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Changiz Eslahchi

Showing results (1-10 of 61) with videos related to

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Frontiers in Genetics|December 16, 2020
Classifying Breast Cancer Molecular Subtypes by Using Deep Clustering ApproachNarjes Rohani, Changiz Eslahchi
Scientific Reports|September 22, 2019
Drug-Drug Interaction Predicting by Neural Network Using Integrated SimilarityNarjes Rohani, Changiz Eslahchi
Frontiers in Genetics|March 17, 2020
DSPLMF: A Method for Cancer Drug Sensitivity Prediction Using a Novel Regularization Approach in Logistic Matrix FactorizationAkram Emdadi, Changiz Eslahchi
Journal of Bioinformatics and Computational Biology|December 1, 2017
Comparison of different approaches for identifying subnetworks in metabolic networksAbolfazl Rezvan, Changiz Eslahchi
Bioinformatics Advances|November 11, 2025
PSO-FeatureFusion: a general framework for fusing heterogeneous features via particle swarm optimizationRaziyeh Masumshah, Changiz Eslahchi
Bioinformatics Advances|September 13, 2023
DPSP: a multimodal deep learning framework for polypharmacy side effects predictionRaziyeh Masumshah, Changiz Eslahchi
Journal of Bioinformatics and Computational Biology|December 20, 2021
Clinical drug response prediction from preclinical cancer cell lines by logistic matrix factorization approachAkram Emdadi, Changiz Eslahchi
BMC Bioinformatics|January 29, 2021
Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov modelAkram Emdadi, Changiz Eslahchi
Scientific Reports|August 30, 2020
ADRML: anticancer drug response prediction using manifold learningFatemeh Ahmadi Moughari, Changiz Eslahchi
Plos One|April 29, 2021
A computational method for drug sensitivity prediction of cancer cell lines based on various molecular informationFatemeh Ahmadi Moughari, Changiz Eslahchi
Pageof 7

Showing results (1-10 of 61) with videos related to

Sort By:
Pageof 7
Frontiers in Genetics|December 16, 2020
Classifying Breast Cancer Molecular Subtypes by Using Deep Clustering ApproachNarjes Rohani, Changiz Eslahchi
Scientific Reports|September 22, 2019
Drug-Drug Interaction Predicting by Neural Network Using Integrated SimilarityNarjes Rohani, Changiz Eslahchi
Frontiers in Genetics|March 17, 2020
DSPLMF: A Method for Cancer Drug Sensitivity Prediction Using a Novel Regularization Approach in Logistic Matrix FactorizationAkram Emdadi, Changiz Eslahchi
Journal of Bioinformatics and Computational Biology|December 1, 2017
Comparison of different approaches for identifying subnetworks in metabolic networksAbolfazl Rezvan, Changiz Eslahchi
Bioinformatics Advances|November 11, 2025
PSO-FeatureFusion: a general framework for fusing heterogeneous features via particle swarm optimizationRaziyeh Masumshah, Changiz Eslahchi
Bioinformatics Advances|September 13, 2023
DPSP: a multimodal deep learning framework for polypharmacy side effects predictionRaziyeh Masumshah, Changiz Eslahchi
Journal of Bioinformatics and Computational Biology|December 20, 2021
Clinical drug response prediction from preclinical cancer cell lines by logistic matrix factorization approachAkram Emdadi, Changiz Eslahchi
BMC Bioinformatics|January 29, 2021
Auto-HMM-LMF: feature selection based method for prediction of drug response via autoencoder and hidden Markov modelAkram Emdadi, Changiz Eslahchi
Scientific Reports|August 30, 2020
ADRML: anticancer drug response prediction using manifold learningFatemeh Ahmadi Moughari, Changiz Eslahchi
Plos One|April 29, 2021
A computational method for drug sensitivity prediction of cancer cell lines based on various molecular informationFatemeh Ahmadi Moughari, Changiz Eslahchi
Pageof 7