Isabella Sanders
PhD candidate, Plant Developmental Systems, Wageningen University & Research
Project: Machine learning-based prediction of transcription factor protein-protein interactions
About my research
Plants use transcription factors to regulate all developmental processes occurring throughout their lifecycle. One family of transcription factors seems to be overly present in these proteins, namely: the MADS-box proteins. These proteins are all highly similar in structure, but have a highly diverse interaction pattern. SOC1, for instance, is capable of interacting with circa 25 other MADS box transcription factors, whereas the highly similar AGL14 interacts with only 4 proteins. In my research, the aim is to understand where the specificity of these protein-protein interactions comes from. We use machine learning to predict what motifs could be of influence. Ultimately, this research should contribute to predicting interaction specificity for other transcription factors.