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1
Hidden Markov Model in Bioinformatics (Part 2)
2
Hidden Markov Model in Bioinformatics - HMM (Part 1)
3
Overlap Matches using pairwise alignment algorithm (Part 1)
4
Finding Repeated Matches - Pairwise Alignment using BLOSUM Substitution Matrix
5
A User-Friendly Guide for Analyzing Big Data of Cancer Genomics
6
Cancer Genomics (Part 3): Easy guide to access RNA sequencing data of cancer (Example: Cbioportal)
7
Cancer Genomics - Types of NGS techniques (Part 2)
8
Cancer Genomics - Data science (Part 1)
9
Cancer Genomics - Data science (Part 1)
10
Multiple Sequence Alignment and Phylogenetic Tree Building using MEGA Software - Tutorial
11
How to install MEGA software for multiple sequence alignment and phylogenetic analysis (Tutorial)
12
Basics of Phylogenetics - How to calculate evolutionary distance
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Basics of Phylogenetics - Difference between distance and character based methods
14
Basics of Phylogenetics - Significance of Root in a tree
15
Basics of Phylogenetics - Understanding the nomenclature and types of phylogenetic tree.
16
SmithWaterman Algorithm (Local Alignment) Part 2 Urdu Version
17
SmithWaterman Algorithm (Local Alignment) Part 3 Traceback Urdu Version
18
SmithWaterman Algorithm (Local Alignment) Part 1 Urdu Version
19
Local Alignment (Smith Waterman)
20
Introduction to Bioinformatics - Needleman Wunsch algorithm - Part 1 (Lecture 11)
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Introduction to Bioinformatics - Needleman Wunsch algorithm - Part 2 (Lecture 11)
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Introduction to Bioinformatics - Needleman Wunsch algorithm - Part 3 (Lecture 11)
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Introduction to Bioinformatics - Needleman Wunsch algorithm Traceback - Part 4 (Lecture 11)
24
Introduction to Bioinformatics - Why database is important in biology ? Lecture 6
25
Basics of Phylogenetics - Gene duplication and Speciation
26
Phylogenetic Tree Topology - Gene species tree reconciliation
27
Phylogenetics - Maximum Likelihood Method
Description:
Explore a comprehensive series of bioinformatics lectures covering a wide range of topics. Dive into Hidden Markov Models, pairwise alignment algorithms, and cancer genomics. Learn about multiple sequence alignment, phylogenetic tree building, and various alignment algorithms including Smith-Waterman and Needleman-Wunsch. Gain insights into the importance of databases in biology, gene duplication, speciation, and maximum likelihood methods in phylogenetics. Access user-friendly guides for analyzing big data in cancer genomics and working with RNA sequencing data. Master essential bioinformatics concepts and techniques through these in-depth lectures, suitable for both beginners and advanced learners in the field.

Bioinformatics Lectures

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#Data Science #Bioinformatics #Computer Science #Machine Learning #Hidden Markov Models #Science #Biology #Evolutionary Biology #Phylogenetics #Genomics #Cancer Genomics #Computational Biology
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Hidden Markov Model in Bioinformatics (Part 2)