Introduction to Bioinformatics Lecturer: Prof. Yael Mandel-Gutfreund Teaching Assistance: Rachelly Normand Alona Rabner Course web site : http://webcourse.cs.technion.ac.il/236523

What is Bioinformatics?

Course Objectives To introduce the bioinfomatics discipline To make the students familiar with the major biological questions which can be addressed by bioinformatics tools To introduce the major tools used in the field

Course Structure and Requirements Class Structure 2 hours lecture 1 hour tutorial 2. Home work Homework assignments will be given every second week The homework will be done in pairs. 4/4 homework assignments will be submitted+ Project proposal 2. A final project will be conducted in pairs * Project will be presented as a poster –poster day 22.3

Grading 20 % Homework assignments 80 % final project (10% proposal, 20% supervisor evaluation 70% poster presentation)

What is Bioinformatics?

What is Bioinformatics? “The field of science in which biology, computer science, and information technology merge to form a single discipline”

Central Paradigm in Molecular Biology Gene (DNA) mRNA Protein 21ST centaury Genome Transcriptome Proteome

Information explosion in biology Human genome length =3*109

The revolution in molecular biology High Throughput Technologies -Next Generation DNA sequencing > Whole genomes sequencing -Metagenomics >Sequencing DNA from the environment -Microbiome Analysis > Sequencing microbial communities -Microrrays/RNA sequencing > RNA expression analysis - Chip-seq > protein-DNA interactions - CLIP-seq > Protein-RNA interactions - Mass Spectrometry > Protein Expression analysis

Building models from parts lists Lazebnik, Cancer Cell, 2002

Building models from parts lists

Computational tools are needed to distill pathways of interest from large molecular interaction databases Thinking computationally about biological process may lead to more accurate models, which in turn can be used to improve the design of algorithms Navlakha an Bar-Joseph 2011

What do we do in Bioinformatics? - Analyze and interpret the various types of biological data: Genomic Sequences (DNA) Transcriptomic Sequences (RNA) Proteomic sequences (Proteins) Protein Structures (Proteins) RNA structure (RNA) Develop new algorithms and tools To assess the biological information, Handel large datasets, find relationships between data sources etc…

What of all this will we learn in the course? > Pairwise and multiple alignment > Database search > Protein alignments > DNA Sequencing > Gene expression/ Clustering analysis > Phylogenetic analysis > Motif search > Structural bioinformatics (RNA and proteins) > Biological networks

Manny different applications.. Basic Science Main Goal: Understand the living cell Find the function of a new protein Find the genes/proteins that are unique to human Medical applications - Identify the mutations (SNPs) that cause genetic diseases - Diagnosis ..find the features that characterize disease states - Find and develop new and better drugs ….. Agriculture applications Higher yield crop Increase shelf life ……

Find the function of a new protein Basic Science Find the function of a new protein -Database search

Discover Function of a new protein

Find the genes/proteins that are unique to human Basic Science Find the genes/proteins that are unique to human -Phylogenetic analysis

How can we be so similar--and yet so different? Perhaps not surprising!!! How humans are chimps? Comparison between the full drafts of the human and chimp genomes revealed that they differ only by 1.23% How can we be so similar--and yet so different?

Where are we different ?? Where are we similar ??? VERY SIMAILAR Conserved between many organisms VERY DIFFERENT

Identify the mutations (SNPs) that cause genetic diseases Medical applications Identify the mutations (SNPs) that cause genetic diseases -Pairwise and multiple alignments -DNA sequencing

Due to 1 swapping of an A for a T Sickle Cell Anemia Due to 1 swapping of an A for a T

Healthy Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGAGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTPEEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

Diseased Individual >gi|28302128|ref|NM_000518.4| Homo sapiens hemoglobin, beta (HBB), mRNA ACATTTGCTTCTGACACAACTGTGTTCACTAGCAACCTCAAACAGACACCATGGTGCATCTGACTCCTGA GGTGAAGTCTGCCGTTACTGCCCTGTGGGGCAAGGTGAACGTGGATGAAGTTGGTGGTGAGGCCCTGGGC AGGCTGCTGGTGGTCTACCCTTGGACCCAGAGGTTCTTTGAGTCCTTTGGGGATCTGTCCACTCCTGATG CTGTTATGGGCAACCCTAAGGTGAAGGCTCATGGCAAGAAAGTGCTCGGTGCCTTTAGTGATGGCCTGGC TCACCTGGACAACCTCAAGGGCACCTTTGCCACACTGAGTGAGCTGCACTGTGACAAGCTGCACGTGGAT CCTGAGAACTTCAGGCTCCTGGGCAACGTGCTGGTCTGTGTGCTGGCCCATCACTTTGGCAAAGAATTCA CCCCACCAGTGCAGGCTGCCTATCAGAAAGTGGTGGCTGGTGTGGCTAATGCCCTGGCCCACAAGTATCA CTAAGCTCGCTTTCTTGCTGTCCAATTTCTATTAAAGGTTCCTTTGTTCCCTAAGTCCAACTACTAAACT GGGGGATATTATGAAGGGCCTTGAGCATCTGGATTCTGCCTAATAAAAAACATTTATTTTCATTGC >gi|4504349|ref|NP_000509.1| beta globin [Homo sapiens] MVHLTPVEKSAVTALWGKVNVDEVGGEALGRLLVVYPWTQRFFESFGDLSTPDAVMGNPKVKAHGKKVLG AFSDGLAHLDNLKGTFATLSELHCDKLHVDPENFRLLGNVLVCVLAHHFGKEFTPPVQAAYQKVVAGVAN ALAHKYH

Diagnosis ..find the features that characterize disease states Medical Applications Diagnosis ..find the features that characterize disease states -Gene expression/clustering analysis -Motif search

Samples were taken from patients with adenocarcinoma. hundreds of genes that differentiate between cancer tissues in different stages of the tumor were found. The arrow shows an example of a tumor cells which were not detected correctly by histological or other clinical parameters. Ramaswamy et al, 2003 Nat Genet 33:49-54

Find and develop new and better drugs Medical applications Find and develop new and better drugs -DNA sequencing -Gene expression -Structural Bioinformatics -Biological networks

Bioinformatics can dramatically reduce the cost and time for developing a new drug Putative drug-target candidates Billions of $ Pre-discovery Discovery VALIDATION Clinical trials Approval Envisagenics Inc.

Bioinformatics can dramatically reduce the cost and time for developing a new drug Putative drug-target candidates Pre-discovery Discovery VALIDATION Clinical trials Approval Millions of $ Good putative drug-target candidates Envisagenics Inc.

Keats (1795-1821) Kafka (1883-1924) Orwell (1903-1950) Mozart (1756-1791) Schubert (1797-1828) Chopin (1810-1849)

Did you know? Infectious diseases are still number 1 cause of premature death (0-44 years of age) worldwide. Annually kill >13 million people (~33% of all deaths)

The ribosome is a target for approximately half of antibiotics characterized to date Antibiotics targets of the large ribosomal subunit

Using bioinformatics to find new target sites on the ribosome Bad site Good site

Manny different applications.. And beyond… Personalized medicine

How can bioinformatics contribute to Medicine? http://www.tedmed.com/talks/show?id=17961 MAKE THE DATA WORK FOR US