Cargando…

Machine learning methods, databases and tools for drug combination prediction

Combination therapy has shown an obvious efficacy on complex diseases and can greatly reduce the development of drug resistance. However, even with high-throughput screens, experimental methods are insufficient to explore novel drug combinations. In order to reduce the search space of drug combinati...

Descripción completa

Detalles Bibliográficos
Autores principales:	Wu, Lianlian, Wen, Yuqi, Leng, Dongjin, Zhang, Qinglong, Dai, Chong, Wang, Zhongming, Liu, Ziqi, Yan, Bowei, Zhang, Yixin, Wang, Jing, He, Song, Bo, Xiaochen
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2021
Materias:	Review
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8769702/ https://www.ncbi.nlm.nih.gov/pubmed/34477201 http://dx.doi.org/10.1093/bib/bbab355

Ejemplares similares

Computational methods, databases and tools for synthetic lethality prediction
por: Wang, Jing, et al.
Publicado: (2022)

DEML: Drug Synergy and Interaction Prediction Using Ensemble-Based Multi-Task Learning
por: Wang, Zhongming, et al.
Publicado: (2023)

Multi-dimensional data integration algorithm based on random walk with restart
por: Wen, Yuqi, et al.
Publicado: (2021)

A benchmark study of deep learning-based multi-omics data fusion methods for cancer
por: Leng, Dongjin, et al.
Publicado: (2022)

TOXRIC: a comprehensive database of toxicological data and benchmarks
por: Wu, Lianlian, et al.
Publicado: (2022)

Exploring novel disease-disease associations based on multi-view fusion network
por: Yang, Xiaoxi, et al.
Publicado: (2023)

A hybrid deep forest-based method for predicting synergistic drug combinations
por: Wu, Lianlian, et al.
Publicado: (2023)

An Algorithm Framework for Drug-Induced Liver Injury Prediction Based on Genetic Algorithm and Ensemble Learning
por: Yan, Bowei, et al.
Publicado: (2022)

COMSUC: A web server for the identification of consensus molecular subtypes of cancer based on multiple methods and multi-omics data
por: He, Song, et al.
Publicado: (2021)

Using machine learning tools for protein database biocuration assistance
por: König, Caroline, et al.
Publicado: (2018)

MantaID: a machine learning–based tool to automate the identification of biological database IDs
por: Zeng, Zhengpeng, et al.
Publicado: (2023)

Informatics and machine learning methods for health applications
por: Shen, Li, et al.
Publicado: (2020)

A survey and evaluation of Web-based tools/databases for variant analysis of TCGA data
por: Zhang, Zhuo, et al.
Publicado: (2018)

EDST: a decision stump based ensemble algorithm for synergistic drug combination prediction
por: Chen, Jing, et al.
Publicado: (2023)

Recent applications of deep learning and machine intelligence on in silico drug discovery: methods, tools and databases
por: Rifaioglu, Ahmet Sureyya, et al.
Publicado: (2018)

Wavelength-multiplexed hook nanoantennas for machine learning enabled mid-infrared spectroscopy
por: Ren, Zhihao, et al.
Publicado: (2022)

Machine Learning Prediction Models for Postoperative Stroke in Elderly Patients: Analyses of the MIMIC Database
por: Zhang, Xiao, et al.
Publicado: (2022)

Serological Biomarker-Based Machine Learning Models for Predicting the Relapse of Ulcerative Colitis
por: Pang, Wenwen, et al.
Publicado: (2023)

NeRD: a multichannel neural network to predict cellular response of drugs by integrating multidimensional data
por: Cheng, Xiaoxiao, et al.
Publicado: (2022)

Study on machine learning of molar incisor hypomineralization in an endemic fluorosis region in central China
por: Zhang, Yimeng, et al.
Publicado: (2023)

A machine learning approach for predicting descending thoracic aortic diameter
por: Yu, Ronghuang, et al.
Publicado: (2023)

Alumina Concentration Detection Based on the Kernel Extreme Learning Machine
por: Zhang, Sen, et al.
Publicado: (2017)

Development of Machine Learning Tools in ROOT
por: Gleyzer, S V, et al.
Publicado: (2016)

Combining Charge Density Analysis with Machine Learning Tools To Investigate the Cruzain Inhibition Mechanism
por: Luchi, Adriano M., et al.
Publicado: (2019)

Developing diagnostic tools for canine periodontitis: combining molecular techniques and machine learning models
por: Ruparell, Avika, et al.
Publicado: (2023)

Investigating Cellular Trajectories in the Severity of COVID-19 and Their Transcriptional Programs Using Machine Learning Approaches
por: Jeong, Hyun-Hwan, et al.
Publicado: (2021)

Machine Learning and Deep Learning based AI Tools for Development of Diagnostic Tools
por: Lepakshi, Vijayalakshmi A.
Publicado: (2022)

Neuromusculoskeletal model-informed machine learning-based control of a knee exoskeleton with uncertainties quantification
por: Zhang, Longbin, et al.
Publicado: (2023)

Classification and Analysis of Multiple Cattle Unitary Behaviors and Movements Based on Machine Learning Methods
por: Li, Yongfeng, et al.
Publicado: (2022)

Differentiating between cardiac amyloidosis and hypertrophic cardiomyopathy on non-contrast cine-magnetic resonance images using machine learning-based radiomics
por: Jiang, Shu, et al.
Publicado: (2022)

Predictive Modeling of Tensile Strength in Aluminum Alloys via Machine Learning
por: Fu, Keya, et al.
Publicado: (2023)

Dynamic Tracking of State Anxiety via Multi-Modal Data and Machine Learning
por: Ding, Yue, et al.
Publicado: (2022)

Machine learning for contour classification in TG‐263 noncompliant databases
por: Livermore, David, et al.
Publicado: (2022)

Evaluating hierarchical machine learning approaches to classify biological databases
por: Rezende, Pâmela M, et al.
Publicado: (2022)

Diagnosis and Prediction of Endometrial Carcinoma Using Machine Learning and Artificial Neural Networks Based on Public Databases
por: Zhao, Dongli, et al.
Publicado: (2022)

A Machine Learning–Based Preclinical Osteoporosis Screening Tool (POST): Model Development and Validation Study
por: Yang, Qingling, et al.
Publicado: (2023)

MLpronto: A tool for democratizing machine learning
por: Tjaden, Jacob, et al.
Publicado: (2023)

MOCSS: Multi-omics data clustering and cancer subtyping via shared and specific representation learning
por: Chen, Yuxin, et al.
Publicado: (2023)

Machine learning-driven exploration of drug therapies for triple-negative breast cancer treatment
por: Kaushik, Aman Chandra, et al.
Publicado: (2023)

Development and validation of an interpretable machine learning scoring tool for estimating time to emergency readmissions
por: Xie, Feng, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_llr9hvgrvn4b8fqjpch6q49atr