Introduction to Python for Biologists.
- Why Python for Biology?
- Biological Data Types and Python
- Sequence Analysis - Part 1
- Sequence Analysis - Part 2
- Image Analysis - Part 1
- Image Analysis - Part 2
- Database Management and Python
- Statistical Analysis in Python
- Bioinformatics and Python
- Data Visualization in Python
- Machine Learning for Biology with Python
- Project Planning and Design
- Implementing a Biological Project with Python
Database Management and Python
Database Management Basics for Biologists
Organized collection of data in computing.
In the realm of biological research, databases play a crucial role in storing, organizing, and retrieving vast amounts of data. This unit will provide an introduction to databases, their types, structures, and the basics of SQL, a language used for managing and manipulating databases.
Introduction to Databases
A database is a structured set of data. In the context of biology, databases can store a wide range of information, from genomic sequences to patient records, and from ecological data to experimental results. The primary advantage of using databases is that they allow for efficient data retrieval, insertion, update, and deletion.
Types of Databases
There are several types of databases, each with its own strengths and weaknesses. The most common types include:
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Relational Databases: These databases organize data into tables, which can be linked—or related—based on data common to each. This type of database is widely used due to its flexibility and robustness.
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Hierarchical Databases: In these databases, data is organized into a tree-like structure, with a single root to which all other data is linked. This type is less flexible than the relational model, but it can be more efficient for certain types of data retrieval.
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Network Databases: These databases allow for complex relationships between data, where each record can have multiple parent and child records.
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Object-oriented Databases: These databases store data in the form of objects, as used in object-oriented programming.
Understanding Database Schemas and Structures
A database schema is the structure described in a formal language supported by the database management system (DBMS). It outlines how data is organized and how the relations among them are associated. It evolves with time; new tables are created, new relations are established, and new fields are added into the existing tables.
Introduction to SQL
SQL (Structured Query Language) is a programming language used to communicate with and manipulate databases. Most of the SQL database programs also have their own proprietary extensions in addition to the SQL standard!
SQL is used in manipulating data stored in Relational Database Management Systems (RDBMS), or for stream processing in a Relational Data Stream Management System (RDSMS).
SQL involves several types of commands for different operations such as:
- SELECT: extracts data from a database
- UPDATE: updates data in a database
- DELETE: deletes data from a database
- INSERT INTO: inserts new data into a database
- CREATE DATABASE: creates a new database
- ALTER DATABASE: modifies a database
- CREATE TABLE: creates a new table
- ALTER TABLE: modifies a table
- DROP TABLE: deletes a table
- CREATE INDEX: creates an index (search key)
- DROP INDEX: deletes an index
In the next unit, we will explore how Python can be used to interact with databases, including executing SQL commands.