About Course

🌱💻 Bioinformatics Ka Chilla

Master 40 Biological Data Science Topics

Introduction to the course

Welcome to Bioinformatics Ka Chilla: Master 40 Biological Data Science Topics in 365 Days 🌱💻

This is an intensive course designed for students, professionals, and aspiring bioinformaticians who want to learn how to harness the power of biological data for scientific research and real-world applications.

In this one-year course, we’ll dive into the world of bioinformatics, data science, and computational biology — making complex biological data easy to understand and apply for researchers, lecturers, professors, healthcare professionals, and biology students in Pakistan.

What Will You Learn?

Basic to Advanced Bioinformatics

Introduction to biological data, databases, and tools used in bioinformatics.

Data Science Concepts for Life Scientists

Learn about machine learning, statistics, and data mining as applied to biology.

Practical Skills

Hands-on experience with real-world datasets (genomics, pangenomics, metagenomics, ribosome profiling, proteomics, metabolomics etc.).

Data Visualization for Biology

Learn to present biological data through charts, graphs, and dashboards.

Ethical, Legal, and Social Implications of Biomedical Data

Understand the ethical considerations and challenges in data usage.

Develop Your Own Bioinformatics Tools

Develop your own bioinformatics tools and host them for public use.

40 Topics Covered

Introduction to Bioinformatics for Beginners
Command Line Interface and Programming, Linux/Unix, Bash, Python, R
Basic Bioinformatics Tools and Databases
Data Science Concepts for Life Scientists
Using Publicly Available Data for Bioinformatics
Data Visualization for Biological Research
Ethical, Legal, and Social Implications of Biomedical Data
Introduction to the European Nucleotide Archive (ENA)
Methods and Resources for Omics Studies
Exploring the European Genome-phenome Archive (EGA)
A Guide to Bioinformatics Resources
A Journey Through Bioinformatics Resources from EMBL-EBI
Biocuration: Understanding the Process and Importance
Biological Data Analysis and Interpretation Methods
Exploring Microbial Ecosystems with Bioinformatics Tools
Biostatistics for Bioinformatics
Genome Bioinformatics: Short-Read to Long-Read Sequencing
Genome Properties and Data Analysis Techniques
Ensembl: Browsing Genomes and Analyzing Data
Introduction to Functional Genomics
Designing Experiments in Functional Genomics
Common Technologies and Data Analysis in Functional Genomics
Submitting Data to Functional Genomics Databases
Understanding Gene Ontology and the QuickGO Project
Introduction to Phylogenetics: A Bioinformatics Approach
Gene and Environmental Exposure Interactions in Health
AlphaFold: Protein Structure Prediction
Bioinformatics Resources for Protein Biology
RNA-Seq Analysis: Techniques and Interpretation
DIY Transcriptomics: Hands-on Bioinformatics
Bioinformatics Approaches to Virus Research
Metagenomics Bioinformatics: Data and Resources
Introduction to Metabolomics in Bioinformatics
Metabolomics Analysis Tools and Techniques
Integrating and Visualizing Multi-Omics Data
Systems Biology: Analyzing Large Datasets
Data-Driven Plant Sciences: Bioinformatics for Agriculture
Genomic Analysis in Livestock Genomics
Proteomics Bioinformatics: Analyzing Protein Data
Single-Cell RNA-Seq Analysis: Using Python, Galaxy, and R

Note: This list will be updated based on the students’ interest and advancement in the field.

Course Teaching Methodology

Mode: Online (with Learning Management System (LMS))
Language: Urdu/Hindi and English
Duration: 1 Year (2025-2026)
Assessments: Monthly quizzes, final project, and live workshops
Certification: Yes, after completing assignments and final project

Bioinformatics Ka Chilla

Basic to Advanced Bioinformatics
Introduction to biological data, databases, and tools used in bioinformatics.
Data Science Concepts for Life Scientists
Learn about machine learning, statistics, and data mining as applied to biology.
Practical Skills
Hands-on experience with real-world datasets (genomics, pangenomics, metagenomics, ribosome profiling, proteomics, metabolomics etc.).
Data Visualization for Biology
Learn to present biological data through charts, graphs, and dashboards.
Ethical, Legal, and Social Implications of Biomedical Data
Understand the ethical considerations and challenges in data usage.
Develop Your Own Bioinformatics Tools
Develop your own bioinformatics tools and host them for public use.

