Features of Biological Database

1. Submitted by: SOMBIR SINGH
Research Scholar
Center for Biotechnology
MD University Rohtak Haryana
sombirkumar9195@gmail.com

2. BIOLOGICAL DATABASE
 A collection of data that is structured, searchable,
updated periodically and cross-referenced.
 Store biological data in electronic form
 Purpose-
systemization of database
availability of biological data
analysis of computed biological data

3. FEATURES OF BIOLOGICAL
DATABASE
 Heterogeneity
 High volume data
 Uncertainity
 Data curation
 Data integration
 Data sharing
 Dynamics

4. 1. Data heterogeneity
Availabilty of diverse and complex data types.
Data types:
 sequence- nucleotide, protein
 graph- data indicating relationship among
themselves can be captured as graph. It include
pathway data, genetic maps and structural texonomy.

5.  high dimensional data- data generated from micro-
array experiments that involve thousands of genes and
hundreds of experimental conditions.
 shapes- consists of 3D molecular structural data.
 temporal data- for studing dynamics of any
biological system. Example- development biology.

6.  Patterns- there are patterns lying within the genome
that characterize biologically entities. example-
regulatory sequence
 Scalar and vector fields
 Extracted features data- numerical data obtained
from combination of one of the above mentioned data
types.

7. 2. High volume data- in addition to being highly
heterogeneous, biological data are voluminous to
support comprehensive investigations in various field
and directions.
3. Uncertainity- biological data have great deal of
uncertainity as they represent biological phenomena
that are observed and assumed.

8. 4. Data curation- biological data collected from various
sources across different and functional boundaries.
 There are always chances of missing links.
 To fill these, the data is analyzed and curated via
automated methods.

9. 5. Data integration- after years of research, across
different structural and functional scales, data is
collected from laboratories through a database and
made available for use.

10. 6. Data sharing- biological data is share via databases.
 Purpose:
for scientific community’s inspection
for cross verification
to prevent repetition and validation of data

11.  Dynamics-
new data is generated every day in laboratories.
sometimes this new data contradicts with the old data
so, it is necessary to develop new organizational
database schemes to incorporate new data.

13. Classification of biological
databases
 Data type
 Maintainer status
 data access
 Data source
 Database design
 Organism

14. 1. Data type
 Sequence database
a. nucleotide database: GenBank, EMBL BANK
b. Protein database: Swiss-Prot, PIR
 Structure database: PDB, NDB, DALI, MSD
 Microarray database: ArrayExpress
 Chemical database: PubChem
 Pathway database: KEGG, BioSilico
 Enzyme database: REBASE, ExPASy
 Disease database: OMIM
 Literature database: PubMed

16. 2. Maintainer status
 NCBI, EMBL
 Academic group or scientist
 Commercial comany

17. 3. Data access
 Publicly available
 Available with copyright
 Browsing only, accessible but not downloadable
 Academic but not freely available
 Restricted

18. 4. DATA SOURCE
a) primary database
original data submission by researcher occurs.
Examples:
Nucleotide - genBank, EMBL, DDBJ
Protein - UniProt
Structure – PDB
Literature - PubMed
b) Secondary database
- results of analysis of primary databases.
- either manually curated or by automated methods
examples: Prosite, Pfam, RefSeq

19. 5. Database design
 Flat files
 relational datase (SQL)
 Object oriented database
 Exchange/ publication technologies (FTP, HTML,
SOAP, COBRA, XML)

20. 6. Organism
 Bacteria
 Virus
 Human