurdle due to the poor understanding of the supportive bone microenvironment. Here, we identify stearoyl‐CoA desaturase (SCD) as a tumor‐promoting enzyme and potential therapeutic target in bone metastatic PCa.
Alexis Wilson +7 more
wiley +1 more source

