Esmaeil Ebrahimie - Concepedia

Author

Esmaeil Ebrahimie

Also Known As

E Ebrahimie, E. Ebrahimie, E. EBRAHIMIE, E. Ebrahimie, Ebrahimi, M., Ebrahimie, E., Ebrahimie, Esmaeil, Eemaeil Ebrahimie, Esameil Ebrahimie, Esmaeil Ebrahimie

265

Publications

4.8K

Citations

H-Index

223

Concepts

All Affiliations

The University of Adelaide Shiraz University University of South Australia University of Qom Flinders University

About

Esmaeil Ebrahimie is an author at The University of Adelaide specializing in medicine, genetics, and functional genomics.

Top Concepts

#	Concept	H-Index	Publications	Citations
1	Medicine	25	61	2.1K
2	Natural Sciences	17	26	760
3	Engineering	15	20	702
4	Health Sciences	8	8	308
5	Education	3	3	318

Esmaeil Ebrahimie

116

Publications

3.9K

Citations

H-Index

Page 1

	Year	Citations
The androgen receptor is a tumor suppressor in estrogen receptor–positive breast cancer Theresa E. Hickey, Luke A. Selth, Kee Ming Chia, Nature Medicine Androgen ReceptorRadiation OncologyBreast OncologyHormonal ReceptorGynecology	2021	243
Predicting academic performance by considering student heterogeneity Sumyea Helal, Jiuyong Li, Lin Liu, Knowledge-Based Systems Student SuccessEducationStudent HeterogeneityEducational AssessmentUniversity Student Retention	2018	181
Comprehensive analysis of machine learning models for prediction of sub-clinical mastitis: Deep Learning and Gradient-Boosted Trees outperform other models Mansour Ebrahimi, Manijeh Mohammadi‐Dehcheshmeh, Esmaeil Ebrahimie, Computers in Biology and Medicine Machine LearningMachine Learning ModelMedicinePredictive AnalyticsDiagnosis	2019	150
MicroRNA-194 Promotes Prostate Cancer Metastasis by Inhibiting SOCS2 Rajdeep Das, Philip A. Gregory, Rayzel C. Fernandes, Cancer Research	2016	120
Integration of machine learning and meta-analysis identifies the transcriptomic bio-signature of mastitis disease in cattle Somayeh Sharifi, A. Pakdel, Mansour Ebrahimi, PLoS ONE E. ColiMachine LearningPathogen DetectionEscherichia ColiGenomics	2018	115
DrugMiner: comparative analysis of machine learning algorithms for prediction of potential druggable proteins Ali Akbar Jamali, Reza Ferdousi, Saeed Razzaghi, Drug Discovery Today Drug TargetEngineeringMachine Learning AlgorithmsDrug DiscoveryProteomics	2016	104
Determining the Most Important Physiological and Agronomic Traits Contributing to Maize Grain Yield through Machine Learning Algorithms: A New Avenue in Intelligent Agriculture Avat Shekoofa, Y. Emam, Navid Shekoufa, PLoS ONE Precision AgricultureEngineeringMachine LearningBotanyMachine Learning Algorithms	2014	85
A large-scale study of indicators of sub-clinical mastitis in dairy cattle by attribute weighting analysis of milk composition features: highlighting the predictive power of lactose and electrical conductivity Esmaeil Ebrahimie, Faezeh Ebrahimi, Mansour Ebrahimi, Journal of Dairy Research NutritionMilk CompositionLivestock ProductionDiagnosisEducation	2018	84
Differential expression of seven conserved microRNAs in response to abiotic stress and their regulatory network in Helianthus annuus Reyhaneh Ebrahimi Khaksefidi, Shirin Mirlohi, Fahimeh Khalaji, Frontiers in Plant Science BotanyGeneticsDna MethylationGene Expression PatternRegulatory Network	2015	77
Underlying functional genomics of fat deposition in adipose tissue Mohammad Reza Bakhtiarizadeh, Mohammad Moradi-Shahrbabak, Esmaeil Ebrahimie Gene ObesityMetabolic SyndromeBody CompositionAdipose TissueMetabolic Regulation	2013	76

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