The accurate prediction of disordered regions in protein sequences
using machine learning approaches
Date and time: 11.30am - 12.30pm, Friday 28th August, 2009
Venue: 10.08.03 (Building 10, Level 08, Room 03)
Abstract:
A major challenge in the post-genome era is to determine the function of
proteins. Many proteins contain intrinsic unstructured or disordered regions (DRs) under physiological conditions and yet carry important
functions. Computational approaches to predicting DRs
can greatly assist biologists studying the structures and functions of
proteins.
We propose novel application of machine learning models and physiochemical
features extracted from protein sequences to predict long, short and global
disorder in proteins. We investigate the database of numerical indices
representing physiochemical properties of amino acids and select the indices
most correlated with disorder. To achieve high accuracy of prediction, novel
feature transforms including autocorrelation and wavelet transform are applied
to DR prediction based on selected physiochemical properties of amino acids.
Several disorder prediction models are built based on Decision Tree,
Random
About the speaker:
Pengfei is a PhD student at the School of
CS&IT at
Seminar Organisation
Seminars are free and open to the general public. No booking is necessary. If you are interested in giving a presentation in this seminar series, or to make suggestions for speakers, please contact Xiaodong Li, the seminar co-ordinator.