Bioinformatics Freelancing Training
Categories: Bioinformatics Programming, In-Depth
About Course
What Will You Learn?
- NCBI
- Sequence Format
- UCSC
- UniProt
- PDB
- ENSEMBL
- InterPro
- Phytozome
- Pairwise Sequence Alignment & Analysis
- Multiple Sequence Alignment & Analysis
- Alignment Format
- Sequence Analysis
- Phylogenetic Analysis
- Phylogenetic Tree Visualization & Analysis
- Secondary Structure Prediction
- Protein Analysis
- Protein Family Database
- Motif & Domain Analysis
- 3D Structure Prediction
- 3D Structure Visualization
- 3D Structure Evaluation
- Molecular Docking
- Docking Complex Evaluation
- Gene Prediction
- PPI Database
- Genomic Tools
- Molecular Dynamics Simulation
- Molecular Dynamics Simulations: GROMACS
- Vaccine Development
- Introduction to Python
- Iterable Objects
- Control Flow
- File Handling
- Functions & Modules
- Error Handling
- Introduction to BioPython
- Sequence Analysis in BioPython
- Sequence Data Parsing
- Sequence Data Extraction
- Alignment Parsing and Analysis
- BLAST Database Searching
- Parsing BLAST results
- Biological Data Retrieval
- Parsing a PDB Structure file
- Phylogenetic Analysis in BioPthon
- R
- Linux
Course Content
Bioinformatics Freelancing Training
-
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
-
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
-
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
-
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
-
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
-
MEGA
21:20 -
iTOL: Creating Publishable Phylogenetic Figures
13:43 -
FigTree
21:27
Secondary Structure Prediction
-
Quick2D
04:33 -
Ali2D
04:09 -
Jpred: Prediction Secondary Structure of the Proteins
04:55 -
HHrepID
05:15 -
DeepCoil
03:23
3D Structure Prediction
-
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
-
UCSF CHIMERA
25:23 -
PyMol
40:49
3D Structure Evaluation
-
WhatCheck
08:40 -
ProCheck
12:41 -
ERRAT
06:44 -
Verify3D
08:35 -
RAMPAGE
03:30 -
SAVES
05:32 -
PROSA
10:05
Molecular Docking
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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
-
PDBsum Docking Complex Evaluation
18:50 -
Pdbepisa Docking Complex Evaluation
23:27 -
SwissADME
15:31
Gene Prediction
-
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
-
STRING: Comprehensive Protein-Protein Interaction Database
13:17
Genomics Tools
-
Gene Structure Display Server 2.0
08:36
Molecular Dynamics Simulation
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
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
-
Target Selection
03:20 -
Removing Duplicates
03:46 -
Screening Non-homologous Proteins
06:42
Immunoinformatics Approach for Epitope Prediction
-
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
-
CTL Epitope Assessment
04:14 -
HTL Epitopes Prediction and Assesment
06:43 -
HTL Epitopes Prediction and Assesment
06:43
Molecular Dynamics and Immune Simulation
-
Molecular Dynamic Simulation
02:14 -
Immune Simulation
02:19 -
In Silico Cloning
02:45
Supplementary 1
-
Codon Optimization
02:35
Supplementary 2
-
Disulfide Engineering
03:03
Supplementary 3
-
Docking of Protein and TLR4
02:18
Introduction to NGS, RNA-Seq Pipeline & GALAXY
-
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
-
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
-
Exercise
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