Analysis on Bioinformatics with AI

Chapter 2: Python Basics

Mon, 01 Jan 0001 00:00:00 +0000

This chapter introduces Python through the lens of molecular biology. Every concept you learn here – variables, strings, conditionals, and lists – maps directly to something you will do with DNA sequences.

We start by storing a DNA sequence in a variable. From there, we learn to concatenate fragments, classify codons, and iterate over collections of sequences. Each vanilla script builds one concept; each AI script shows how an LLM can interpret the biological meaning behind your code.

Chapter 3: The Central Dogma

Mon, 01 Jan 0001 00:00:00 +0000

The central dogma of molecular biology describes the flow of genetic information: DNA is transcribed to RNA, which is translated to protein. This chapter implements that process in code.

You will build a codon table, translate DNA to protein, explore all six reading frames, and parse FASTA files. These are the core operations of computational biology.

Each script adds one layer of complexity. By the end, you will have a working translation pipeline that reads a FASTA file and outputs protein sequences.

Chapter 4: Biological Data

Mon, 01 Jan 0001 00:00:00 +0000

Bioinformatics runs on structured data. Gene annotations, variant calls, protein databases, and sequence alignments all follow specific formats. This chapter teaches you to parse and work with biological data formats.

You will learn to handle GenBank and FASTA formats using BioPython, extract features from sequence records, and write sequences to files. These skills are the bridge between raw data and biological insight.

Every tool in bioinformatics depends on parsing structured data correctly. This chapter gives you that foundation.