introduction to bioinformatics fall 2007-8 1: introduction
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Introduction to Bioinformatics
Fall 2007-8
1: Introduction
Teachers:Dr. Tal Pupko [email protected] Stern [email protected]
TA:Nimrod Rubinstein [email protected] Burstein [email protected] Doron [email protected]
Reception hours:by appointment. Britannia 405, 03-640-9245
1: Introduction
Administration
Course Website1: Introduction
http://bioinfo.tau.ac.il/~intro_bioinfo/
WHAT ARE THE QUESTIONS IN THE EXAMS?
Requirements1: Introduction
Final exam – 80% Exercises – 20%
Exercises that won’t be submitted on time will receive a grade of 0.
Do not copy!
Exercises
• Each student participates once in 2 weeks:Sunday 16:00-18:00or Monday 12:00-14:00
or
Monday 14:00-16:00
Computer classroom Sherman 03
1: Introduction
Goals
To familiarize the students with research topics in bioinformatics, and with bioinformatic tools
Prerequisites
• Familiarity with topics in molecular biology (cell biology and genetics)
• Basic familiarity with computers & internet
1: Introduction
Ask, Ask, Ask!!
"אין הביישן למד"
1: Introduction
What is Bioinformatics
• “The analysis of biological information using computers and statistical techniques; the science of developing and utilizing computer databases and algorithms to accelerate and enhance biological research “
www.niehs.nih.gov/dert/trc/glossary.htm
1: Introduction
What do bioinformaticians study?
• Bioinformatics today is part of almost every molecular biological research.
• Just a few examples…
1: Introduction
Example 1
• Compare proteins with similar sequences (for instance –kinases) and understand what the similarities and differences mean
1: Introduction
Example 2
• Look at the genome and predict where genes are (promoters; transcription binding sites; introns; exons)
1: Introduction
• Predict the 3-dimensional structure of a protein from its primary sequence
Example 3
Ab-initio prediction – extremely difficult!
1: Introduction
• Correlate between gene expression and disease
Example 4
A gene chip – quantifying gene expression in different tissues under different conditions
May be used for personalized medicine
1: Introduction
1: Introduction
Computational biology – revolutionizing science at the turn of the century.
Three studies using bioinformatics which impacted science
1. Classifying life into domains2. Predicting drug resistance in HIV
and personalizing drug administration
3. Solving the mystery of anthrax molecular biology
1: Introduction
Revolutionizing the Classification of Life
1: Introduction
•Life was classified as
plants and animals
•When Bacteria were discoveredthey were initially classified as plants.
•Ernst Haeckel (1866) placed all unicellular organisms in a kingdom called Protista, separated from Plantae and Animalia.
In the very beginning
1: Introduction
1: Introduction
Thus, life were classified to 5 kingdoms:
When electron microscopes were developed, it was found that Protista in fact include both cells with and without nucleus. Also, fungi were found to differ from plants, since they are heterotrophs (they do not synthesize their food).
LIFE
FungiPlants Animals ProtistsProcaryotes
1: Introduction
Later, plants, animals, protists and fungi were collectively called the Eucarya domain, and the procaryotes were shifted from a kingdom to be a Bacteria domain.
Domains EucaryaBacteria
FungiPlants Animals ProtistsKingdoms
Even later, a new Domain was discovered…
1: Introduction
•The translation apparatus is universal and probably already existed in the “beginning”.
rRNA was sequenced from a great number of organisms to study phylogeny
1: Introduction
Carl R. Woese and rRNA phylogeny1: Introduction
A distance matrix was computed for each two organisms. In a very influential paper, they showed that methanogenic bacteria are as distant from bacteria as they are from eucaryota (1977).
1: Introduction
One sentence about methanogenic “bacteria”
“There exists a third kingdom which, to date, is represented solely by the methanogenic bacteria, a relatively unknown class of anaerobes that possess a unique metabolism based on the reduction of carbon dioxide to methane”.
These "bacteria" appear to be no more related to typical bacteria than they are to eucaryotic cytoplasms.“
1: Introduction
From sequence analysis only, it was thus established that life is divided into 3:BacteriaArchaeaEucarya
1: Introduction
1: Introduction
The rRNA phylogenetic tree
Revolutionizing HIV treatment
1: Introduction
There are very efficient drugs for HIV
1: Introduction
A few viruses in blood
DRUG, +a few more days
Many viruses in blood
DRUG, +a few days
Many viruses in blood
Explanation: the virus mutates and some viruses become resistant to the drug.
Solution 1: combination of drugs (cocktail).
Solution 2: not to give drugs for which the virus is already resistant. For example, if one was infected from a person who receives a specific drug.
The question: how do one knows to which drugs the virus is already resistant?
