Course Content
Bioinformatics Databases
0/47
Introduction to National Center of Biotechnology Information (NCBI)
18:02
Sequence Analysis
17:59
Sequence Retrieval from NCBI
16:17
PubMed Central & ENTREZ
11:07
GenBank: Nucleotide Database on NCBI
06:50
FASTA vs GenBank
18:26
Gene Database: A Comprehensive Gene Database
30:21
NCBI Genomes & NCBI Assembly: Retrieval of Genomes
36:14
RefSeq Database: Retrieval of Single Reference Sequences
11:16
BLAST Database Searching
25:37
Introduction to Molecular Modeling Database
08:07
Database of Short Genetic Variations (dbSNP)
12:16
HomoloGene: Discovery of Gene and Protein Families
06:11
Taxonomy
09:57
Introduction to UCSC Genome Browser & SARS-CoV-2 Viral Genome
13:40
Retrieve an Entire Genome & Retrieval of SARS-CoV-2 Viral Genome
09:41
Retrieval of Genomic Data & Annotation of SARS-CoV2 Viral Genome
05:30
Table Browser & SARS-CoV-2 Viral Genome
12:16
Visualization of Genomic Data on the Genome Browser & SARS-CoV-2 Genome
10:51
UniProt BLAST – Database Searching
12:33
UniProt Peptide Search – Find Regions Within UniProt Database
03:15
Introduction to ENSEMBL
07:50
Retrieval of a Gene-Protein-Chromosomal Region
18:02
Genome Assembly Retrieval and Analysis
10:24
Gene Analysis & Annotation
34:40
Variation Analysis
24:37
ENSEMBL BLAST/BLAT
15:08
Regulation – Understand the Influence of Regulatory Elements on Genes
04:19
Comparative Genomics Analysis
05:35
Introduction to Phytozome
09:39
Interpret Plant Genome Records
09:07
Download an Entire Plant Genome & Proteome
26:41
Keyword or BLAST Search in a Plant Genome
15:58
Visualize a Plant Genome Using JBrowse
17:38
UniProt Align – Pairwise & Multiple Sequence Alignment and Annotation
03:48
UniRef And Retrieve Protein Clusters
11:36
UniParc And Find the Non-Redundant Entries
04:59
Genome Reference Consortium (GRC)
07:48
BioProject
06:40
BioSystems
04:16
BioSample
02:56
Sequence Read Archive (SRA)
07:15
Introduction to Gene Expression Omnibus Database
09:16
Gene Expression Omnibus – Platforms
05:42
Gene Expression Omnibus – Samples
04:16
Gene Expression Omnibus – Series
04:01
Gene Expression Omnibus – Datasets
04:45
Bioinformatics File Formats
0/11
FASTA (Sequence Format)
06:13
GenBank (Sequence Annotation Format)
07:08
FASTQ Format
18:02
Gene File Format/Gene Transfer Format
11:07
BED (Gene Structure Format)
04:27
SAM
09:07
BAM
09:07
Clustal Omega Alignment Format
05:32
MEGA (Alignment Format)
05:32
PHYLIP – Multiple Sequence Alignment Format
04:35
Stockholm Alignment Format
03:10
Protein Databases & Analysis
0/27
Introduction to UniProt
09:56
UniProtKB & Protein Analysis
39:30
UniProteome & Retrieval of an Entire Proteome
13:05
UniProt BLAST – Database Searching
12:33
ID Mapping & Making Analysis Easier
07:17
Introduction to Protein Data Bank (PDB)
06:45
Accurately Searching for a Protein Structure on PDB & Protein Analysis
13:56
Biological Annotation and Protein Features View & Analysis
08:18
Browsing PDB According to Annotation
06:52
Digging Out Categorized & Specific Protein Structures from PDB Archives
06:23
Alignment Between Two PDB Sequences & Structures
06:08
3D Structure Visualization on PDB
10:49
