The document outlines the importance and structure of various biomedical databases relevant to genomics research, including types of databases, data submission processes, and tools for database exploitation. It details the roles of major data providers like NCBI and EBI, along with examples of nucleotide, genome, protein, and microarray databases. Additionally, it discusses the bioinformatics methods for data analysis and searching within these databases.

1. Hospital Universitari Vall d’Hebron
Institut de Recerca - VHIR
Institut d’Investigació Sanitària de l’Instituto de Salud Carlos III (ISCIII)
Bioinformàtica per la
Recerca Biomèdica
http://ueb.vhir.org/2014BRB
Alex Sánchez
alex.sanchez@vhir.org
13/05/2014
STORING AND ACCESSING INFORMATION
DATABASES AND QUERIES

2. 1. Data banks and databases
● Information in the genomics era
● Distinct DB usages
● To take into account
● Main resources providers
2. Types of databases
● EMBL vs NCBI
● Bibliography DB
● Taxonomy DB
● Nucleotide DB
● Genome DB
● Protein DB
● Microarray DB
● Other DB
● Lists of DB
PRESENTATION OUTLINE
213/05/2014
3. Structure and formats of the databases
● Structure of the DB
● Formats of the DB
● Sequence FASTA format
● GenBank entry example
● EMBL entry example
4. Submitting data
● Submitting sequences
● Submitting expression data
5. Tools for DB exploitation
● ENTREZ
● Cross-search tables
● Entrez queries
● Entrez fields
● Help system

3. Data banks and databases
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4. INFORMATION IN THE GENOMICS ERA
4
• Genomics era: huge amount of
data
• To be able to use this information,
it should be properly stored
• The access to that info
– Must be quick
– Has to be done in a flexible way
• That is possible thanks to the
– Creation of databases
– It’s online availability
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5. DISTINCT DB USAGES
5
• Information search
– By keyword, accession number, authors…
• Homology search
– Is there any sequence identical or similar to that mine?
• Pattern search
– Has my sequence any known pattern?
• Predictions
– Can I find proteins, with already known function, similar to
mine?
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6. Bioinformatics reagent: Databases
Organized array of information
Place where you put things in, and (if all is well)
you should be able to get them out again.
Resource for other databases and tools.
Simplify the information space by specialization.
Bonus: Allows you to make discoveries.
Important question to ask:
what is the data model?

7. 7
Bioinformatics experiments:
BLAST searchSequence Alignment
Reagents:
•Sequence
•Databases
Method:
•P-P BLASTP
•N-P BLASTX
•P-N TBLASTN
•N-N BLASTN
•N (P) – N (P) TBLASTX
Interpretation:
•Similarity
•Hypothesis testing
Know
your reagents
Know
your methods
Do your controls

8. 8
Nature 409:452
Bioinformatics Citizenship: What it means,
and what does it cost?

9. Databases
Information system
Query system
Storage System
Data

10. Databases
Information system
Query system
Storage System
Data
GenBank flat file
COSMIC record
Interaction Record
Title of a book
Book

11. Databases
Information system
Query system
Storage System
Data
Boxes
Oracle
MySQL
PC binary files
Unix text files
Bookshelves

12. Databases
Information system
Query system
Storage System
Data
A List you look at
A catalogue
indexed files
SQL
grep

13. The library of Congress
Google
Entrez
EnsEMBL
UCSC gemome browser
Databases
Information system
Query system
Storage System
Data

14. TO TAKE INTO ACCOUNT
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Information organization
Resources providers Databases Tools
Organizations or centers devoted to the
offer and maintain the databases
To find/check/export information into/from DB
Diverse and very different information

15. MAIN RESOURCES PROVIDERS
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• The National Center for Biotechnology Information
(NCBI) offers data banks, databases and tools at the
USA
• The European Bioinformatics Institute (EBI) does a
similar function in Europe
• GenomeNet gathers several databases from Japan