1: Introduction
Sequences of HIV-1 from patients who were treated with drug A:
AAGACGCATCGATCGATCGATCGTACGACGACGCATCGATCGATCGATCGTACGAAGACACATCGATCGTTCGATCGTACG
Sequences of HIV-1 from patients who were never treated with drug A:AAGACGCATCGATCGATCGATCTTACGAAGACGCATCGATCGATCGATCTTACG AAGACGCATCGATCGATCGATCTTACG
1: Introduction
drug A+AAGACGCATCGATCGATCGATCGTACGACGACGCATCGATCGATCGATCGTACGAAGACACATCGATCGTTCGATCGTACG
drug A-AAGACGCATCGATCGATCGATCTTACGAAGACGCATCGATCGATCGATCTTACG AAGACGCATCGATCGATCGATCTTACG
This is an easy example.
1: Introduction
drug A+AAGACGCATCGATCGATCGATCGTACGACGACGCATCGATCGATCGATCGTACGAAGACACATCGATCATTCGATCATACG
drug A-AAGACGCATCGATCTATCGATCTTACGAAGACGCATCGATCTATCGATCTTACG AAGACGCATCGATCAATCGATCGTACG
This is NOT an easy example. This is an example of a classification problem.
1: Introduction
1: Introduction
2006: Five machine learning tools were compared:•Decision trees•Linear regression•Linear discriminant analysis•Neural networks•Support vector regression
~80% accuracy
1: Introduction
Revolutionizing our understanding of the anthrax molecular mechanism
1: Introduction
•Anthrax is a disease whose causative agent is the gram positive Bacillus anthracis.
•It infects mainly cattle, swine, and horses but it can also infect humans.
•Humans are infected from milk or meat from infected animals.
•In humans it causes skin problems, in cattle – fatal blood poisoning.
1: Introduction
•A vaccine was found by Pasteur.
•Koch was the first to isolate the bacterium.
•Airborne anthrax, such as that induced by weaponized strains used forbioterrosrism is almost always fatal in humans (respiratory distress, hemorrhage).
1: Introduction
How does the bacterium Bacillus anthracis work?It secretes three proteins: protective antigen (PA), edema factor (EF), and lethal factor (LF).
PA monomer first binds to a host-cell surface receptor. This binding triggers proteolytic cleavage (a part of the N terminus is cut out).
The (remaining) PA monomers oligomerize, forming heptamers.
1: Introduction
LF and EF bind the heptamer and the entire complex is internalized into an endosome.
The acidity in the endosome causes a conformational change in the complex, thus it penetrates the endosome membrane and forms a pore.
The story continues…
1: Introduction
Researchers from the group of David Baker wanted to know how LF and EF bind to the heptameric PA. They used a method called docking…
1: Introduction
This is where the two proteins interact!
1: Introduction
Once they had a prediction, they performed mutagenesis experiments. Changing residues in the predicted interface cancelled the binding.
1: Introduction
How does docking work? Each 3D conformation is given a score. The pair with the best score is chosen.
1: Introduction
Challenges: what is the best score?How to go over as many conformations as possible?How to take into account that proteins are flexible?
Gregor Mendellaws of inheritance,“gene”1866
Watson and Crick
DNA Discovery 1953
Genome
Project 2003
1: Introduction
Genome
Project 2003
1: Introduction
1: Introduction
)Slide from Prof. Ron Shamir(
BioinformaticsBioinformatics
• Organize, store, analyze, visualize genomic data • Utilizes methods from Computer Science,
Mathematics, Statistics and Biology
The marriage of Computer Science and Biology
1: Introduction
)Slide from Prof. Ron Shamir(
• At the convergence of two revolutions: the ultra-fast growth of biological data, and the information revolution
Biology is becoming an information science
22 Aug 2005:100,000,000,000 bases
1: Introduction Bioinformatics)Slide from Prof. Ron Shamir(
Bioinformatics – a short CV
• Born ~1990• Grown rapidly.• Experience: essential part of modern life
science and medicine• Now a separate multidisciplinary scientific
area• Is one of the cornerstones of 21st Century
medical and biological research
1: Introduction
)Slide from Prof. Ron Shamir(
1: Introduction
•Academic research: where it all started•Biotechnology companies•Big Pharmas and big AgBio•National and international centers
The Bioinformatics Actors
Find me gene (gin?)
Bioinformatics in Israel
• World class player in research
• Ranked 2-3 in absolute number of papers in the most prestigious and competitive conferences
• Maintaining our competitive global position is nontrivial
1: Introduction )Slide from Prof. Ron Shamir(
Bioinformatics in TAU
• TAU is the Israeli leader in the field…
1: Introduction
)Slide from Prof. Ron Shamir(