Intelligent systems in

ocelotgiantAI and Robotics

Nov 7, 2013 (3 years and 9 months ago)

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Intelligent systems in
bioinformatics

Introduction to the course

Contact details

Dr. Karen Page

Computer Science
-

Room G50a

Tel: 020 7679 3683 (internal: 33683)

Email:
k.page@cs.ucl.ac.uk

http://www.cs.ucl.ac.uk/staff/K.Page


Lecture format


Monday and Thursday afternoons (2
-
5pm)


Pearson Lecture Theatre (Mon.)
& Rm 229 (Thurs.)


We will take one or two 10/15
-
minute
breaks, so typically the lecture might be
split:


50
-
10
-
50
-
10
-
50






or





80
-
15
-
75

Coursework & Homework


Coursework:


1 piece


15% of total mark


towards end of course



Homework:


Each week (doesn’t contribute to course
grade)


Attach cover sheet
(
http://www.cs.ucl.ac.uk/teaching/cwsheet.
htm
)


Give to JJ Giwa (G07) by 12pm on due date

Exam


Written exam


15
th

March


85% of total mark


Newsgroups/ Mailing list


All communication concerning this
course will be done via the email list.


Please join by sending an email with


Subject
: join


to
gi10
-
request@cs.ucl.ac.uk



or local.cs.gi10


or
4c58
-
request@cs.ucl.ac.uk


or local.cs.4c58

Useful Books


Alberts et al
-

Molecular Biology of
the Cell


Stryer
-

Biochemistry


Baldi and Brunak


Bioinformatics


a
machine learning approach


Durbin, Eddy, Krogh and Mitchison


Biological sequence analysis


Kanehisa
-

Post genome informatics


Lesk
-

Introduction to bioinformatics


Orengo, Jones and Thornton
-

Bioinformatics

The Course
-

motivation for
biological material


Modern molecular biology and
especially genomics has led to vast
quantities of data: DNA/ protein
sequence, gene expression.


This mainly consists of vast strings/
matrices of letters/ numbers, which in
their raw form are not very interesting.


What’s needed now is synthesis of data
and mining of data for patterns.


Intelligent systems techniques are very
good for extracting useful patterns.

Motivation


In order to extract useful information, it
is necessary to understand biological
principles involved.


In this course we will introduce some
basic molecular biology/ genomics and
look at ways in which computers can be
used to analyse it (bioinformatics), with
a particular focus on intelligent systems
techniques.

Course material content


I will give five three
-
hour blocks of
lectures towards the start of the course.


Prof. David Jones will give the rest of
the lectures.


Will now give a brief summary of the
content of my lectures and a very brief
one of his.


Content


Block 1: Biology


Introduction to course


Basic molecular biology


Cells, DNA, RNA, proteins, central dogma


Sequencing


Block 2: Genomics


History of genomics


Introduction to bioinformatics


Gene prediction

Content


Block 3: Microarrays


Microarray technology


Statistics


Analysis of microarray data


Block 5: Guest lectures (Systems
biology and Gene networks)


Intelligent systems and software for
systems biology (Dr. Peter Saffrey, UCL)


Bayesian networks (Dr. Lorenz Wernisch,
Birkbeck)


Reverse engineering of gene networks from
microarray data (Dr. Lorenz Wernisch)

Content


Block 8: Gene networks and
Computational biology


Continuation of analysis of microarray data


Signalling pathways


Reverse engineering of networks from
microarray data


Evolutionary games and evolutionary
algorithms (if time)



Content


Below is a
rough

outline of what
Prof. Jones will cover:

Blocks 4,6,7,9 & 10:


Gene finding and basic sequence
comparisons


Sequence comparisons; Hidden Markov
Models; proteins


Databases; agent technology


Protein structure; structure classification;
structure prediction


Protein structure prediction; drug discovery