16. Types of databases
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17. TYPES OF DB
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• There are hundreds of BD, so it is not feasible to
enumerate them (but they have tried here)
• We can classify them by multiple criteria
• The structural organization of the EMBL and the
NCBI resources is radically different

18. EMBL vs NCBI
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• EMBL
– Bibliographic DB
– Taxonomic DB
– Nucleotide DB
– Genomic BD
– Protein BD
– Microarrays DB
…
• NCBI
– PubMed
– Entrez
– OMIM
– Books
– TaxBrowser
– Structure
…

19. BIBLIOGRAPHY DB
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• Collection of papers published in
scientific journals
– Pubmed (NCBI)
– Medline (EBI)
– Biocatalog: papers organized by
concrete molecular biology topics

20. TAXONOMY DB
2013/05/2014
• Information on the
classification of living things
– basically hierarchical
– and based on molecular
evidences
• To classify any organism
from which at least one
nucleic acid sequence has
been determined
• There is indeed some
controversy in the scientific
community

21. NUCLEOTIDE DB
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• Sequences from experimental laboratories
• Daily updated
• Daily exchanging of its contents
– Genbank (NCBI)
– EMBL (EBI)
– KEGG (Genome net)

22. Sequences NOT in NucleotideDB
• WGS: whole genome shotgun
• TPA: third party annotations
• SNPs
• SAGE tags (serial analysis of gene expression)
• RefSeq (Genomic, mRNA, or protein)
• Consensus sequences

23. GENOME DB
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• Sequences and annotations of
whole genomes
– Ensembl (EBI)
– Genome viewer (NCBI)
– Goldenpath (UCSC)
• Specialized genomic resources
– Transfact
– EST
– UTRDB
– SpliceSitesDB
…

24. PROTEIN DB (I)
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• Aminoacids primary
sequences
– Without human revision
• Trembl (EBI)
• NR (NCBI)
– With annotation’s curation
• Uniprot (EBI)
– Proteome DB
• Proteome analysis (EBI)

25. PROTEIN DB (II)
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• Secondary structures or protein domains
• They depend on the protein source and the analysis
perfomed on them
– PROSITE: Regular Expressions over Swiss-Prot
– PRINTS: Set of motifs that define a family over Swiss-
Prot/TrEMBL
– BLOCKS: Aligned motifs from PROSITE/PRINTS
– PFAM: Markov Modelos over Swiss-Prot
– INTERPRO: Integrates information from several domain-
focused data bases.

26. PROTEIN DB (III)
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• 3D structures with coordinates
of each atom
– PDB: Reference protein 3D
structure (x-ray, NMR) database
– CATH: Classification of the PDB
in different functional and
structural groups
– MMDB: subset de PDB
maintained by the NCBI
– MSD: subset of the PDB
maintained by the EBI

27. MICROARRAY DB
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• Expression arrays results
– ArrayExpress
– caArray
– Gene Expression Omnibus

28. OTHER DB (1)
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• Biological Annotations
– Gene Ontology
– KEGG
– Gene Cards
• Therapeutic targets
– Therapeutic targets database
– PharmGKB
…

29. Historical perspective on the Human
Genome Data
Human Expressed Seq Tags (mRNA) sequencing
Human genome mapping and sequencing
Population analysis and polymorphism measurements
Genome Wide Association Studies
<the Homer paper>
The Cancer Genome Atlas pilot
The 1000 genome project
The Cancer Genome Atlas
The International Cancer Genome Consortium

30. • Detailed Phenotype and Outcome data
• Region of residence
• Risk factors
• Examination
• Surgery
• Drugs
• Radiation
• Sample
• Slide
• Specific histological features
• Analyte
• Aliquot
• Donor notes
• Gene Expression (probe-level data)
• Raw genotype calls
• Gene-sample identifier links
• Genome sequence files
ICGC Controlled
Access Datasets
• Cancer Pathology
Histologic type or subtype
Histologic nuclear grade
• Patient/Person
Gender
Age range
• Gene Expression (normalized)
• DNA methylation
• Genotype frequencies
• Computed Copy Number and
Loss of Heterozygosity
• Newly discovered somatic variants
ICGC OA
Datasets
http://goo.gl/w4mrV
Main source of Cancer Data: ICGC

