This talk will be in two parts (time permitting). The first part will focus on an algorithm for identifying clusters based on a Gaussian mixture model for the similarity data (as in the CLICK algorithm). The resulting algorithm has a complexity similar to the k-means algorithm. The second part of the talk will focus on ongoing work on a probabilistic model for the evolution of mRNA populations within a cell. The mRNA populations are modelled as queues (Markov chains) whose rates of transcription are regulated by probabilistic generalizations of Boolean functions. A statistical inference procedure based on the EM algorithm will be described. As this work is in progress only sample numerical results will be presented.