Results 51 to 60 of about 368,749 (284)
The Shewanella oneidensis Fic enzyme SoFic targets the switch‐I region of EF‐Tu for AMPylation
FEBS Letters, EarlyView.Fic enzymes mediate diverse post‐translational modifications across all domains of life, including AMPylation. Prokaryotic EF‐Tu can be AMPylated and deAMPylated by the conserved Fic enzyme SoFic. Structural and biochemical approaches were used to characterize the effect of AMPylation on EF‐Tu, SoFic's enzymatic activities, and the enzyme‐target ...
Svenja Runge +6 more
wiley +1 more source
Inherent Disagreements in Human Textual Inferences
Transactions of the Association for Computational Linguistics, 2019 We analyze human’s disagreements about the validity of natural language inferences. We show that, very often, disagreements are not dismissible as annotation “noise”, but rather persist as we collect more ratings and as we vary the amount of context ...
Pavlick, Ellie, Kwiatkowski, Tom
doaj +1 more source
Compressing BERT for Binary Text Classification via Adaptive Truncation before Fine-Tuning
Applied Sciences, 2022 Large-scale pre-trained language models such as BERT have brought much better performance to text classification. However, their large sizes can lead to sometimes prohibitively slow fine-tuning and inference.
Xin Zhang, Jing Fan, Mengzhe Hei
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Membrane composition and thermodynamic identity as boundaries of life for synthetic cell research
FEBS Letters, EarlyView.What makes a cell a cell? The boundary of a living cell is not just a wall. Read as a Markov blanket, the membrane separates internal from external states, generating identity and non‐equilibrium order. Can this identity be rebuilt from scratch in a synthetic cell?
Caterina Presutti, Bert Poolman
wiley +1 more source
Textual Entailment for Modern Standard Arabic
Informatica, 2021 This paper summarizes the Doctoral Thesis that examines various techniques to recognizing Arabic textual entailment, deciding whether one fragment of text entails another, where there is an exceptional level of structural and lexical ambiguities. As far as we know, the current work is the first study to apply this task for Arabic.
openaire +2 more sources
Arabic Textual Entailment with Word Embeddings [PDF]
Proceedings of the Third Arabic Natural Language Processing Workshop, 2017 Determining the textual entailment between texts is important in many NLP tasks, such as summarization, question answering, and information extraction and retrieval. Various methods have been suggested based on external knowledge sources; however, such resources are not always available in all languages and their acquisition is typically laborious and ...
Nada AlMarwani, Mona T. Diab
openaire +1 more source
The role of miR‐335‐5p in the redifferentiation of BRAF p.V600E thyroid cancers
Molecular Oncology, EarlyView.The BRAF p.V600E mutation promotes thyroid cancer dedifferentiation and radioiodine resistance. Using a network approach, we identified miR‐335‐5p as a key regulator of BRAF‐mutated thyroid tumors. Restoring miR‐335‐5p increased thyroid‐specific gene expression and iodine uptake in cells and organoids.
Valeria Pecce +11 more
wiley +1 more source
Molecular Oncology, EarlyView.Breast cancer remains a major cause of cancer death in women, frequently developing endocrine therapy resistance. This study demonstrates that upregulated p21‐activated kinase 1 (PAK1) activity drives resistance to tamoxifen and long‐term estrogen deprivation in ER+ breast cancer models.
Luisa Schwarzmüller +10 more
wiley +1 more source
Journal of Information Systems Engineering and Business IntelligenceBackground: Recognizing Textual Entailment (RTE) is a task in Natural Language Processing (NLP), used for question-answering, information retrieval, and fact-checking.
Teuku Yusransyah Tandi +2 more
doaj +1 more source
An Open Domain Factoid QA Framework with Improved Validation Techniques
International Journal of Information Science and Management, 2022 The generic Question Answering (QA) framework processes questions by querying a knowledge base and extracting answers from retrieved passages using various Natural Language Processing techniques.
Emmanuel Adebisi +2 more
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