Mapping Genomic Position to Protein Sequence and 3D Structure
04:35
Genomic Discovery of Protein Structure Through Gene
04:07
PDB – Protein Symmetry
02:34
Introduction to InterPro
04:10
InterPro – Protein Family Classification and Analysis
14:35
InterPro – Protein & Protein Domain Analysis
09:29
HMMER – Hidden Markov Model Based Protein Profiles Database
13:16
SignalP: Prediction of Signal Peptides
07:57
TargetP: Prediction of Protein Localization
09:22
Pfam – Understand the Relation of a Protein to its Family and Clan
15:56
PROSITE – A Database of Protein Domain, Families and Functional Sites
13:46
ScanProsite – Scanning Protein for Important Protein Sites Against PROSITE Database
07:36
Marcoil – Predict Coiled Coil Domains in Proteins
04:06
SMART
06:45
PDB – Ligands
05:23
Sequence Alignment & Analysis
0/9
EMBOSS NEEDLE: Global Alignment of Sequences
20:02
Clustal Omega: Most Reliable Multiple Sequence Alignment Tool
19:18
EMBOSS Water
09:10
Jalview
13:42
T-Coffee: Iterative Multiple Sequence Alignment Tool
08:38
MUSCLE: Accurate Multiple Sequence Alignment Tool
21:08
MEGA – Multiple Sequence Alignment
04:23
MAFFT – Fastest Multiple Sequence Alignment Tool
08:22
Aln2Plot
02:31
Phylogenetic Analysis
0/3
MEGA
21:20
iTOL: Creating Publishable Phylogenetic Figures
13:43
FigTree
21:27
Secondary Structure Prediction
0/5
Quick2D
04:33
Ali2D
04:09
Jpred: Prediction Secondary Structure of the Proteins
04:55
HHrepID
05:15
DeepCoil
03:23
3D Structure Prediction
0/7
MODELLER: Most Commonly Used Homology Modelling
36:13
SwissModel: Homology Modeling Through Web-server
12:53
HHPred
14:09
M4T
09:27
IntFold
08:41
ROBETTA: ab initio Protein Structure Prediciton
14:40
Homology Modeling Using MOE
12:34
3D Structure Visualization
0/2
UCSF CHIMERA
25:23
PyMol
40:49
3D Structure Evaluation
0/7
WhatCheck
08:40
ProCheck
12:41
ERRAT
06:44
Verify3D
08:35
RAMPAGE
03:30
SAVES
05:32
PROSA
10:05
Docking Complex Evaluation
0/12
MOE: Protein Ligand Docking
09:23
MOE: Protein Protein Docking
11:39
SwissDock Protein Ligand Docking
19:16
Autodock Vina Protein Ligand Docking
15:49
MOE: Docking Library of Compounds
19:48
MOE: Structure Based Drug Designing
16:19
ClusPro Protein Protein Docking
21:44
Patchdock Protein Protein Docking
17:40
PEPFOLD 3 Peptide Structure Prediction
13:15
Zdock Protein Protein/Ligand docking
19:35
MDockPEP Protein Peptide Docking
10:06
Discovery Studio+
12:03
Docking Complex Evaluation
0/3
PDBsum Docking Complex Evaluation
18:50
Pdbepisa Docking Complex Evaluation
23:27
SwissADME
15:31
Gene Prediction
0/4
GeneMark: Gene Prediction from Eukaryotic Genomes
16:51
Prodigal: Gene Prediction from Microbial Genomes
25:47
GenScan – Prediction of Genes from Green Monkey and Finding a Novel Gene
10:41
AUGUSTUS – Prediction of Novel Genes in Star Fish or Any Genome
17:28
PPI Database
0/1
STRING: Comprehensive Protein-Protein Interaction Database
13:17
Genomics Tools
0/1
Gene Structure Display Server 2.0
08:36
Molecular Dynamics Simulation
0/11
Getting Started With Molecular Dynamics Simulation – Pre-processing of Protein Structure and Removal of Unnecessary Structural Features
12:34
pdb2gmx – Construction of Topology File for Simulation
09:01
