Structural Bioinformatics Dr. Avraham Samson Course no.: Credit points: 1.5 Final grade is based on 10 assignments Course homepage:

2 Bioinformatics Definition: –“The collection, archiving, organization, and interpretation of biological data.” [Orengo, 2003] Etymology: - Bio- from “biology”, and –informatics from “information science”.

Bioinformatics 3 Sequence bioinformatics Structure bioinformatics Systems biology

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5 Structural Bioinformatics Focus on data sets with molecular structure

6 Structural Bioinformatics Motivation 1: Detailed understanding of molecular interactions

7 Structural Bioinformatics Motivation 2: Lots of structural data is becoming available

8 Outline of today’s lecture Overview of structural bioinformatics –Goals –Challenges –Applications Overview of course –Topics –Lectures –Assignments

9 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

10 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

11 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

12 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

13 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

14 Structural Bioinformatics Goals: Analysis Visualization Comparison Prediction Design

15 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

16 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

17 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

18 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

19 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

20 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

21 Structural Bioinformatics Research challenges: Structure prediction Binding site detection Binding site modeling Binding site matching Binding prediction Molecular design etc.

22 Structural Bioinformatics Applications: Biology Medicine Agriculture Industry etc.

Overview of course 23

24 y = f(x)  Biologists like experiments, specifics and classifications They like it better to know many (x i,y i ) – i.e., facts – and classify them, than to know f  Computer scientists like simulation, abstractions, and general algorithms They want to know f – the explanation of the facts – and efficient ways to compute it, but rarely care for any (x i,y i )  One challenge of Computational Biology is to fuse these two cultures The Shock of Two Cultures