Journal of Physical Chemistry & Biophysics
Open Access

Esmaeil Ebrahimie

Biography

Esmaeil Ebrahimie work history includes positions as NHMRC Research Fellow (Academic level B2) at The University of Adelaide, Adjunct Lecturer in the School of Molecular and Biomedical Science of The University of Adelaide, Researcher on influenza virus at School of Animal and Veterinary Sciences of The University of Adelaide based on Australian Centre for International Agricultural Research (ACIAR) grant, Assistant Professor at Shiraz University, Data Analyst at The University of South Australia and Vavilov-Frankel Research Fellow at The University of Adelaide.

 

Research Interest

Dr. Esmaeil Ebrahimie expert in transcriptomics, genomics and functional genomics analysis in particular in understanding the regulatory mechanisms, finding biosignatures, and developing functional genomics-based biomarkers. Remarkably, he highly creative in developing new ideas and approaches for analysis of huge genomics and transcriptomic datasets, particularly NGS (next generation sequencing) data. Examples are (1) Introducing a method for prediction of hot spots in different cancers based on combination of genomics and transcribotomic analysis with network and promoter analysis (PLOS One, 2014, 9: e96320), (2) Inventing a new genome-wide approach for gene discovery based on number and location of transcription factor binding sites on non-coding promoters regions (Gene, 2013, 531: 212-219), (3) Developing a novel approach for biomarker discovery based on RNA-Seq SSRs and small RNASeq SSRs (Gene, 2015, 560: 34-43), (4) Knowledge discovery and sequence-based prediction of pandemic influenza by machine learning analysis of big datasets (Journal of Biomedical Informatics, 2015, 57: 181-188). Furthermore, I have track record in application of novel data mining and rule discovery in biomedical research. Our analysis resulted in discovery of novel transcription factors controlling infection diseases (BMC Genomics, 2014, 15:769; Plos ONE, 2013, 8, e70862). Also, we developed the first specialised Gene Ontology (GO) webserver for bacteria (PLOS One, 2013, 8: e58759) and recently we updated this web application to zebrafish, human, and yeast to provide the possibility of GO enrichment and construction of Gene Ontology Interaction Networks.

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