Defining a Solvant Box for Simulation
04:14
Solvation – Adding Water Molecules in Solvant Box
05:31
Generating Input Run File Replacement of Water Molecules With Ions
06:55
Genion – Replacement of Water Molecules With Ions
04:19
Energy Minimization – Relaxing and Fixing the Structure for Simulation
11:25
GRACE – Visualization and Analysis of Minimized Structure
04:12
Equibiliration of Protein Structure NVT ENSEMBLE Phase 1
08:38
Equibiliration of Protein Structure NPT ENSEMBLE Phase 2
08:10
mdrun – Executing Simulation Analysis
03:47
Python
0/21
Introduction to Python and it’s Installation
08:25
Why Python in Bioinformatics
09:16
Comments
05:43
Basic Input and output
15:38
Mathematical Operations
07:20
Strings
21:51
Dictionaries
10:57
Lists
28:48
Lists (pt 2) and Tuples
10:38
Sets
07:36
If-Else
09:19
For Loop and Calculation of Molecular Weight of Proteins
10:56
While Loop and Biological Data Analysis
09:37
Reading Files
13:45
CSV (A special kind of file in Bioinformatics)
08:42
Writing Files
07:18
Consolidate (merge) multiple DNA and Protein Sequences into one FASTA file
09:25
OS
31:47
Function
26:41
With
08:50
Error Handling
15:31
BioPython
0/45
Introduction to BioPython & Installation
10:19
Bio.Seq Seq Object Behaves Like a String
09:54
Bio.Seq Create a Seq Object
07:34
Bio.Seq Central Dogma in Play Through Python
08:41
Bio.Seq Unknown & Mutable Sequences
06:54
Bio.Alphabet Understanding the Alphabets of Biology
07:38
Bio.Alphabet IUPAC and Types of Sequence Representations
07:38
Bio.Alphabet Concatenation of Multiple Seq Records Using Generic Alphabets
09:47
SeqRecord Creating Seq Records
12:28
SeqRecords & FASTA
04:36
SeqRecords & GenBank
03:29
SeqRecord Formatting Records
03:06
SeqRecord Comparison & Reading Multiple FASTA Files from Directory
05:47
SeqIO Reading a Sequence File
10:32
SeqIO – Write Sequences and SeqRecords Into Files
11:43
SeqIO Extracting Annotations and Pattern-wise Sequence Data Extraction
10:35
AlignIO – Writing Alignments and Multiple Sequence Alignment Records
05:29
AlignIO – Conversion of Alignment Formats
04:02
AlignIO – Manipulating Alignments
02:57
AlignIO – ClustalW Python Wrapper – Align Multiple Sequences
07:47
AlignIO – Pairwise2 – Align Two Sequences
07:31
AlignIO – Information Mapping of Alignments
02:33
AlignIO – Format Alignments
03:36
AlignIO – Slicing Alignments
06:06
Bio.Blast – Querying NCBI BLAST Through Python
11:15
Bio.Blast – Parsing BLAST Results
14:52
Bio.Entrez – Accessing ENTREZ Using Python
09:32
Bio Entrez Use Esummary To Get Summary Of Your Accessions
08:59
Bio.Entrez – Use EFetch to Download Complete Records
13:57
Bio.Entrez – Use EGQuery to Do Global Quries for Search Counts
07:24
Bio.Entrez – Use Elink To Search For Database Links Of Records
03:42
Bio.Entrez – Use ESearch to Search the Entrez Databases
08:20
Bio.Entrez – Use Espell To Get Correct Spellings For Your Search Terms
05:21
Bio.Entrez – Download GenBank and Entrez Records
14:17
Bio.Entrez – Taxonomy Database Searching
07:05
Bio.Entrez – Download PubMed Articles
08:28
Bio.PDB – Reading a PDB (3D Structure) File
11:59
Bio.Phylo – Calculating Distance Matrix Between Sequences For Phylogenetic Analysis