31. http://dcc.icgc.org/

32. Module 2a bioinformatics.ca

33. Another source of important Cancer Data:
:
http://www.sanger.ac.uk/genetics/CGP/cosmic/

34. Module 2a bioinformatics.ca
What is Cancer Data?
Structured Clinical Data about the patient
Structured Clinical Data about the treatment
Structured Clinical Data about the tumor
Associated with a number of
positions (hundreds, if not
thousands) of nucleotide
coordinate system on one
reference genome.

35. ICGC is implementing NCBI’s bioprojects
http://www.ncbi.nlm.nih.gov/bioproject

36. LISTS OF BD
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Nucleic Acids Research Database Listing
– Annual Database issue
http://www.oxfordjournals.org/nar/database/c/
– Suplement that comes with each year’s January issue
– 2009 2013 describes 179 1512 databases, sorted into 14
categories and 41 subcategories.
– They ara added to the list of Nucleic Acids Research
online Molecular Biology Database Collection
– Good starting point for selecting the appropriate DB

37. LISTS OF BD
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38. Structure and formats
of the DB
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39. STRUCTURE OF THE DB
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• The way of organizing data in any DB
depends mainly in the model or architecture
in which it is based on
• There are multiple models
Relational, Hierarchical, Network-based…
but the most usual relational
– Several tables, that could have relationships
between them
– The relationships are done through key fields

40. FORMATS OF THE DB
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• To work with relational DB implies the use of
plane data formats
– Text files
– Some kind of labels to specify the contents of
every line or region of the file
• There are multiple formats, so a good
program or application should be able to
recognize (and even interchange) them.

41. SEQUENCE FASTA FORMAT
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Identifier Additional info
sequence
1stline
>gi|15341523|gb|AF405321.1| Human echovirus 29 strain JV-10 5' UTR, partial
sequence CAAGCACTTCTGTTTCCCCGGACTGAGTATCAATAGACTGCTCACGCGGTTGAAGGAGAAAACGTTCGTT
ATCCGGCCAACTACTTCGAGAAACCTAGTAACGCCATGGAAGTTGTGGAGTGTTTCGCTCAGCACTACCC
CAGTGTAGATCAGGTTGATGAGTCACCGCATTCCCCACGGGTGACCGTGGCGGTGGCTGCGTTGGCGGCC
TGCCCATGGGGAAACCCATGGGACGCTCTTATACAGACATGGTGCGAAGAGTCTATTGAGCTAGTTGGTA
GTCCTCCGGCCCCTGAATGCGGCTAATCCCAACTGCGGAGCATACACTCTCAAGCCAGAGGGTAGTGTGT
CGTAATGGGCAACTCTGCAGCGGAACCGACTACTTTGGGT
>gi|15341527|gb|AF405325.1| Human echovirus 6 strain D' Amori 5' UTR, partial
sequence
CAAGCACTTCTGTTTCCCCGGACCGAGTATCAATAAGCTGCTCACGCGGCTGAAGGAGAAAGTGTTCGTT
ACCCGGCTAGTTACTTCGAGAAACCTAGTACCACCATGAAGGTTGCGCAGCGTTTCGCTCCGCACAACCC
CAGTGTAGATCAGGTCGATGAGTCACCGCGTTCCCCACGGGCGACCGTGGCGGTGGCTGCGTTGGCGGCC
TGCCCATGGGGCAACCCATGGGACGCTTCAATACTGACATGGTGCGAAGAGTCTATTGAGCTAACTAGTA
GTCCTCCGGCCCCTGAATGCGGATAATCTTAACTGCGGAGCAGGTGCTCACAATCCAGTGGGTGGCCTGT
CGTAACGGGCAACTCTGCAGCGGAACCGACTACTTTGGGT

