Cargando…

Prediction of Interactions between Viral and Host Proteins Using Supervised Machine Learning Methods

BACKGROUND: Viral-host protein-protein interaction plays a vital role in pathogenesis, since it defines viral infection of the host and regulation of the host proteins. Identification of key viral-host protein-protein interactions (PPIs) has great implication for therapeutics. METHODS: In this study...

Descripción completa

Detalles Bibliográficos
Autores principales:	Barman, Ranjan Kumar, Saha, Sudipto, Das, Santasabuj
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Public Library of Science 2014
Materias:	Research Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4223108/ https://www.ncbi.nlm.nih.gov/pubmed/25375323 http://dx.doi.org/10.1371/journal.pone.0112034

Ejemplares similares

Dynamic Modularity of Host Protein Interaction Networks in Salmonella Typhi Infection
por: Dhal, Paltu Kumar, et al.
Publicado: (2014)

Prediction of Intra-Species Protein-Protein Interactions in Enteropathogens Facilitating Systems Biology Study
por: Barman, Ranjan Kumar, et al.
Publicado: (2015)

Identification of infectious disease-associated host genes using machine learning techniques
por: Barman, Ranjan Kumar, et al.
Publicado: (2019)

An improved method for identification of small non-coding RNAs in bacteria using support vector machine
por: Barman, Ranjan Kumar, et al.
Publicado: (2017)

A network biology approach to identify crucial host targets for COVID-19
por: Barman, Ranjan Kumar, et al.
Publicado: (2022)

Prediction of Phage Virion Proteins Using Machine Learning Methods
por: Barman, Ranjan Kumar, et al.
Publicado: (2023)

Assessing the druggability of protein-protein interactions by a supervised machine-learning method
por: Sugaya, Nobuyoshi, et al.
Publicado: (2009)

Metagenomic Surveys of Gut Microbiota
por: Mandal, Rahul Shubhra, et al.
Publicado: (2015)

Prediction of virus-host infectious association by supervised learning methods
por: Zhang, Mengge, et al.
Publicado: (2017)

Predicting protein complex in protein interaction network - a supervised learning based method
por: Yu, Feng Ying, et al.
Publicado: (2014)

Support Vector Machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs
por: Rashid, Mamoon, et al.
Publicado: (2007)

Machine Learning and Artificial Intelligence for the Prediction of Host–Pathogen Interactions: A Viral Case
por: Yakimovich, Artur
Publicado: (2021)

Predicting the Printability in Selective Laser Melting with a Supervised Machine Learning Method
por: Chen, Yingyan, et al.
Publicado: (2020)

Supervised Machine Learning Methods for Seasonal Influenza Diagnosis
por: Marquez, Edna, et al.
Publicado: (2023)

Supervised Algorithms of Machine Learning for the Prediction of Cervical Cancer
por: F., Asadi, et al.
Publicado: (2020)

Predictive Supervised Machine Learning Models for Diabetes Mellitus
por: Muhammad, L. J., et al.
Publicado: (2020)

Gully erosion prediction method from geoenvironmental data and supervised machine learning techniques
por: Lana, Julio Cesar
Publicado: (2023)

Machine learning techniques for sequence-based prediction of viral–host interactions between SARS-CoV-2 and human proteins
por: Dey, Lopamudra, et al.
Publicado: (2020)

A Comparative Study of Supervised Machine Learning Algorithms for the Prediction of Long-Range Chromatin Interactions
por: Vanhaeren, Thomas, et al.
Publicado: (2020)

Host-Virus Protein Interaction Network Reveals the Involvement of Multiple Host Processes in the Life Cycle of Hepatitis E Virus
por: Subramani, Chandru, et al.
Publicado: (2018)

Supervised machine learning in wind forecasting and ramp event prediction
por: Dhiman, Harsh S, et al.
Publicado: (2020)

Comparing different supervised machine learning algorithms for disease prediction
por: Uddin, Shahadat, et al.
Publicado: (2019)

Predicting cash holdings using supervised machine learning algorithms
por: Özlem, Şirin, et al.
Publicado: (2022)

Predicting Breast Cancer Leveraging Supervised Machine Learning Techniques
por: Aamir, Sanam, et al.
Publicado: (2022)

Prediction of Diabetes Mellitus Progression Using Supervised Machine Learning
por: Chauhan, Apoorva S., et al.
Publicado: (2023)

Examining Supervised Machine Learning Methods for Integer Link Weight Prediction Using Node Metadata
por: Mori, Larissa, et al.
Publicado: (2022)

Classification and prediction of protein–protein interaction interface using machine learning algorithm
por: Das, Subhrangshu, et al.
Publicado: (2021)

Prediction of viral-host interactions of COVID-19 by computational methods
por: Alakus, Talha Burak, et al.
Publicado: (2022)

Integrated Deep Learning and Supervised Machine Learning Model for Predictive Fetal Monitoring
por: Gude, Vinayaka, et al.
Publicado: (2022)

Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods
por: Rashidi, Hooman H., et al.
Publicado: (2019)

Supervised machine learning with Python: develop rich Python coding practices while exploring supervised machine learning
por: Smith, Taylor
Publicado: (2019)

Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks
por: Palukuri, Meghana V., et al.
Publicado: (2021)

Super.Complex: A supervised machine learning pipeline for molecular complex detection in protein-interaction networks
por: Palukuri, Meghana Venkata, et al.
Publicado: (2021)

Predictions of the mechanical properties of unidirectional fibre composites by supervised machine learning
por: Pathan, M. V., et al.
Publicado: (2019)

A framework for predicting academic orientation using supervised machine learning
por: El Mrabet, Hicham, et al.
Publicado: (2022)

Supervised Machine Learning Empowered Multifactorial Genetic Inheritance Disorder Prediction
por: Ghazal, Taher M., et al.
Publicado: (2022)

Prediction of Fracture Toughness of Pultruded Composites Based on Supervised Machine Learning
por: Karamov, Radmir, et al.
Publicado: (2022)

Prediction of inherited genomic susceptibility to 20 common cancer types by a supervised machine-learning method
por: Kim, Byung-Ju, et al.
Publicado: (2018)

Exploratory application of machine learning methods on patient reported data in the development of supervised models for predicting outcomes
por: Verma, Deepika, et al.
Publicado: (2022)

Antibiotic binding of STY3178, a yfdX protein from Salmonella Typhi
por: Saha, Paramita, et al.
Publicado: (2016)

Cannot write session to /tmp/vufind_sessions/sess_3tc46vbdegcfelu0molifmr9cc