04:18
Bio.Phylo – Converting Phylogenetic Tree Data Formats
03:29
Bio.Phylo – Printing Out Phylogenetic Tree In Ascii
02:17
Bio.Phylo – Reading Phylogenetic Trees
06:29
Bio.Phylo – Visualization And Manipulation Of Phylogenetic Trees
09:36
Bio.motifs – Creating a WebLogo of Motifs
00:00
Bio.Phylo – Writing Out Phylogenetic Data
04:04
Bio.motifs – MEME Analysis
09:49
R
0/53
Introduction to R in Bioinformatics & R Installation
09:48
The R User Interface
06:23
Comments
04:17
Variable Declaration and Objects
05:24
Built-in Functions & ARGS
04:32
Sample & Replacement
09:09
Write Your Own Functions And Arguments
05:39
Scripts
07:36
Packages
04:00
Install Packages
05:25
Library & Initialize Packages
02:28
Getting Help with Help Packages
03:43
Atomic Vectors
02:43
Doubles
03:31
Integers
03:23
Characters
04:43
Logicals
02:27
Attributes and Names
04:46
Dim & Dimensions
05:46
Matrix & Matrices
04:43
Arrays
03:42
Class
03:13
Factors
06:41
Lists
06:42
Coercion
04:27
Data Frames
06:30
Loading Biological Data
07:56
Saving Biological Data
05:27
R Notation & Selecting Values from Biological Dataset
04:09
Negative Integers for subsetting Biological Dataset (DataFrame)
05:28
Positive Integers for subsetting Biological Dataset (DataFrame)
05:26
Zero Notation for subsetting Biological Datasets (DataFrames)
01:09
Blank Spaces For Biological Data Subsetting
03:21
Dollar Signs for Biological Dataset Subsetting
02:58
Modifying Values in Existing DataFrames/Datasets
07:06
NA Values in Biological Dataset
05:25
Figuring out NA Values in Biological Dataset
02:06
Logical Subsetting in Biological Datasets
09:46
If Else Statement
04:15
For Loops & Biological Data Binding
16:30
While Loops & Reading Multiple Biological Datasets
16:16
Introduction to ggplot2 for Biological Datasets
10:46
ggplot2: Key components
08:26
ggplot2: Human Mitochondrial Proteome & Aesthetics (Size, Shape, Color)
26:06
ggplot2: Facetting of Human Genome
22:25
ggplot2: Smooth Out the Biological Data
08:43
ggplot2: Boxplots for Human Mitochondrial Proteome
07:56
ggplot2 :Histograms for Human Mitochondrial Pattern Finding
06:02
ggplot2: Frequency Plots for Human Mitochondrial Information Frequency Mining
06:13
ggplot2: Bar Charts Human Mitochondrial Knowledge Mining
10:43
ggplot2 – Scaling and Limiting Data Visualization
03:53
ggtree – Phylogenetic Tree Visualization
05:41
ggplot2 – Saving the Visualizations in High Resolution
04:45
Linux
0/29
Introduction to Linux for Bioinformatics
22:32
PWD – Print Working Directory
01:26
CD – Changing Directories
05:03
MKDIR – Making Directories
08:13
MV – Moving Files, Directories and Data
05:11
RM – Deleting Files and Directories
01:24
Which & Whereis – Find Programs You Installed
03:43
LS – Listing Files and Directories on Linux
06:46
Find – Finding User Created Files
03:39
Piping and Redirection of Data
06:35
Cat – Visualization and Inspection of Text Data
03:56
Head – Reading Specified Number of Lines from Top
03:50
Tail- Reading Specified Number of Lines from Bottom
02:23
Touch – Modifying File Statistics and Creating Files
07:04
Stat – Statistics of File & Directories
02:43
Wget – Retrieval of Genome Assemblies
06:48
