Transcript Section 1 - Introduction to the Course

Intelligent systems in
bioinformatics
Introduction to the course
Contact details
Dr. Karen Page
Computer Science - Room G50a
Tel: 020 7679 3683 (internal: 33683)
Email: [email protected]
http://www.cs.ucl.ac.uk/staff/K.Page
Lecture format
• Monday and Thursday afternoons (25pm) – 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
• 15th 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 [email protected]
or local.cs.gi10
or [email protected]
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