The use of databases in bioinformatics

1
The use of databases in bioinformatics

• Rebecca Ward
• Research Rotation Presentation
• Graduate Program in Biomedical Sciences
• 11-16-2005

2
Evolution of Biological Information

• Historically, study of overall structures
• In the last 50 years, more molecular in nature
• Molecular Structure
• Molecular Function

3
What is Bioinformatics?

• Organization of biological data for easier
• Searching
• Analysis
• Interpretation

4
Why databases?

• Very complex data is generated
• Need a method of interpreting data for those who
  cannot directly analyze it

5
Some Common Databases

• European Molecular Biology Laboratory
• http//www.ebi.ac.uk/Information/
• DNA Database of Japan
• http//www.ddbj.nig.ac.jp/
• Discover http//discover.nci.nih.gov/
• Oncomine 3.0 http//www.oncomine.org/main/in
  dex.jsp
• Gene Expression Omnibus http//www.ncbi.nlm.ni
  h.gov/geo/
• CGAP/SAGE
• http//cgap.nci.nih.gov/

6
EMBL and DDBJ
Collaborative effort with NCBI GenBank
Searchable databases of gene information
7
EMBL

• Gene Expression and Protein Sequences
• UniProt Knowledgebase
• A complete annotated protein sequence database
• Macromolecular Structure Database
• European Project for the management and
  distribution of data on macromolecular structures
  
• ArrayExpress
• Gene expression data
• IntAct
• Provides a freely available, open source database
  system and analysis tools for protein interaction
  data

8
DDBJ

• Tools to compare nucleic acid sequences and amino
  acid sequences
• Fasta, blastn, tblastx
• nucleotide nucleotide
• Fastx and blastx
• nucleotide amino acid
• Tfasta, tfastx,blastp, tblastn
• amino acid nucleotide

9
Discover

• Contains various tools for analyzing microarray
  data
• Has tools for biological literature searches
  related specific genes or drugs

10
Discover Tools

• High Throughput GoMiner
• multiple drug treatments
• multiple gene knockouts
• multiple lead compounds for potential drugs
• MedMiner
• Searching of biological literature
• Gene
• Gene gene
• Gene Drug

11
MedMiner
12
(No Transcript)
13
Oncomine

• Allows analysis of gene expression
• Differential Expression data

14
Oncomine
15
Gene Expression Omnibus (GEO)

• Storage of data found in microarray experiments
• Can be searched via
• gene (Gene Profiles)
• study (DataSets)
• GEO accession number

16
How to Use GEO
17
AFAP (GEO)
18
CGAP
19

• Gene Finder
• Anatomical Viewer
• Digital Gene Expression Database

20
CGAP Gene Finder
21
AFAP Gene Info
22
AFAP Expression SAGEAnatomical Viewer
23
SAGE GDED
24
When results are displayed, click on full text to
generate list below
This list can be searched using the Find function
(CtrlF)
25
My Goals in Dr. Guos Lab

• Learn general information about databases
• Generate differential expression data for genes
  expressed in normal versus cancerous tissues
• Collaboration with Dr. Flynn to determine
  differential expression of AFAP

26
Data Generated SAGE
27
MAPK Expression in Breast Cancer
28
AFAP Expression SAGEAnatomical Viewer
29
AFAP Oncomine
30
Quantitative Expression
31
Summary

• Importance of biological databases
• Availability of Databases to Public
• Data generated by database analysis

32
References

• Allen JE, Salzberg SL. JIGSAW integration of
  multiple sources of evidence for gene prediction.
  Bioinformatics 21(18) 2005.
• Barrett T, Suzek TO, Troup DB, Wilhite SE, Ngau
  WC, Ledoux P, Rudnev D, Lash AE, Fujibchi W,
  Edgar R. NCBI GEO mining millions of expression
  profiles-database and tools. Nucleic Acids
  Research 33, 2005.
• Beerenwinkel N, Sing T, Lengauar T, Rahnenfuhrer
  J, Roomp K, Savenkov I, Fischer R, Hoffman D,
  Selbig J, Korn K, Walter H, Berg T, Braun P,
  Fatkenheuer G, Oette M, Rocksrtoh J, Kupfer B,
  Kaiser R, Daumer M. Computational methods for the
  design of effective therapies against drug
  resistant HIV strains. Bioniformatics 21(21)
  2005.
• Bueler, Lukas K and Hooman H Rashidi.
  Bioinformatics Basics Applications in Biological
  Science and Medicine. Boca Raton, FL, CRC Press
  2005.
• Dinel S, Bolduc C, Belleau P,Boivin A, Yoshioka
  M, Calvo E, Peidboeuf B, Snyder EE, Labrie F,
  St-Amand J. Reproducibility, bioinformatics
  analysis and power of the SAGE method to evaluate
  changes in transcriptome. Nucleic Acids Research
  33(3) 2005.
• Fox JA, Butland SL, McMillan S, Campbell G,
  Ouelette BFF. The Bioinformatice Link Directory
  a compilation of molecular biology web servers.
  Nucleic Acids Research 33 2005.
• Kendziorski C, Irizarry RA, Haag JD, Gould MN. On
  the utility of pooling biological samples in
  microarray experiments. PNAS 102(12) March 22,
  2005.
• Margulies EH, Kardia LR, Innis JW. Identification
  and prevention of GC content bias in SAGE
  libraries. Nucleic Acids Research, 29(12) 2001.
• Martin LC, Gloor GB, Dunn D, Wahl LM. Using
  information theory to search for co-evolving
  residues in proteins. Bioinformatics 21(22) 2005.
• Yuting Y, Engin L, Wurtele ES, Cruz-Neira C,
  Dickerson JA. Integration of metabolic Networks
  and gene expression in virtual reality.
  Bioinformatics 21(18) 2005.