Curl – Retrieval of Bioinformatics Files
02:25
Vim – Create and Edit Text Files
05:59
Diff – Find Sequence Differences in Files
02:35
GZIP – Compress and Archive Files Efficiently
06:05
Tar – Create Archives of Genome Data
04:19
GUNZIP – Extract Compressed Content
02:14
Grep – Finding Uncharacterized Proteins in Human Genome
08:55
Cut – Subsetting Required Textual Data from Text Files
05:49
Sort – Sorting Data
04:23
Uniq – Finding Unique Data Items
10:33
WC – Statistics of the Data Within File
02:46
CP – Copying Files and Files Contents
03:43
Column – Proper Visualization of Delimited Datasets
04:38
R
0/53
Introduction to BioConductor
10:28
Installing Packages from BioConductor
04:12
Reading and Writing the FASTA File
06:58
Getting the Detail of a Sequence Composition
07:46
Pairwise Sequence Alignment
08:08
Multiple Sequence Alignment
09:47
Handling BLAST Results
03:54
Pattern Finding in a Sequence
05:51
Performing ID Conversions
05:45
The GO Annotation of Genes
04:33
The GO Enrichment of Genes
09:28
The KEGG Enrichment of Genes
07:16
Introduction to dplyr
15:38
Filter Rows with filter()
20:13
Select Columns with select ()
28:30
Add New Variables with mutate ()
21:19
Grouped Summaries with summerize ()
18:30
Grouped Mutates (and Filters)
19:58
Introduction to tidyr
11:35
Data Spreading Function
13:51
Data Gathering Function
19:30
Data Separating & Pull
17:24
Missing Values
29:58
Introduction to ArrayExpress – Getting Started With MicroArray Analysis
09:56
Introduction to BioConductor – Installing MicroArray Packages
05:06
Getting Started with R Studio Project for MicroArray Analysis
04:51
Downloading MicroArray Raw Data from ArrayExpress
04:19
Creating Raw Intensities MicroArray Data Structure and Log2 Transformation
14:41
Principle Component Analysis of Raw Expression Dataset
15:44
Box Plot Visualization of Raw Intensity Data to Interpret the Median Intensities of the Samples
03:11
ArrayQualityMetrics – Automated Quality Control for Microarray Datasets
05:38
Annotating the Probe IDs with Gene Symbols and Names
04:19
Excluding Probe IDs with Multiple Mappings from the ExpressionSet
04:39
Filtering out the Genes that are Above Threshold
06:02
Heatmap Visualization of the Normalized Gene Expression Values
11:52
Intensity-based Filteration of Low-Intensity Transcripts
06:19
Normalization of Raw Intensities Values
04:36
Relative Log Expression Analysis and Visualization
08:57
Removal of the Probe IDs that Match to Multiple Genes
04:04
Robust Multi-Array Summarization and Background Correction of the Raw MicroArray Data
03:47
LIMMA – Data Preparation for Linear Modelling
11:49
Factors Preparation
10:26
Analysis of Gene Expression Levels of a Single Gene Among Different Conditions
12:00
LIMMA – Applying Linear Model on a Single Gene Expression Data
05:34
Data Visualization of the Gene Expression of a Single Gene
00:00
Applying t-test to Find if Genes are Differentially Expression
06:51
LIMMA – Applying Linear Model for Differential Gene Expression Analysis
11:38
Extraction of Differentially Expressed Genes from the Fitted Linear Model
03:35
Setting a Threshold for Differentially Expressed Genes
04:17
