• DeepTSS: multi-branch convolutional neural network for transcription start site identification from CAGE data 

      Grigoriadis D., Perdikopanis N., Georgakilas G.K., Hatzigeorgiou A.G. (2022)
      Background: The widespread usage of Cap Analysis of Gene Expression (CAGE) has led to numerous breakthroughs in understanding the transcription mechanisms. Recent evidence in the literature, however, suggests that CAGE ...
    • DIANA-miRGen v3.0: Accurate characterization of microRNA promoters and their regulators 

      Georgakilas G., Vlachos I.S., Zagganas K., Vergoulis T., Paraskevopoulou M.D., Kanellos I., Tsanakas P., Dellis D., Fevgas A., Dalamagas T., Hatzigeorgiou A.G. (2016)
      MicroRNAs (miRNAs) are small non-coding RNAs that actively fine-tune gene expression. The accurate characterization of the mechanisms underlying miRNA transcription regulation will further expand our knowledge regarding ...
    • DIANA-miRGen v4: Indexing promoters and regulators for more than 1500 microRNAs 

      Perdikopanis N., Georgakilas G.K., Grigoriadis D., Pierros V., Kavakiotis I., Alexiou P., Hatzigeorgiou A. (2021)
      Deregulation of microRNA (miRNA) expression plays a critical role in the transition from a physiological to a pathological state. The accurate miRNA promoter identification in multiple cell types is a fundamental endeavor ...
    • Identifying pri-miRNA transcription start sites 

      Georgakilas G., Perdikopanis N., Hatzigeorgiou A.G. (2018)
      MicroRNAs (miRNAs) are small non-coding RNAs that can regulate gene expression playing vital role in nearly all biological pathways. Even though miRNAs have been intensely studied for more than two decades, information ...