Course Content

00: Resources

Bioinformatics ka Chilla – LMS Access terms and conditions
01:34
Discord Server
01:49
Linux/Unix Cheatsheet
GitHub repo for this course

01: Course Introduction and Registration

02: Know your Instructor

03: What is Bioinformatics?

04: Coding for Bioinformatics

05: Linux-Everything you need to know

06: Zoom Meetings to know everyone

07: File Formats

08: VScode installation

09: Conda environments for Bioinformatics

10: git and gitHub

11: R and RStudio

12: Linux Tool installation and use for Bioinformatics

13: Sequencing Technologies

14: Quality Control of Short Reads

15: DNA and DNA sequencing

16: Genes and Genome

17: Prokaryotic vs. Eukaryotic Genomes as bioinformatician’s perspective

Quizzes-01

18: Marker Gene Analysis | 16S rRNA, 18S rRNA, ITS

19: VScode, Git, GitHub, Markdown

20: Whole Genome Sequencing (WGS) and Genome Assembly workflow | Bacteria/Archaea

Intro to whole genome sequencing and assembly
27:24
Select the paper and bacterial strain for raw sequence RAW reads files
36:36
Extract raw reads from NCBI SRA using grabseqs
22:01
Genome assembly workflow summary so far
04:08
raw reads and meta-data exploration
07:56
Genome assembly example in bandage and IGB for Bacteroides fragilis NCTC9343 from NCBI
28:34
Short reads only genome assembly workflow and plan
18:13
Short reads only assembly quality control of short reads automation
30:48
Short reads genomes assembly guide and limitations with repeat regions
26:34
fastqc quality report reading
20:49
fastp use for read processing and trimming
27:07
SPAdes as short reads assembler
13:36
SPAdes output files for short reads only assembly
04:16
Read spades output files and folders to make sense
13:24
CheckM2 for Genome assembly quality check – Installation to use Complete Guide
54:57
Task to use QUAST for quality check of genomes by yourself
00:59
QUAST for quality evaluation | QUAST Part-1/2
07:51
QUAST expert mode run for genome quality evaluation | QUAST Part-2/2
01:52
QUAST outputs and reading results
13:58
use BUSCO as genome assembly quality check | A-Z
22:55
Types of genome assemblies based on quality metrics
11:20
Tips to improve genome assembly quality
08:28
Genome annotation with Prokka and Bakta
30:43
Installation and analysis script is available on github
01:58
Hybrid Genome Assembly Guide from Raw Reads (short + Long) | A- Z
01:14:08
Results of Unicycler for Hybrid Genome Assembly
17:36
Find plasmids in a genome using plassembler
01:31:24
AMR genes and mobile genetic elements | ABRicate and geNomad
13:42
geNomad to find mobile genetic elements inside a genome | A-Z
29:55
Whole Genome Sequencing and Genome assembly | Summary
01:26
Tips to run script step by step for whole genome assembly
06:31
Genome taxonomy and script
01:25
Genome Taxonomy and database use GTDB-TK | A-Z guide
34:17
Average Nucleotide Identity ANI score and cutoffs for novel species
12:00
Reading Materials
Quiz Whole Genome Sequencing and Assembly
02:49
CompareM2 for genome assembly comparison | Big Pipeline

21: RNAseq/Transcriptomics | for Prokayotes (Bacteria and Archaea)