Volcano Plot – Visualization of the Genes that are Differentially Expressed
04:36
Matching the DEGs with Background Genes to Find Overlap
00:00
topGO – Gene Enrichment & Ontology Analysis
28:02
topGO – KEGG & REACTOME Pathway Analysis
08:44
Target Identification
0/3
Target Selection
03:20
Removing Duplicates
03:46
Screening Non-homologous Proteins
06:42
Immunoinformatics Approach for Epitope Prediction
0/4
Screening Antigenocity Of Protein
04:21
Linear B-cell Epitope Prediction
02:22
Assessment Of Linear B-Cell Epitope
05:06
CTL Epitope Prediction
04:54
Computational Construction of the Vaccine
0/6
CTL Epitope Assessment
04:14
HTL Epitopes Prediction and Assesment
06:43
Mapping Vaccine Construct
05:23
Secondary And Tertiary Structure Prediction Of Vaccine
02:10
Tertiary Structure Refinement And Validation
03:47
Discontinues B-cell Epitope Prediction
02:22
Molecular Dynamics and Immune Simulation
0/3
Molecular Dynamic Simulation
02:14
Immune Simulation
02:19
In Silico Cloning
02:45
Supplementary 1
0/1
Codon Optimization
02:35
Supplementary 2
0/1
Disulfide Engineering
03:03
Supplementary 3
0/1
Docking of Protein and TLR4
02:18
Introduction to NGS, RNA-Seq Pipeline & GALAXY
0/4
Introduction to Next Generation Sequencing & RNA-Seq
12:09
RNA-Seq Data Analysis Workflow
01:20
What is Galaxy
04:11
How to Get Started With Galaxy Account
01:01
Practical RNA-Seq Differential Gene Expression Analysis
0/7
RNA-Seq Dataset Retrieval
03:27
Quality Control with FastQC
10:02
Pro-processing of the Reads
04:39
Alignment of the Reads Against Reference Genome
05:16
Post Alignment Processing
05:37
Transcript Assembly and Quantification with StringTie
04:57
Differential Gene Expression Analysis with DESEQ2
09:20
In-Depth Introduction to RNA-Seq
0/3
In-depth Introduction to RNA-Seq Data Analysis, Linux Computing and R
44:08
Introduction to Linux for Bioinformatics
22:32
Introduction to ArrayExpress – Getting Started With MicroArray Analysis
09:56
Genomic Databases for Raw Data
0/17
BioProject
06:40
BioSystems
04:16
BioSample
02:56
Introduction to Gene Expression Omnibus Database
09:16
Gene Expression Omnibus – Platforms
05:42
Gene Expression Omnibus – Samples
04:16
Gene Expression Omnibus – Series
04:01
Gene Expression Omnibus – Datasets
04:45
Gene Expression Omnibus – Profiles – How to Search for Gene Expression Profiles
05:55
NCBI Genomes & NCBI Assembly
36:14
Genome Reference Consortium
07:48
Introducton to Phytozome
09:39
Download an Entire Plant Genome & Proteome
26:41
Introduction to UCSC Genome Browser
13:40
How to retrieve an entire genome & Retrieval of SARS-CoV-2 Viral Genome
09:41
Introduction to ENSEMBL
07:50
Genome Assembly Retrieval and Analysis
10:24
File Formats
0/4
BED
04:27
GTF/GFF
11:07
SAM
09:07
FASTQ
18:02
Introduction to Linux for RNA-Seq
0/18
Introduction to Linux for Bioinformatics
22:32
PWD – Print Working Directory
01:26
MKDIR – Making Directories
08:13
CD – Changing Directories
05:03
MV – Moving Files, Directories and Data
05:11
RM – Deleting Files and Directories
01:24
Which & Whereis – Find Programs You Installed
03:43
Find – Finding User Created Files
03:39
LS – Listing Files and Directories on Linux
06:46
