Bioinformatics. Ingo Ruczinski. Some selected examples... and a bit of an overview

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1 Bioinformatics Some selected examples... and a bit of an overview Department of Biostatistics Johns Hopkins Bloomberg School of Public Health July 19, EnviroHealth Connections

2 Bioinformatics and Computational Biology Wikipedia: Bioinformatics and computational biology involve the use of techniques including applied mathematics, informatics, statistics, computer science, artificial intelligence, chemistry, and biochemistry to solve biological problems usually on the molecular level. Major research efforts in the field include sequence alignment, gene finding, genome assembly, protein structure alignment, protein structure prediction, prediction of gene expression and protein-protein interactions, and the modeling of evolution.

3 Bioinformatics and Computational Biology Wikipedia: The terms bioinformatics and computational biology are often used interchangeably. However bioinformatics more properly refers to the creation and advancement of algorithms, computational and statistical techniques, and theory to solve formal and practical problems inspired from the management and analysis of biological data. Computational biology, on the other hand, refers to hypothesis-driven investigation of a specific biological problem using computers, carried out with experimental or simulated data, with the primary goal of discovery and the advancement of biological knowledge.

4 Bioinformatics and Computational Biology NIH definition of Bioinformatics and Computational Biology: Bioinformatics and computational biology are rooted in life sciences as well as computer and information sciences and technologies. Both of these interdisciplinary approaches draw from specific disciplines such as mathematics, physics, computer science and engineering, biology, and behavioral science. Bioinformatics applies principles of information sciences and technologies to make the vast, diverse, and complex life sciences data more understandable and useful. Computational biology uses mathematical and computational approaches to address theoretical and experimental questions in biology. Although bioinformatics and computational biology are distinct, there is also significant overlap and activity at their interface.

5 Bioinformatics and Computational Biology NIH definition of Bioinformatics and Computational Biology: The NIH Biomedical Information Science and Technology Initiative Consortium agreed on the following definitions of bioinformatics and computational biology recognizing that no definition could completely eliminate overlap with other activities or preclude variations in interpretation by different individuals and organizations. Bioinformatics: Research, development, or application of computational tools and approaches for expanding the use of biological, medical, behavioral or health data, including those to acquire, store, organize, archive, analyze, or visualize such data. Computational Biology: The development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.

6 The central dogma of biology Drawn by Ebbe Sloth Andersen

7 Topics DNA RNA Protein DNA Sequence analysis, genome annotation, evolutionary biology, phylogeny, DNA alterations, comparative genomics, SNP association studies RNA Analysis of gene expression and regulation Proteins Analysis of protein expression, protein-protein docking, prediction of protein structure Systems Biology: modeling biological systems, gene/protein networks

8 Some selected examples 1 Chromosomal alterations 2 Protein structure prediction 3 2D gel electrophoresis

9 Some selected examples 1 Chromosomal alterations 2 Protein structure prediction 3 2D gel electrophoresis

10 Karyotypes

11 Trisomy

12 DNA changes

13 The data

14 Deletion

15 FISH

16 Amplification

17 Uniparental Isodisomy

18 Cancer samples

19 Mosaicism

20 SNPchip S4 classes and methods

21 Estimation 1 By SNP: Estimate genotype and copy number for each SNP. 2 Within a sample: Borrow strength between SNPs to infer regions of LOH and copy number changes. 3 Between samples: Comparison between normal and disease populations to find chromosomal alterations associated with disease.

22 Vanilla ICE Deletion Normal LOH Amplification A D B C E 2 1 Van ICE A D B E Van ICE Mb

23 A HapMap sample Deletion Normal LOH Amplification 1 Van ICE Van ICE Mb

24 Many HapMap samples

25 SNP Trio

26 HMM for SNP Trio chromosome 10 chromosome 22 BPI BPI UPI F UPI F UPI M UPI M MI D MI D MI S non BPI MI S non BPI BPI BPI position (Mb) position (Mb)

27 HMM for SNP Trio BPI UPI P UPI M MI D MI S HMM BPI UPI P UPI M MI D MI S HMM copy number child copy number child mother mother copy number copy number copy number father copy number father

28 Some selected examples 1 Chromosomal alterations 2 Protein structure prediction 3 2D gel electrophoresis

29 Proteins Amino acids are the building blocks of proteins.

30 Proteins Both figures show the same protein (the bacterial protein L). The right figure also highlights the secondary structure elements.

31 Proteins From Lehninger, Principles of Biochemistry

32 Functional Annotation

33 Genome Wide Annotation

34 Some selected examples 1 Chromosomal alterations 2 Protein structure prediction 3 2D gel electrophoresis

35 2D Gel Electrophoresis

36 2D Gel Electrophoresis

37 2D Gel Electrophoresis A B A:1 A:2 A:3 A:4 A:5 A:6 A:7 A:8 A:9 A:10 A:11 A:12 B:1 B:2 B:3 B:4 B:5 B:6 B:7 B:8 B:9 B:10 B:11 B:12

38 2D Gel Electrophoresis A B A:1 A:2 A:3 A:4 B:1 B:2 B:3 B:4

39 2D Gel Electrophoresis % reduction of concentration as compared to background st Trimester 3 rd Trimester 20 Folate Placebo

40 2D Gel Electrophoresis

41 2D Gel Electrophoresis

42 iruczins/

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