01-RNAseq or Transcriptomics | Introduction and plan
22:46
02-RNAseq task for students — Must learn from this task
00:30
03-RNAseq sessions and tips for learning
02:16
04-Central dogma and Transcriptomics
02:11
05-Isolate vs. Community of organisms
02:19
06-Cultured vs. Uncultured Organisms
02:20
07-What is a genome?
01:25
08-Key Aspects of a Genome important for Omics
06:46
09-Omics Techniques to learn as a Bioinformatics and Transcriptomics
08:40
10-RNAseq steps, history and tools | RNAseq vs. Riboseq
12:58
11-Task for Single Cell Transcriptomics | What do you think?
01:15
12-Types and Methods of Transcriptomics Analysis
13:19
13-Bulk RNAseq example in detail
06:08
14-Steps involved in RNAseq experiments
01:56
15-Study Design in RNAseq experiment Step-1
09:58
16-Library preparation and sequencing Step-2
01:18
17-Deeper sequencing or More replicates for RNAseq experiment
17:49
18-Read length for sequencing for illumna
02:48
19-Single End vs. Paired End Reads from Illumina
11:44
20-Two important costs for RNAseq Experiments
02:17
21-Sequencing short reads but which Illumna sequencing should we go for
10:28
22-Learning short reads and long reads sequencing Illumina NanoPore PacBio
01:52
23-Data output of sequencing machines | What happens after sequencing?
02:25
24-Understand FASTQ file and Quality Score (phred score)
06:16
25-FASTA file format vs. FASTQ
01:25
26-Important file formats in OMICS | Genomics and other OMICS
04:46
27-RNAseq workflow for Bioinformatics
06:24
28-RNAseq pipelines for Transcriptomics analysis
11:22
29-READemption RNAseq pipeline installation step by step guide
17:16
30-Complete RNAseq Analysis A-to-Z Project for Salmonella sp.
21:59
31-Task for RNAseq analysis for Students
01:45
32-Handling errors for installations and run for READemption
08:27
33-Methods to prevent errors for READemption
08:35
34-READemption scripts are online on github
03:19
35-Read count & Normalization for RNAseq
16:15
36-RPKM FPKM TPM and Log2FoldChange in RNAseq
14:25
37-READemption Output and results of RNAseq for interpretation
22:57
38-DESeq output files reading and understanding
10:04
39-Save your data first and then work on it
02:15
40-READemption use for future analysis
01:40
41-RNAseq analysis on a publication data for Archaea
07:01
42-Complete RNAseq run for a Published dataset with Reademption | Started the Analysis
23:54
43-Task for Students
01:20
44-Pipeline successfully worked for the analysis
02:12
45-Paper Output to read and link with Paper Outputs of RNAseq analysis
19:20
46-IGB to read coverage files for each RNAseq outputs
15:23
47-Docker with DockerHub for any bioinformatics tool
14:13
48-Docker uninstallation issue and bugs
06:11
49-Google Antigravity for Bioinformaticians and RNAseq + Docker
09:26
50-Install Docker for Bioinformatics Tools
14:21
51-Use docker for RNAseq analysis with READemption
15:59
52-Five step guide for Docker containers use for RNAseq analysis
04:45
53-RNAseq analysis for Paired-end reads with three conditions
04:07
54-RNAseq analysis for this project and paper with samples and paired-end reads
05:35
55-genome fasta and gff files for the sample Organisms
02:58
56-Download raw reads for the sample paper for paired end reads
10:19
57-Method No. 1 for RNAseq analysis for Paired-end reads
09:13
58-Method No. 1 for paired-end reads with analysis example
10:38
59-Method No. 2 for RNAseq analysis for Paired-end reads
03:41
60-Method No. 2 for RNAseq analysis for Paired-end reads
09:30
61-RNAseq analysis results for Merged reads Method No. 2
16:05
62-Method No. 3 for RNAseq analysis for Paired-end reads
03:13
63-rRNAs are bad for RNAseq analysis, really?
10:11
64-Publication ready plots for RNAseq analysis outputs from READemption
19:48
65-Task for Students for RNA analysis from a Paper
01:49
66-RNAseq visualization Application for READemption output
50:28
67-Functional Enrichment Analysis Application is ready
21:57
68-Application deployment on streamlit cloud
04:22
69-RNAseq course completed
01:52