Cat – Visualization and Inspection of Text Data
03:56
Head – Reading Specified Number of Lines from Top
03:50
Tail- Reading Specified Number of Lines from Bottom
02:23
Touch – Modifying File Statistics and Creating Files
07:04
Stat – Statistics of File & Directories
02:43
Wget – Retrieval of Genome Assemblies
06:48
Curl – Retrieval of Bioinformatics Files
02:25
Vim – Create and Edit Text Files
05:59
Diff – Find Sequence Differences in Files
02:35
RNA-Seq Data Analysis Pipeline (Theoretical & Practical)
0/15
How to Retreive Raw Reads for RNA-Seq Data Analysis
03:26
Retrieval of Data Required for this Course
08:45
In-depth Theory: Quality Control
19:37
Practical: Preprocess Raw Reads Using FASTQC, FASTP, Trimmomatic & Cutadapt
31:54
In-depth Theory: Mapping & Transcriptome Assembly
48:22
Practical: Mapping Preprocessed Reads Against a Reference Genome Using HISAT2, TOPHAT2, BOWTIE2, STAR
31:51
Practical: Transcriptome Assembly Using StringTie
54:31
Mapping Visualization & Evaluation
36:37
In-depth Theory: Gene Quantification, Expression Estimation & Differential Gene Expression
18:28
In-depth Theory: DeSeq2, Ballgown, edgeR
32:22
Practical: Differential Gene Expression Analysis Using Ballgown, edgeR, DESEQ2 in R
34:39
Theory: Functinal Enrichment Analysis of the DEGs
18:39
Practial: Gene Ontology Analysis
28:02
Practical: Pathways Analysis Using KEGG, PANTHER, Reactome
12:41
Practical: Protein-Protein Interaction Using STRING
13:17
Basics of Cellular Biology
0/9
What is a Cell
12:47
What is a DNA and its Importance
09:03
What are Nucleotides
11:11
What are the Major Types of RNA
11:22
What are Nucleotide Codons
09:57
What are Amino Acids
06:55
What are Enzymes
14:38
Features of Cellular Structure
14:37
Biochemical Diversity Within Prokaryotic Cells
08:18
Genetic Information and Its Flow
0/7
What are Genes
08:22
What is Evolution
09:46
What are Mutations and its Types
07:44
What are Gene & Protein Families
07:41
Orthologs vs. Paralogs
06:12
Gene Transfer Between Organisms
05:59
What is a Genetic Sequence
00:00
Brief Introduction to Genome and Model Organism
0/4
Eukaryotic Genomes and Their Regulatory DNA
08:42
Model Organisms for Genomics Studies: Yeast, Worm, Drosophila, Mouse, Human & Arabidopsis
10:54
How Can Gene Expression of all Genes of an Oganism be Studied
09:11
Example of Repeated Duplications: Vertebrate Genome
05:42
Cell Metabolism and Energy Production
0/4
Cell Metabolism: Enzymes, Heat Energy and Oxidation
08:51
How ATP Energy is Generated and Synthesis of Biological Polymers
08:47
Glycolysis: Central ATP-Produing Pathway and Fermentation
07:18
Nitrogen Cycle: Amino Acids and Nucleotide Synthesis
08:46
Protein Structure, Shape and Characteristics
0/12
Primary Structure: How Amino Acids Dictate the Shape of Protein Structure
06:16
Native Conformation: Proteins Fold into a Conformation of Lowest Energy
06:43
Secondary Structures: Alpha Helices and Beta Sheets
06:10
Tertiary Structure of Larger Proteins: Domains and Motifs
07:37
Tertiary Structure of Larger Proteins: Domains and Motifs
07:37
Quarternay Structure of Proteins
05:25
How Covalent Bonds Stablize Extracellular Proteins
06:34
Why Do Proteins Bind to Molecules?
