Cargando…

DPSP: a multimodal deep learning framework for polypharmacy side effects prediction

MOTIVATION: Because unanticipated drug–drug interactions (DDIs) can result in severe bodily harm, identifying the adverse effects of polypharmacy is one of the most important tasks in human health. Over the past few decades, computational methods for predicting the adverse effects of polypharmacy ha...

Descripción completa

Detalles Bibliográficos
Autores principales:	Masumshah, Raziyeh, Eslahchi, Changiz
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Oxford University Press 2023
Materias:	Original Paper
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10493180/ https://www.ncbi.nlm.nih.gov/pubmed/37701676 http://dx.doi.org/10.1093/bioadv/vbad110

Ejemplares similares

A neural network-based method for polypharmacy side effects prediction
por: Masumshah, Raziyeh, et al.
Publicado: (2021)

ADRML: anticancer drug response prediction using manifold learning
por: Ahmadi Moughari, Fatemeh, et al.
Publicado: (2020)

Author Correction: ADRML: anticancer drug response prediction using manifold learning
por: Moughari, Fatemeh Ahmadi, et al.
Publicado: (2020)

Predicting parkinsonism side-effects of antipsychotic polypharmacy prescribed in secondary mental healthcare
por: Kadra, Giouliana, et al.
Publicado: (2018)

Classifying Breast Cancer Molecular Subtypes by Using Deep Clustering Approach
por: Rohani, Narjes, et al.
Publicado: (2020)

Drug-Drug Interaction Predicting by Neural Network Using Integrated Similarity
por: Rohani, Narjes, et al.
Publicado: (2019)

DSPLMF: A Method for Cancer Drug Sensitivity Prediction Using a Novel Regularization Approach in Logistic Matrix Factorization
por: Emdadi, Akram, et al.
Publicado: (2020)

Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov model
por: Emdadi, Akram, et al.
Publicado: (2021)

SimVec: predicting polypharmacy side effects for new drugs
por: Lukashina, Nina, et al.
Publicado: (2022)

A computational method for drug sensitivity prediction of cancer cell lines based on various molecular information
por: Ahmadi Moughari, Fatemeh, et al.
Publicado: (2021)

Protein complex prediction based on k-connected subgraphs in protein interaction network
por: Habibi, Mahnaz, et al.
Publicado: (2010)

PMLPR: A novel method for predicting subcellular localization based on recommender systems
por: Mirzaei Mehrabad, Elnaz, et al.
Publicado: (2018)

Modeling polypharmacy side effects with graph convolutional networks
por: Zitnik, Marinka, et al.
Publicado: (2018)

Impact of RNA structure on the prediction of donor and acceptor splice sites
por: Marashi, Sayed-Amir, et al.
Publicado: (2006)

DeepTraSynergy: drug combinations using multimodal deep learning with transformers
por: Rafiei, Fatemeh, et al.
Publicado: (2023)

Multimorbidity or polypharmacy: two sides of the same coin?
por: Sinnott, Carol, et al.
Publicado: (2015)

NN-RNALoc: Neural network-based model for prediction of mRNA sub-cellular localization using distance-based sub-sequence profiles
por: Babaiha, Negin Sadat, et al.
Publicado: (2023)

Multimodal Spatiotemporal Deep Learning Framework to Predict Response of Breast Cancer to Neoadjuvant Systemic Therapy
por: Verma, Monu, et al.
Publicado: (2023)

Removing the association of random gene sets and survival time in cancers with positive random bias using fixed-point gene set
por: Maghsoudi, Maryam, et al.
Publicado: (2023)

IPCA-CMI: An Algorithm for Inferring Gene Regulatory Networks based on a Combination of PCA-CMI and MIT Score
por: Aghdam, Rosa, et al.
Publicado: (2014)

TripNet: A Method for Constructing Rooted Phylogenetic Networks from Rooted Triplets
por: Poormohammadi, Hadi, et al.
Publicado: (2014)

Do Triplets Have Enough Information to Construct the Multi-Labeled Phylogenetic Tree?
por: Hassanzadeh, Reza, et al.
Publicado: (2014)

OrthoGNC: A Software for Accurate Identification of Orthologs Based on Gene Neighborhood Conservation
por: Jahangiri-Tazehkand, Soheil, et al.
Publicado: (2017)

An order independent algorithm for inferring gene regulatory network using quantile value for conditional independence tests
por: Mahmoodi, Sayyed Hadi, et al.
Publicado: (2021)

DisCoVering potential candidates of RNAi-based therapy for COVID-19 using computational methods
por: Rohani, Narjes, et al.
Publicado: (2021)

Intelligent ADL Recognition via IoT-Based Multimodal Deep Learning Framework
por: Javeed, Madiha, et al.
Publicado: (2023)

MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework
por: Lee, Garam, et al.
Publicado: (2019)

Gender Classification Based on Eye Movements: A Processing Effect During Passive Face Viewing
por: Sammaknejad, Negar, et al.
Publicado: (2017)

ExamPle: explainable deep learning framework for the prediction of plant small secreted peptides
por: Li, Zhongshen, et al.
Publicado: (2023)

MARSY: a multitask deep-learning framework for prediction of drug combination synergy scores
por: El Khili, Mohamed Reda, et al.
Publicado: (2023)

Deep learning with multimodal representation for pancancer prognosis prediction
por: Cheerla, Anika, et al.
Publicado: (2019)

Multimodal Deep Learning for Prognosis Prediction in Renal Cancer
por: Schulz, Stefan, et al.
Publicado: (2021)

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data
por: Yu, Lijia, et al.
Publicado: (2023)

Multimodal representation learning for predicting molecule–disease relations
por: Wen, Jun, et al.
Publicado: (2023)

MC-Net: a method for the construction of phylogenetic networks based on the Monte-Carlo method
por: Eslahchi, Changiz, et al.
Publicado: (2010)

Construction of random perfect phylogeny matrix
por: Sadeghi, Mehdi, et al.
Publicado: (2010)

In silico studies reveal structural deviations of mutant profilin-1 and interaction with riluzole and edaravone in amyotrophic lateral sclerosis
por: Sadr, Ahmad Shahir, et al.
Publicado: (2021)

Increasing the accuracy of single sequence prediction methods using a deep semi-supervised learning framework
por: Moffat, Lewis, et al.
Publicado: (2021)

A deep learning framework using CNN and stacked Bi-GRU for COVID-19 predictions in India
por: Ahuja, Sahil, et al.
Publicado: (2021)

DeepREAL: a deep learning powered multi-scale modeling framework for predicting out-of-distribution ligand-induced GPCR activity
por: Cai, Tian, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_3jfnvco1j21nk6hcs5qoo1psv4