Results 41 to 50 of about 4,804,928 (276)
Agent-Specific Prompt Engineering for LLM-Guided RL Exploration
Recently, Large Language Model (LLM)-based Reinforcement Learning (RL) has gained attention as a new approach to improving exploration efficiency. However, traditional LLM-exploration relies on human-in-the-loop processes when encoding agent-specific ...
Bonwoo Gu, Jinseok Oh, Yunsick Sung
doaj +1 more source
Proteostasis and the gut microbiota play a key role in shaping host physiology. Microbiota‐derived metabolites, vitamins, and RNA modulate host proteostasis. Findings from model systems, including C. elegans, indicate microbes can either stabilize or disrupt host proteostasis.
Abhishek Anil Dubey, Maria Ermolaeva
wiley +1 more source
Developing Prompt Engineering as a 21st-Century Skill
Artificial intelligence (AI)-powered large language models, such as ChatGPT, are increasingly utilized in education, particularly for language learning.
Jennifer Preschern +3 more
doaj +1 more source
CT10 regulator of kinase (CRK) and CRK‐Like (CRKL) are signaling adaptors driving cell adhesion, motility, differentiation, and proliferation. SH2‐domain containing (SH) proteins are enriched in YXXP motifs which when phosphorylated create preferred binding sites for CRK family SH2 domains.
Phoebe M. Cousens +8 more
wiley +1 more source
Tell Me Your Prompts and I Will Make Them True: The Alchemy of Prompt Engineering and Generative AI
This paper explores the emerging field of prompt engineering within generative AI, emphasizing its role as a critical intersection between art and science.
Aras Bozkurt
doaj +1 more source
Reconstructing enzyme evolution by protein engineering
Natural enzyme evolution can be retraced by protein engineering methods such as directed evolution, rational design, and ancestral sequence reconstruction. These approaches reveal how enzymes emerged from ligand‐binding scaffolds, developed varying substrate preferences, formed oligomeric complexes, adapted to environmental changes, and evolved novel ...
Lukas Drexler +2 more
wiley +1 more source
Cancer progression is regulated by the dynamic matrix code of the tumor microenvironment, which influences cellular behavior and disease development. Importantly, matrix remodeling in three‐dimensional cancer models more accurately reflects in vivo conditions compared to conventional two‐dimensional systems.
Sylvia Mangani +3 more
wiley +1 more source
Is This the Best Prompt? Scoring Prompts for Arabic NLP Across LLMs
Large language models (LLMs) demonstrate impressive capabilities across a range of natural language processing (NLP) tasks. However, they are highly sensitive to prompt design, which significantly affects their ability to align outputs with user intent ...
Dania Refai +2 more
doaj +1 more source
The process of internalization of the Shiga toxin A subunit via formation of a complex with the Shiga toxin B subunit, which specifically binds to the Gb3 receptor. The peptide is designed to act as a carrier of drugs into cancer cells. Here, we explored the potential of peptides derived from the catalytic A subunit of Shiga toxin (STxA) to be drug ...
Giulia Opassi +6 more
wiley +1 more source
Investigating transcription factor dynamics in health and disease using FRAP
FRAP analysis of GFP‐tagged transcription factors reveals how molecular mobility and target engagement change in response to drug treatment. By combining live‐cell imaging, quantitative model fitting, and statistical analysis, this approach uncovers transcription factor dynamics linked to disease mechanisms, providing a powerful framework for ...
Kannan Govindaraj +3 more
wiley +1 more source

