Bioinformatics with Python

Bioinformatics with Python, available at $54.99, has an average rating of 2.4, with 47 lectures, based on 406 reviews, and has 2748 subscribers.

You will learn about Bioinformatics using Python Learn Biopython and Scikit-bio Sequence Analysis and Sequence Alignments Write Custom Functions For DNA Sequence analysis and Protein Synthesis Create Our Own Bioinformatics Python Package using Poetry This course is ideal for individuals who are Beginner Python Programmers curious about doing Bioinformatics with programming or Students and Researchers or Beginners to Bioinformatics,Computational Biology and Genomics It is particularly useful for Beginner Python Programmers curious about doing Bioinformatics with programming or Students and Researchers or Beginners to Bioinformatics,Computational Biology and Genomics.

Enroll now: Bioinformatics with Python

Summary

Title: Bioinformatics with Python

Price: $54.99

Average Rating: 2.4

Number of Lectures: 47

Number of Published Lectures: 47

Number of Curriculum Items: 47

Number of Published Curriculum Objects: 47

Original Price: $49.99

Quality Status: approved

Status: Live

What You Will Learn

Bioinformatics using Python

Learn Biopython and Scikit-bio

Sequence Analysis and Sequence Alignments

Write Custom Functions For DNA Sequence analysis and Protein Synthesis

Create Our Own Bioinformatics Python Package using Poetry

Who Should Attend

Beginner Python Programmers curious about doing Bioinformatics with programming

Students and Researchers

Beginners to Bioinformatics,Computational Biology and Genomics

Target Audiences

Beginner Python Programmers curious about doing Bioinformatics with programming

Students and Researchers

Beginners to Bioinformatics,Computational Biology and Genomics

Do you know that the human genomic sequence if printed out in a normal text font, would stretch for 5000 km, which is like the distance from London to Montreal, Los Angeles to Panama, Accra to Cape Town,  Tokyo to Calcutta.

This same sequence would fill about 3000 books the size of a normal book.

Understanding and analyzing this sequence is clearly going to be a huge task.

But with the advent of powerful tools and databases we can be able to grabs a simple understanding of some aspect of it.

In this introductory course we will explore the various Python tools and libraries used in analyzing DNA,RNA and genome sequence.

Hence if you are interested in analyzing large sum of biological data or are curious about DNA sequence,protein synthesis,and how vaccines are designed. Then this course is for you.

Whether you are a student or a researcher, data scientist or bioinformatics engineer,computational biologist, this course will serve as a helpful guide when doing bioinformatics in Python.

We will be exploring bioinformatics with BioPython, Biotite, Scikit-Bio, BioJulia and more.

Data is everywhere, biological data is in every living organism.Let us analyse it for useful insights

We will learn

how to do sequence analysis with BioPython,Biotite,etc

how to perform sequence alignment with code.

how to create our own custom functions for analyzing DNA,RNA and Proteins.

how to do some bioinformatics with Python.

how to analysis the DNA sequence of Covid 19, MERS and more.

NOTE: This is an introductory course structured like a reference material for anyone interested in doing bioinformatics with python.

Join us as we explore the world of biological data with Python

Course Curriculum

Chapter 1: Module 01 – Introduction

Lecture 1: Introduction and Course Plan

Lecture 2: What is Bioinformatics?

Lecture 3: What is a DNA?

Lecture 4: What is Protein Synthesis?

Lecture 5: Overview of Bioinformatics Databases

Chapter 2: Module 02 – Bioinformatics with BioPython

Lecture 1: Handling Sequences with BioPython

Lecture 2: BioPython – Protein Synthesis

Lecture 3: BioPython – DNA Composition – GC Content,AT Content and Frequency

Lecture 4: BioPython – Sequence Alignment

Lecture 5: BioPython – Difference Between Sequence Similarity and Sequence Identity

Lecture 6: BioPython – Checking for Similarity Using Distance

Lecture 7: BioPython – Checking for Similarity Using DotPlot

Lecture 8: BioPython – Working with Biological Data File Formats – FASTA,GENBANK,etc

Lecture 9: BioPython – Working with 3D Structures

Lecture 10: BioPython – Visualizing 3D Structures

Lecture 11: BioPython – Using Nglview For 3D Structures

Lecture 12: BioPython – Using Pytraj For 3D Structure

Lecture 13: BioPython – BLAST

Lecture 14: Section Materials – For BioPython

Lecture 15: Real Example with BioPython – Sequence Analysis of Covid 19 DNA

Lecture 16: BioPython – Alphabets Updates

Chapter 3: Module 03 – Bioinformatics with Biotite

Lecture 1: Biotite – Introduction, Handling Sequences and Protein Synthesis

Lecture 2: Biotite -Sequence Alignments

Lecture 3: Biotite – Working with Files

Lecture 4: Biotite – Reading Data From Bioinformatic Databases

Lecture 5: Biotite – Fetching PDB Files from Protein Data Bank

Lecture 6: Biotite – Fetching and Querying Multiple PDB Files

Lecture 7: Biotite – Working 3D Structures of Protein

Lecture 8: Biotite – Quick Overview of Phylogenetics with Biotite

Lecture 9: Biotite – Applications Subpackage

Lecture 10: Real Example with Biotite – Comparing Coronavirus and MERS viral genome

Lecture 11: Section Materials – For Biotite

Chapter 4: Module 03 – Bioinformatics with Scikit-Bio

Lecture 1: Scikit-Bio- Handling DNA,RNA and Protein Sequence

Lecture 2: Scikit-Bio – Protein Synthesis

Lecture 3: Scikit-Bio – DNA Composition – Checking for GC Content and AT Content

Lecture 4: Scikit-Bio – Checking for Similarity using Hamming Distance and Kmer-Distance

Lecture 5: Scikit-Bio – Kmers and Kmers Frequency

Lecture 6: Scikit-Bio – Sequence Alignment – Global and Local Alignments

Lecture 7: Scikit-Bio – Working with FASTA and GenBank File Formats

Lecture 8: Scikit-Bio – Phylogenetics – A Simple Overview using Newick Format

Lecture 9: Section Materials – For Scikit-Bio

Chapter 5: Module 04 – Bioinformatics Extra – Using Custom Functions, BioJulia etc

Lecture 1: Bioinformatics using Custom Functions in Python

Lecture 2: Building A BioInformatics Package with Python -From Scratch

Lecture 3: Bioinformatics with NeatBio

Lecture 4: Building A Simple BioInformatics App with Streamlit

Lecture 5: Bioinformatics with Julia

Lecture 6: Thank You Note

Instructors

Jesse E. Agbe
Developer

Rating Distribution

1 stars: 28 votes

2 stars: 37 votes

3 stars: 90 votes

4 stars: 131 votes

5 stars: 120 votes

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