Cargando…

A deep learning framework for identifying essential proteins based on multiple biological information

BACKGROUND: Essential Proteins are demonstrated to exert vital functions on cellular processes and are indispensable for the survival and reproduction of the organism. Traditional centrality methods perform poorly on complex protein–protein interaction (PPI) networks. Machine learning approaches bas...

Descripción completa

Detalles Bibliográficos
Autores principales:	Yue, Yi, Ye, Chen, Peng, Pei-Yun, Zhai, Hui-Xin, Ahmad, Iftikhar, Xia, Chuan, Wu, Yun-Zhi, Zhang, You-Hua
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	BioMed Central 2022
Materias:	Research
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9351218/ https://www.ncbi.nlm.nih.gov/pubmed/35927611 http://dx.doi.org/10.1186/s12859-022-04868-8

Ejemplares similares

DeepEP: a deep learning framework for identifying essential proteins
por: Zeng, Min, et al.
Publicado: (2019)

An ensemble framework for identifying essential proteins
por: Zhang, Xue, et al.
Publicado: (2016)

GNE: a deep learning framework for gene network inference by aggregating biological information
por: KC, Kishan, et al.
Publicado: (2019)

GSPHI: A novel deep learning model for predicting phage-host interactions via multiple biological information
por: Pan, Jie, et al.
Publicado: (2023)

An iteration model for identifying essential proteins by combining comprehensive PPI network with biological information
por: Li, Shiyuan, et al.
Publicado: (2021)

Identifying the quality characteristics of pork floss structure based on deep learning framework
por: Shen, Che, et al.
Publicado: (2023)

Identification of essential proteins based on edge features and the fusion of multiple-source biological information
por: Liu, Peiqiang, et al.
Publicado: (2023)

Incorporating Time Delays in Process Hitting Framework for Dynamical Modeling of Large Biological Regulatory Networks
por: Sheikh, Iftikhar Ali, et al.
Publicado: (2019)

A new computational strategy for identifying essential proteins based on network topological properties and biological information
por: Qin, Chao, et al.
Publicado: (2017)

Edge Caching in Fog-Based Sensor Networks through Deep Learning-Associated Quantum Computing Framework
por: Hasan, Tayyabah, et al.
Publicado: (2022)

EnsembleDL-ATG: Identifying autophagy proteins by integrating their sequence and evolutionary information using an ensemble deep learning framework
por: Yu, Lezheng, et al.
Publicado: (2023)

An interpretable deep learning framework for genome-informed precision oncology
por: Ren, Shuangxia, et al.
Publicado: (2023)

MUNIn: A statistical framework for identifying long-range chromatin interactions from multiple samples
por: Liu, Weifang, et al.
Publicado: (2021)

Framework and algorithms for identifying honest blocks in blockchain
por: Wang, Xu, et al.
Publicado: (2020)

ACPNet: A Deep Learning Network to Identify Anticancer Peptides by Hybrid Sequence Information
por: Sun, Mingwei, et al.
Publicado: (2022)

Investigating the Role of Obesity in Prostate Cancer and Identifying Biomarkers for Drug Discovery: Systems Biology and Deep Learning Approaches
por: Yeh, Shan-Ju, et al.
Publicado: (2022)

A Computational Framework Based on Ensemble Deep Neural Networks for Essential Genes Identification
por: Le, Nguyen Quoc Khanh, et al.
Publicado: (2020)

Play framework essentials
por: Richard-Foy, Julien
Publicado: (2014)

.NET framework essentials
por: Thai, Thuan L, et al.
Publicado: (2002)

.NET framework essentials
por: Thai, Thuan L, et al.
Publicado: (2001)

.NET framework essentials
por: Thai, Thuan L, et al.
Publicado: (2003)

A Systems Biology Approach to Identify Essential Epigenetic Regulators for Specific Biological Processes in Plants
por: McCoy, Rachel M., et al.
Publicado: (2021)

BAGEL: a computational framework for identifying essential genes from pooled library screens
por: Hart, Traver, et al.
Publicado: (2016)

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information
por: Yi, Hai-Cheng, et al.
Publicado: (2018)

The CRIT framework for identifying cross patterns in systems biology and application to chemogenomics
por: Gianoulis, Tara A, et al.
Publicado: (2011)

Intrusion Detection in IoT Using Deep Learning
por: Banaamah, Alaa Mohammed, et al.
Publicado: (2022)

Biologically informed deep neural network for prostate cancer discovery
por: Elmarakeby, Haitham A., et al.
Publicado: (2021)

An attention-based context-informed deep framework for infant brain subcortical segmentation
por: Chen, Liangjun, et al.
Publicado: (2023)

Identifying Informal Settlements Using Contourlet Assisted Deep Learning
por: Ansari, Rizwan Ahmed, et al.
Publicado: (2020)

English Text Recognition Deep Learning Framework to Automatically Identify Fake News
por: Wu, Fei, et al.
Publicado: (2022)

Essential biology /
por: Campbell, Neil A., 1946-
Publicado: (2004)

Essential biology /
por: Campbell, Neil A., 1946-
Publicado: (2007)

Multiple-component covalent organic frameworks
por: Huang, Ning, et al.
Publicado: (2016)

Security of Information and Networks
por: Ahmad, Iftikhar, et al.
Publicado: (2015)

A seed expansion-based method to identify essential proteins by integrating protein–protein interaction sub-networks and multiple biological characteristics
por: Zhao, He, et al.
Publicado: (2023)

DeepITEH: a deep learning framework for identifying tissue-specific eRNAs from the human genome
por: Zhang, Tianjiao, et al.
Publicado: (2023)

An Integrative Framework for Bayesian Variable Selection with Informative Priors for Identifying Genes and Pathways
por: Peng, Bin, et al.
Publicado: (2013)

Estimating global identifiability using conditional mutual information in a Bayesian framework
por: Bhola, Sahil, et al.
Publicado: (2023)

An Information Extraction Framework for Cohort Identification Using Electronic Health Records
por: Liu, Hongfang, et al.
Publicado: ( 201)

Data-informed deep optimization
por: Zhang, Lulu, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_92qlp7qrd6h27qn04utcjt0p9p