Introduction to Biological Databases

Introduction to Biological Databases

• Bioinformatics is a field where biology, computer science, and information technology combine.
• Biologists collect molecular data (DNA, protein sequences, gene expression).
• Computer scientists (and related fields) develop tools, software, and algorithms for storing and analyzing data.
• Bioinformaticians use analyzed molecular data to study biological questions.
• Bioinformatics aims to understand living cells and their functions at a molecular level.
• Bioinformatics uses computers to store, retrieve, manipulate, and distribute information on biological macromolecules (RNA, DNA, and proteins).
• Computational biology encompasses all areas of biology that involve computation.

What is a Database?

• A database is a computerized archive used to organize and store data.
• Databases can be visualized as a stack of record cards.
• Each record card includes specific information fields like name, address, phone number, birth date.
• Each field within a record holds a value (can be null).
• Searching databases involves retrieving entries with specific values in a particular field.
• Biological databases often have more complex requirements than general-purpose databases.

DNA Database Overview

• Bioinformatics has two major components:
  • Storing/retrieving information about DNA sequencing using biological databases.
  • Manipulating the information with tools to explore various aspects (e.g., sequence similarity, protein function).
• Biological Databases serve as a storage place for DNA sequence information. Users query these databases for specific information.

Types of Biological Databases

• Databases are categorized as:
  • Primary Databases: These hold experimental data on DNA sequences, and three-dimensional structures; Examples: GenBank, EMBL, DDBJ.
  • Secondary Databases: These are analyses of primary database data; Examples: SWISS-PROT, TrEMBL, and UniProt.
  • Composite Databases: These merge and filter data from primary sources to answer specific biological research questions; Examples: OWL, NRD, and Swiss-Prot.
• Some specialized databases focus on a particular organism (e.g. SGD for yeast).

Traditional File-Based Systems

• A file is a collection of logically related records.
• Each record contains one or more fields, representing characteristics of the modeled object.

Limitations of File-Based Approach

• Data redundancy and inconsistency (multiple files, duplicate data).
• Difficulty accessing data (need to write new programs for each task).
• Data isolation (multiple files and formats).
• Integrity problems (integrity constraints not explicitly addressed in program code).
• Atomicity problems (partial updates lead to inconsistent database states).
• Concurrent access issues (multiple users can cause inconsistencies).
• Security problems (limited ability to control data access).

What is Database?

• A database is a shared collection of logically related data, and a description of this data, designed to meet the information needs of an organization.
• A DBMS (Database Management System) is a software system that enables users to define, create, maintain, and access the database.

Database Management System (DBMS)

• DBMS enables users to define, update, manipulate, and retrieve data using Data Definition Language (DDL) and Data Manipulation Language (DML) like SQL.
• DBMS provides controlled access, security, integrity, concurrency control, recovery, and catalog.

Types of Databases

• Hierarchical databases
• Network databases
• Relational databases
• Object-oriented databases

Relational Database

• Relational DBMS (RDBMS) organizes data as tables with relationships described by three "keys": relation, domain, and attribute.

Database Schemas

• Database schema describes all the data entities, attributes, and relationships with integrity constraints.
• The database schema consists of different views (external schemas).
• The conceptual schema describes entities, attributes, and relationships together with integrity constraints.
• Internal schema is data on stored records, representation methods, data fields and indexes.
• Mappings translate information, ensuring data independence between different levels in the database (e.g. external to conceptual, conceptual to internal).

This quiz covers the basics of bioinformatics and biological databases, exploring how biological data is collected, analyzed, and stored. It also delves into the integration of biology, computer science, and information technology. Test your knowledge of the critical concepts and tools used in the field of bioinformatics.