אירועים והרצאות בפקולטה למדעי המחשב ע"ש הנרי ומרילין טאוב

Small regulatory RNAs are a class of non-coding RNAs that are primarily involved in post-transcriptional gene silencing. The principle members of this growing class are microRNAs and small interfering RNAs (siRNAs) which guide a silencing complex to an mRNA target by base pairing at the 3 untranslated region (3UTR).

In recent years, microRNAs have emerged as a major class of regulatory genes central to a wide range of cellular activities, and their importance is underscored by their evolutionary conservation in most of metazoan and plant species. A central and ongoing computational challenge is the accurate prediction of the mRNA targets of a microRNA.

Target specificity of a microRNA is not conditioned on perfect complementarity to the target mRNA, although a (near) perfect base- pairing in the 5end of the microRNA (positions 2-8), termed the seed region, is a primary determinant of target recognition. However, seed region complementarity alone is a poor predictor suggesting that additional factors are involved in microRNA mediated regulation.

In the first part of this talk I will present a supervised learning strategy for ranking microRNA target sites. We trained a support vector regression model to rank predicted target sites, which are represented by a set of features that include the base-pairing configurations of the predicted target site duplex along with additional sequence and context information. We tested the model on a number of test sets and show that it significantly improves upon leading microRNA target prediction programs.

In the second part of this talk, I will present recent collaborative work in studying microRNA function in stem cell differentiation and in long-term synaptic plasticity.