Markov chains provide a fundamental framework for modelling stochastic processes, where the next state depends solely on the current state. Hidden Markov models (HMMs) extend this framework by ...

The amino acid sequence of the transmembrane protein and its corresponding positions on the cell membrane are transformed into a hidden Markov process. After evaluating the parameters, the Viterbi ...

In his landmark 1949 paper, Claude Shannon showed how simple statistical models called Markov chains could reproduce the structure of human language. By modeling how letters and words depend on one ...

Antitumor activity of MP0250, a bispecific VEGF- and HGF-targeting darpin, in patient-derived xenograft models. This is an ASCO Meeting Abstract from the 2014 ASCO Annual Meeting I. This abstract does ...

A 30-minute talk about Markov modeling generally, with specific reference to the seminal 1986 contribution of Professor Eaves, which described Markov processes for genetic and environmental variance ...