42. GENBANK ENTRY EXAMPLE
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43. EMBL ENTRY EXAMPLE
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44. Submitting data
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45. SUBMITTING DATA
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• Several biological databases are public, so
any (properly identified) user can contribute
uploading new data
• There are multiple types of data to upload,
but the most usual are
– Sequencies
– Expression data (from microarrays)

46. SUBMITTING SEQUENCES
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How to submit your sequences to…
• EMBL
– http://www.ebi.ac.uk/embl/Submission/
• GeneBank
– http://www.nlm.nih.gov/pubs/factsheets/sdgenbk.html

47. SUBMITTING EXPRESSION DATA
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And your expression data to…
• ArrayExpress (EBI)
– http://www.ebi.ac.uk/microarray/submissions.html
• Gene Expression Omnibus (NCBI)
– https://www.ncbi.nlm.nih.gov/geo/info/faq.html

48. Tools for DB exploitation
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49. ENTREZ
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• It is the NCBI’s searching system
• Great power and versatility, but less intuitive
than SRS
• It doesn’t provide forms for each field
• Usually used in a “Top Bottom” manner
– Perform a first query
– Refine the results until reaching what you are
looking for.

50. CROSS-SEARCH TABLES
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51. ENTREZ QUERIES
5113/05/2014
• Boolean operators: AND, OR, NOT, “”, *
• AND applied by default
• Query by Accession Numbers (AC) in
– Genbank / EMBL / DDBJ:
• 1 char. + 5 nums. (U12345)
• 2 char. + 6 nums. (AF123456)
– SwissProt / PIR:
• 1 char. + 5 nums. (P12345)
• Refine queries with the reserved word LIMITS
• Combine queries with HISTORY

52. ENTREZ AVAILABLE FIELDS
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53. HELP AND INFORMATION SYSTEM
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54. Estamos interesados en el gen MLH1 humano, implicado en el cáncer de
colon
– Separar el grano de la paja: identificar una secuencia de mRNA
representativa y bien anotada del gen MLH1.
– Obtener literatura asociada y su secuencia protéica.
– Identificar proteínas similares.
– Identificar dominios conservados dentro de la proteína.
– Identificar mutaciones conocidas en el gen o la proteína.
– Encontrar la estructura tridimensional de la proteína, si esta es
conocida, o si no es así, identificar estructuras de secuencia homóloga.
– Ver el contexto genómico del gen y descargar la región que lo contiene.
Vall d'Hebron Institut de Recerca 21/06/2011
Ejemplos de búsqueda con Entrez

55. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta directa (1.1)

56. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta directa (1.2) Límites

57. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta directa (1.3) Filtros

58. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta directa (1.4) Registro

59. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (2) Enlaces a otras BD

60. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (3) Secuencias

61. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (4) Proteína

62. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (5.1) Mutaciones

63. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (5.2) SNPs

64. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (5.3) OMIM

65. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (6.1) Estructuras

66. Mouse over the residues of NP_000240 until the grey footer bar shows ‘gi
4557757, loc 67’ (Glycine). Click on the corresponding Glycine residue in
1H7U_A (loc 74) to highlight it.
In the structure window use the left mouse button to spin the 3D structure until
you can clearly see and identify the highlighted residue. Is it possibly in
the active site? For example, is it within 5 Ä of the ATPS molecule?
Double click on the Mg-complexed ATPS to highlight it. Then use the menu bar
option called ‘Show/Hide|Select By Distance|Residues Only’ to highlight
all residues within 5 Ä of the ATPS. Indeed, the Glycine at position #74 is
within 5 Ä and is likely part of the active site for this energy-producing
domain. This hints at the possible problems a Gly  Trp mutation might
cause at that position.
Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (6.2) Alineamiento de secuencia y
estructura

67. Vall d'Hebron Institut de Recerca 21/06/2011
Consulta (7) Visualización en contexto
genómico