Course Content
Bioinformatics Freelancing Training
0/9
In-Depth Introduction to Bioinformatics Freelancing
31:44
In-depth guide on FIVERR
13:51
In-depth guide on Upwork
14:44
What kind of services can you sell as a Bioinformatician?
09:24
What exactly do you need to learn to provide your services?
12:40
How to connect with clients and accept their projects?
14:19
Case Study 1: Mutagenesis of Proteins Using PyMol
09:53
Case Study 2: Scripting for biological analysis
08:11
Case Study 3: Functional Bioinformatics Analysis
01:08:16
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 & Retreieval 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
Molecular Docking
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
Draft LessonBio.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
10:47
Bio.Phylo – Writing Out Phylogenetic Data
04:04
Bio.motifs – MEME Analysis
09:49
R
0/54
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
ggplot2 – Changing Labels and Finalizing Visualization
08:42
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
0/23
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 Microarray Analysis & R
0/5
Introduction to ArrayExpress – Getting Started With MicroArray Analysis
09:56
Introduction to BioConductor – Installating 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
Quality Control & Normalization
0/12
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
Robust Multi-Array Summarization and Background Correction of the Raw MicroArray Data
03:47
Relative Log Expression Analysis and Visualization
08:57
Normalization of Raw Intesnities Values
04:36
Heatmap Visualization of the Normalized Gene Expression Values
11:52
Intensity-based Filtration of Low-Intensity Transcripts
06:19
Filtering out the Genes that are Above Threshold
06:02
Annotating the Probe IDs with Gene Symbols and Names
04:19
Removal of the Probe IDs that Match to Multiple Genes
04:04
Excluding Probe IDs with Multiple Mappings from the ExpressionSet
04:39
Differential Expression Analysis
0/10
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
Applying t-test to Find if Genes are Differentially Expression
06:51
LIMMA – Applying Linear Model on a Single Gene Expression Data
05:34
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
Downstream Functional Enrichment Analysis Using enrichR – Gene Ontology & KEGG Pathways 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
0/3
CTL Epitope Assessment
04:14
HTL Epitopes Prediction and Assesment
06:43
HTL Epitopes Prediction and Assesment
06:43
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
Evaluation
0/1
Exercise
01:30:00
Bioinformatics Freelancing Training
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