06:47
Enzymes: Substrate Binding and Catalystic Reactions
10:16
How Proteins are Modified by Protein Phosphorylation
00:00
How Small Proteins Assist the Movement of Large Proteins
05:30
Protein Machines: Large Complexes, Their Use of Genetic Information and Position at Specific Sites
00:00
Chromsomes & Their Characteristics
0/3
Nucleosome and Its Structure: Basic Unit of Eukaryotic Chromosome
00:00
Chromatin Remodeling Complexes
00:00
Causes of Genome Alterations: Failure in Copying and Maintaining DNA
00:00
Evolutionary & Mutation Rates
0/3
Evolutionary Rates Determine the Size of a Verteberate Genome Due to DNA Addition and Deletion
00:00
How Neutral Mutations Become Fixed in a Population With a Probability that Depends on Population Size
00:00
Why Mutation Rates Are Extremely Low and Why Their Are Necessary For Life
00:00
DNA Replication
0/1
DNA Replication: Base-pairing Underlies DNA Replication & DNA Repair
00:00
PyMol MasterClass: Perform Expert Level 3D Structure Visualization for Drug Discovery
0/7
A Comprehensive Introduction to PyMol and Biomolecule Visualization
08:34
How to Perform Superimposition of Biomolecules (Onco-proteins Example)
07:37
How to Perform Interaction Analysis Between Protein Ligand Complex and Identify Polar Contacts (Human Adenovirus and Inhibitor Example)
11:46
How to Identify Interactions Between Protein-Protein Complex (Onco-protein Cancer Drug Example)
10:32
How to Identify Hydrogen Bond Interactions in 3D Structures (Antibiotic Resistant Fungal Mutant Protein)
17:21
How to Create a Publication Ready
12:42
Quiz
00:10:00
Hands-on: NGS (Whole Genome Sequencing) Variant Calling for Microbial Genomics
An NGS data analysis course on specifically microbial genomes (haploid in nature). In this course, the student will learn NGS from the very basics and will have proper hands-on understanding of whole-genome variant calling of microbial genomes such as parasites, bacterial or viral species. In this course, we will find both substitutions (snps) and insertions/deletions (indels).
0/7
In-depth Introduction to NGS and Variant Calling
47:13
Haploid vs. Diploid Organisms for Variant Calling
07:26
Whole Genome Sequencing: A Comprehensive Sequencing Approach for Microbial Genomics Surveillance
24:02
Single Nucleotide Polymorphism (SNPs) and Their Biological Significance for Bioinformatics Analysis
31:22
Retrieval of Necessary Data for Variant Calling
02:25
Microbial Variant Calling on (WGS/NGS) Dataset Using Snippy
50:22
How to Interpret a Variant Calling Format (VCF) File
00:00
Introduction to Anaconda and Jupyter-Notebook for Bioinformatics
0/3
Introduction to Anaconda and Jupyter-Notebook for Bioinformatics
22:46
How to Get Started With Jupyter-Notebook for Bioinformatics Analysis
17:14
How to Write & Run Your First Script in Jupyter-Notebook
09:41
Hands-on: Single-Cell RNA-Sequencing Data Analysis Using Python
0/9
Introduction to Single-Cell RNA-seq, Its Pipeline and Analysis
23:34
Gene Expression and Its Significance
21:42
Cellular and Tumor Heterogeneity
09:10
Bulk RNA-sequencing vs. Single-Cell RNA-sequencing
21:50
Single-Cell RNA-seq Technologies (10x Genomics, Smart-Seq, Drop-seq and more)
23:09
Cell Isolation and Cell Lysis Protocols for Single-Cell Genomics
09:53
In-depth Introduction to Single-Cell RNA-sequencing Analysis Pipeline
24:45
Droplet Technologies: 10x Genomics
14:10
Full-Length Transcript Technologies: Smart-Seq2
17:55
Hands-on: NGS (Whole Exome Sequencing) Variant Calling Using Linux
0/8
In-depth Introduction to NGS and Variant Calling
20:12
Fundamentals of Whole Exome Sequencing: A Comprehensive Sequencing Approach
26:16
Haploid vs. Diploid Organisms for Variant Calling
07:26
Ploidy and Its Significance in Disease Research
14:58
A Bioinformatics Approach Towards Germline vs. Somatic Mutations
14:30
Single Nucleotide Polymorphisms: An Introduction to SNPs and Their Types
31:22
Structural Variations: Large Scale Variations in Genomes
08:55
Copy Number Variations: Role of CNVs in Diseases
10:29
Evaluation
0/1
MCQs
01:30:00
All-Access Membership

Exercise Files
An Introduction to National Center for Biotenchnology.pptx
Size: 5.88 MB
An Introduction to National Center for Biotechnology.pdf
Size: 169.08 KB
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