Introduction to Machine Learning (IML)

James Cussens (JC)


Contents


Announcements


Reading

Apart from lecture- and practical- specific reading the following are of general relevance to this part of the module.


Lecture / practical schedule






Time and Place Title Reading Practical/Problem class
RCH/017 1015 10 Jan Multiple alignments, families of sequences and profile hidden Markov models Chapter 1 of HMMER User guide
RCH/017 1415 10 Jan Profile HMMs for ungapped regions of a multiple alignment First 3.5 pages of chapter 5 of Durbin et al
RCH/017 1015 12 Jan Profile HMMs for multiple alignments with gaps HERE
RCH/018 1015 16 Jan HMMer tutorial
RCH/017 0915 18 Jan Estimation of probabilities
RCH/018 1615 24 Jan Estimating probabilities
RCH/042 1015 23 Jan Forward and backward probabilities in HMMs
RCH/018 1015 30 Jan HMMs1
RCH/017 1115 24 Jan The Viterbi and Baum-Welch algorithms for HMMs
RCH/018 1115 31 Jan HMMs2
RCH/042 1015 6 Feb Significance of hits. Local and global alignment with HMMER


 Acknowledgements


Other useful links