Protein Prediction II for Computer Scientists WS13/14

Type:	Lecture (4 SWS) + Exercise (2 SWS)
Ects:	8.0
Lecturer	Burkhard Rost (lecture) Lothar Richter (exercise) mail: pp2ex@rostlab.org
Rotation:	Tuesday, 11:00 - 12:30 (lecture) Thursday, 11:00 - 12:30 (lecture) Thursday, 12:30 - 13:30 (exercise)
Place:	Lecture: Tuesday: FMI 01.09.034, Thursday: FMI 01.09.034 Exercise: Thursday: FMI 01.09.014 Exceptions: on Dec 5th and Dec 19th in FMI 00.09.038 Exam: 00.12.019 see also below in Announcements
Language:	English
Announcements:	The latest new is always on top! Please check out frequently since on the semester beginning there always can be changes on short notice. Review and Inspection is open until March 14th. Please arrange for an appointment (email to pp2ex@rostlab.org). Examination will take place in room 00.12.039 (Faculty Room) on Tue Feb 4th between 11-13 o'clock. No lecture and exercise on Dec 12th because of Dies Academicus No lecture on Tuesday Nov 12th because of SSV (Students' Plenum) No lecture on Oct. 31st, but the exercise takes place The room numbers has changed. Please see above. For exercise we will have a new room soon. Please note: The first lecture in the winter semester 2013/14 will take place on Thursday, October 17th, in room MW 2050 (Boltzmannstr. 15). Examen: Feb 4th (Important: Don't forget to register at TUMonline for the exam) Makeup: tba

Content

This lecture continues the 'Protein Prediction' lecture. Topics will include (but not be limited to):

Predicting protein function using sequence: sequence alignments, multiple sequence alignments, motifs, domain assignment, annotation transfer by homology, ab initio predictions.
Predicting protein function using structure: structural alignments, structural motifs, annotation transfer via structure similarity.
From structure prediction to function prediction: comparative modeling; prediction of: secondary structure, hydrophilicity profiles, solvent accessibility, transmembrane segments, disordered regions, contact maps, functional residues; template free modeling.
Machine learning.