Computational Molecular Biology. Protein-nucleic acid recognition and regulation, Regulatory networks
In our laboratory we develop and apply computational approaches to study nucleic acid recognition and regulation, by integrating genomic, molecular structure and high throughput expression data.
Our main goal is to understand the underlying principles of RNA and DNA recognition and to develop tools towards identifying novel proteins, pathways and drug targets involved in the gene expression regulation.
Prof, Shura Mankin UIC , USA on predicting novel antibiotic binding sites on the ribosome
Prof Manny Ares, UCSC, USA on cross-network controls between splicing regulatory networks and transcriptional regulatory networks in mammalian cells.
Leibovich L., Mandel-Gutfreund Y*., Yakhini ZP. * A structural-based statistical approach suggests a cooperative activity of PUM1 and miR-410 in human 3′-untranslated regions. Silence, 22:17 (2010) *corresponding authors
Shazman S, Elber G, Mandel-Gutfreund Y. From face to interface recognition: a differential geometric approach to distinguish DNA from RNA binding surfaces. Nucleic Acids Res. 39:7390. (2011)
Kosti I, Radivojac P, Mandel-Gutfreund Y. An integrated regulatory network reveals pervasive cross-regulation among transcription and splicing factors. PLoS Comput Biol.8:e1002603. (2012)
Kligun, E. and Mandel-Gutfreund, Y. Conformational readout of RNA by small ligands, RNA Biology 16;10(6). (2013)
Dror I, Zhou T, Mandel-Gutfreund Y*, Rohs R*. Covariation between homeodomain transcription factors and the shape of their DNA binding sites Nucleic Acids Res.. (2014). *corresponding authors