Results 231 to 240 of about 622,064 (301)

Harnessing Large Language Models to Advance Microbiome Research: From Sequence Analysis to Clinical Applications

Advanced Intelligent Discovery, EarlyView.
Large language models are transforming microbiome research by enabling advanced sequence profiling, functional prediction, and association mining across complex datasets. They automate microbial classification and disease‐state recognition, improving cross‐study integration and clinical diagnostics.
Jieqi Xing, He Wang, Yangyang Sun, Xiaoquan Su, Shunyao Wu   +4 more
wiley   +1 more source

Chemical Ecology of Parasitic Hymenoptera. [PDF]

Biomed Res Int, 2016
Benelli G, Daane KM, Soler R, Stökl J.
europepmc   +1 more source

LLM‐Based Scientific Assistants for Knowledge Extraction: Which Design Choices Matter?

Advanced Intelligent Discovery, EarlyView.
A comprehensive framework for optimizing Large Language Models in domain‐specific applications is introduced. The LLM Playground integrates Prompt Engineering, knowledge augmentation, and advanced reasoning strategies to enable systematic comparison of architectures and base models.
David Exler, Manuel Raimann, Marc Münker, Maxim Rosin, Joaquin E. Urrutia Gómez, Christof M. Niemeyer, Markus Reischl, Luca Rettenberger   +7 more
wiley   +1 more source

Chemical Ecology of Capnodis tenebrionis (L.) (Coleoptera: Buprestidae): Behavioral and Biochemical Strategies for Intraspecific and Host Interactions. [PDF]

Front Physiol, 2019
Bari G, Scala A, Garzone V, Salvia R, Yalcin C, Vernile P, Aresta AM, Facini O, Baraldi R, Bufo SA, Vogel H, de Lillo E, Rapparini F, Falabella P.   +13 more
europepmc   +1 more source

Composition‐Aware Cross‐Sectional Integration for Spatial Transcriptomics

Advanced Intelligent Discovery, EarlyView.
Multi‐section spatial transcriptomics demands coherent cell‐type deconvolution, domain detection, and batch correction, yet existing pipelines treat these tasks separately. FUSION unifies them within a composition‐aware latent framework, modeling reads as cell‐type–specific topics and clustering in embedding space.
Qishi Dong, Zijian Huang, Xuanwu Wang, Zhenghui Feng, Wei Liu, Bingding Huang   +5 more
wiley   +1 more source

Life history and chemical ecology of the Warrior wasp Synoeca septentrionalis (Hymenoptera: Vespidae, Epiponini). [PDF]

PLoS One, 2018
Santos EB, Shemilt S, de Carvalho CAL, Martin SJ.   +3 more
europepmc   +1 more source

An Attention‐Assisted Machine Learning System for Deep Microorganism Image Classification

Advanced Intelligent Systems, EarlyView.
An attention‐assisted DenseNet201 framework was developed for the classification of eight microorganism classes from microscopic images. The proposed model improved classification performance and achieved an accuracy of 87.38%. Advances in microbiology and environmental health fundamentally depend on precise and timely microorganism identification ...
Yujie Li, Ailing Gao, Guoxu Liu, Chunlei Chen, Yonghui Zhang, Sunkyoung Kang, M. Khosravi   +6 more
wiley   +1 more source

Challenges and opportunities in marine chemical ecology. [PDF]

J Chem Ecol, 2014
Hay ME.
europepmc   +1 more source

Biodegradable and Bioinspired UV Light Recognition via Sustainable Synaptic Transistors for Artificial Intelligence Vision Systems

Advanced Intelligent Systems, EarlyView.
We report a biodegradable electrolyte‐gated synaptic phototransistor that combines low‐power UV sensing with memory functionality, offering a sustainable platform for AI vision systems and health‐monitoring technologies. Presented here is a biodegradable, bioinspired synaptic phototransistor (SPT) based on an electrolyte‐gated field‐effect transistor ...
Theodoros Serghiou, Rogério Morais, Douglas Henrique Vieira, Neri Alves, Roghaieh Parvizi, Jeff Kettle   +5 more
wiley   +1 more source

Olfactory learning and chemical ecology of olfaction in disease vector mosquitoes: a life history perspective. [PDF]

Curr Opin Insect Sci, 2017
Lutz EK, Lahondère C, Vinauger C, Riffell JA.   +3 more
europepmc   +1 more source