David Nono, Ernest Mwebesa, Godfrey Bagenda, Isaac Okullo, Charles Mugisha Rwenyonyi, Simon Williams
Assessment of the knowledge, attitude and practices of the informed consent process in oral healthcare among dental students in Makerere University Dental Hospital, Uganda
BMC medical education
deep learning emerged powerful tool investigating intricate biological processes plants harnessing potential largescale data gene regulation complex process transcription factors tfs cooperating target genes participate various aspects biological processes despite significance study gene regulation primarily focused limited number notable instances leaving numerous aspects interactions yet explored comprehensively developed degrn deep learning expression gene regulatory network innovative deep learning model designed decipher gene interactions leveraging highdimensional expression data obtained bulk rnaseq scrnaseq data model plant arabidopsis degrn exhibited compared level predictive power applied various datasets utilization degrn successfully identified extensive set 3053363 highquality interactions encompassing 1430 tfs 13739 nontf genes notably degrns predictive capabilities allowed us uncover novel regulators involved range complex biological processes including development metabolism stress responses using leaf senescence example revealed complex network underpinning process composed diverse tf families including bhlh erf myb also identified novel tf named maf5 whose expression showed strong linear regression relation progression senescence mutant maf5 showed early leaf decay compared wild type indicating potential role regulation leaf senescence hypothesis supported expression patterns observed across four stages leaf development well transcriptomics analysis overall comprehensive coverage provided degrn expands understanding gene regulatory networks paves way investigations functional implications