Cargando…

Predicting metabolic response to dietary intervention using deep learning

Due to highly personalized biological and lifestyle characteristics, different individuals may have different metabolic responses to specific foods and nutrients. In particular, the gut microbiota, a collection of trillions of microorganisms living in our gastrointestinal tract, is highly personaliz...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wang, Tong, Holscher, Hannah D., Maslov, Sergei, Hu, Frank B., Weiss, Scott T., Liu, Yang-Yu
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Cold Spring Harbor Laboratory 2023
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10054958/ https://www.ncbi.nlm.nih.gov/pubmed/36993761 http://dx.doi.org/10.1101/2023.03.14.532589

Ejemplares similares

FUN-PROSE: A deep learning approach to predict condition-specific gene expression in fungi
por: Nambiar, Ananthan, et al.
Publicado: (2023)

Predicting tumor cell line response to drug pairs with deep learning
por: Xia, Fangfang, et al.
Publicado: (2018)

Dietary fiber and prebiotics and the gastrointestinal microbiota
por: Holscher, Hannah D.
Publicado: (2017)

Etiology of Metabolic Syndrome and Dietary Intervention
por: Xu, Hang, et al.
Publicado: (2018)

Ecology-guided prediction of cross-feeding interactions in the human gut microbiome
por: Goyal, Akshit, et al.
Publicado: (2021)

Avenues of research in dietary interventions to target tumor metabolism in osteosarcoma
por: Leite, Taiana Campos, et al.
Publicado: (2021)

A Toolbox Model of Evolution of Metabolic Pathways on Networks of Arbitrary Topology
por: Pang, Tin Yau, et al.
Publicado: (2011)

The Challenging Chase for Nutrigenetic Predictors of Metabolic Responses to Dietary Interventions
por: Sarzynski, Mark A., et al.
Publicado: (2013)

Cancer metabolism and dietary interventions
por: Qian, Lin, et al.
Publicado: (2022)

Deep Learning Methods for Predicting Disease Status Using Genomic Data
por: Wu, Qianfan, et al.
Publicado: (2018)

Interactive Deep Learning for Shelf Life Prediction of Muskmelons Based on an Active Learning Approach
por: Albert-Weiss, Dominique, et al.
Publicado: (2022)

Perspective: Leveraging the Gut Microbiota to Predict Personalized Responses to Dietary, Prebiotic, and Probiotic Interventions
por: Gibbons, Sean M, et al.
Publicado: (2022)

Dietary Interventions in Obesity and Metabolic Syndrome
por: Szewczyk-Golec, Karolina, et al.
Publicado: (2023)

Prediction of the Antioxidant Response Elements' Response of Compound by Deep Learning
por: Bai, Fang, et al.
Publicado: (2019)

Prediction of lymphoma response to CAR T cells by deep learning-based image analysis
por: Tong, Yubing, et al.
Publicado: (2023)

UV-Induced Mutagenesis in Escherichia coli SOS Response: A Quantitative Model
por: Krishna, Sandeep, et al.
Publicado: (2007)

Software Defect Prediction Based on Hybrid Swarm Intelligence and Deep Learning
por: Li, Zhen, et al.
Publicado: (2021)

C677T gene polymorphism of MTHFR and metabolic syndrome: response to dietary intervention
por: Di Renzo, Laura, et al.
Publicado: (2014)

Prediction of plant secondary metabolic pathways using deep transfer learning
por: Bao, Han, et al.
Publicado: (2023)

Prediction of Protein-protein Interactions on the Basis of Evolutionary Conservation of Protein Functions
por: Kotelnikova, Ekaterina, et al.
Publicado: (2007)

Deep learning of dynamically responsive chemical Hamiltonians with semiempirical quantum mechanics
por: Zhou, Guoqing, et al.
Publicado: (2022)

An Introductory Review of Deep Learning for Prediction Models With Big Data
por: Emmert-Streib, Frank, et al.
Publicado: (2020)

DeepCarc: Deep Learning-Powered Carcinogenicity Prediction Using Model-Level Representation
por: Li, Ting, et al.
Publicado: (2021)

Evidence for a multi-level trophic organization of the human gut microbiome
por: Wang, Tong, et al.
Publicado: (2019)

DeepPhos: prediction of protein phosphorylation sites with deep learning
por: Luo, Fenglin, et al.
Publicado: (2019)

Deep-RBPPred: Predicting RNA binding proteins in the proteome scale based on deep learning
por: Zheng, Jinfang, et al.
Publicado: (2018)

Using deep learning to predict anti-PD-1 response in melanoma and lung cancer patients from histopathology images
por: Hu, Jing, et al.
Publicado: (2020)

Deep Learning for Improved Risk Prediction in Surgical Outcomes
por: Jalali, Ali, et al.
Publicado: (2020)

DeepTP: A Deep Learning Model for Thermophilic Protein Prediction
por: Zhao, Jianjun, et al.
Publicado: (2023)

Berry Dietary Interventions in Metabolic Syndrome: New Insights
por: Venturi, Samuele, et al.
Publicado: (2023)

Corrigendum: DeepCarc: Deep learning-powered carcinogenicity prediction using model-level representation
por: Li, Ting, et al.
Publicado: (2022)

Ensemble deep learning enhanced with self-attention for predicting immunotherapeutic responses to cancers
por: Jin, Wenyi, et al.
Publicado: (2022)

Modeling microbial cross-feeding at intermediate scale portrays community dynamics and species coexistence
por: Liao, Chen, et al.
Publicado: (2020)

Heterogeneity in Metabolic Responses to Dietary Fructose
por: Hou, Ruixue, et al.
Publicado: (2019)

The MIND Dietary Pattern Is Selectively Related to Cognitive Processing Speed
por: Holthaus, Tori, et al.
Publicado: (2022)

Deep learning for automatically predicting early haematoma expansion in Chinese patients
por: Zhong, Jia-wei, et al.
Publicado: (2021)

Deep learning and multi-omics approach to predict drug responses in cancer
por: Wang, Conghao, et al.
Publicado: (2022)

Predicting Anticancer Drug Response With Deep Learning Constrained by Signaling Pathways
por: Zhang, Heming, et al.
Publicado: (2021)

Biology-guided deep learning predicts prognosis and cancer immunotherapy response
por: Jiang, Yuming, et al.
Publicado: (2023)

Inflation Prediction Method Based on Deep Learning
por: Yang, Cheng, et al.
Publicado: (2021)

Cannot write session to /tmp/vufind_sessions/sess_846bjs7fpmgfdqrg7m12he4ahv