22a: Pangenomics

22b: Anvio for Pangenomics

01-Installation of Anvio Pipeline | Anvio for Pangenomics
28:40
02-Steps to perform Pangenome analysis using ANVIO pipeline
14:45
03-Hands on Pangenome Analysis using Anvio with Real Genomes (Part-1/2)
33:03
04-Hands on Pangenome Analysis using Anvio with Real Genomes (Part-2/2)
13:57
05 -Task for students to do Pangenome analysis
00:42
06-Graphical User Interface of ANVIO Pangenome Main Menu
20:44
07-Anvio pangenome BINs and Options
16:42
08-Dendograms and layes in Anvio pangenome
03:17
09-Search function of Anvio and layers in Anvio Pangenome
16:19
10-Legends in Anvio Pangenome
02:16
11-Anvio ANI using pyANI and layers on Pangenome
16:04
12 -Split pangenome parts from main pangenome
05:16
13-Task for Students Anvio Pangenome (Part-1)
04:32
14-Task for Students Anvio Pangenome (Part-2)
00:52
15-Ideas for Pangenome analysis
01:48
16-Important key ideas for Pangenome manuscripts
01:38
17-Pangenomics strategies for complete studies and papers
07:35
18-Step 1: QC before pangenomics
09:11
19-Step 2: Define biological questions clearly for pangenomics
16:58
20-Step 3: Inspect core vs. Accessory vs. Sigleton in pangenome
08:39
21-Step 4: Build a phylogenomics view of pangenome
05:25
22-Step 5: Functional Enrichment Analysis and Annotation
10:28
23-Step 6: Identify clade specific gene clusters in pangenome
02:03
24-Step 7: Explore Genome organization and synteny
03:23
25-Step 8: Check for Mobile Genetic Elements
02:17
26-Step 9: Test pangenome Openness
01:56
27-Step 10: Link Meta data to presence absence matrix of genes
01:45
28-Step 11: Pangenome and ANI score
02:08
29-Step 12: Look for Evidence of Horizontal gene transfer
01:52
30-Step 13, 14, 15: Analysis to results reporting
03:49
31-Step 1 to 15: Summary of Strategies for Pangenome Analysis and Reporting in papers
01:28
32-Practical Guide for Pangenome Analysis in guided steps
02:19
33-Most common mistakes in Pangenome analysis and Strategies to overcome
02:51
34-Task for Students for ANVIO Pangenomics analysis
01:45

23: CAZyme (Carbohydrate Active Enzymes) and PULs (Polysaccharides Utilization Loci) Analysis

24: Secretion Systems in Bacteria (Type-I to Type-VI and Type-IX)

25: CRISPR_Cas, CONJscan and TFFscan systems in Bacterial Genome

26: Amplicon Sequencing (Microbial Ecology)

01-Microbial Ecology and 16s rRNA sequence analysis
14:30
02-16S rRNA gene and Amplicon sequencing analysis using QIIME2
11:23
03-QIIME2 installation in linux with conda giving errors
14:29
04-Installation of QIIME2 using conda and mamba in linux (Working fine)
07:35
05-Task for Students
00:50
06-QIIME2 analysis of real data as an example
09:48
07-Metadata to visualization as QIIME2 artifact
03:28
08-Jupyter notebooks are much better than CLI for QIIME2 analysis
05:30
09-Importing data in QIIME2 to use for analysis
07:48
10-Demultiplexing the data in QIIME2 for amplicon sequencing
08:49
11-Summary of next steps
12:18
12-DADA2 for denoising the samples
29:08
13-Deblur for denoising the samples
16:47
14-Feature Tables summary and representative sequences
10:25
15-Generate Phylogenetic trees after aligning the data
04:46
16-How to view phylogenetic trees in iOTL?
03:14
17-Assignment alert before next lecture
02:51
18-Alpha vs. Beta diversity introduction and need in Amplicon sequencing
33:17
19-Alpha diversity Richness vs. Evenness
04:10
20-Alpha diversity Metrics and Methods
20:07
21-List of Alpha diversity Metrics in Qiime2
01:55
22-Beta diversity methods and metrics
23:09
23-Assignment or task alert
02:05
24-PCA | Principal Component Analysis | Theory
01:12:44
25-PCA | Principal Component Analysis | Case Study in Python
30:39
26-PCA vs. PCoA analysis for Beta-diversity analaysis
23:37
27-Alpha- and Beta-Diversity Core Metrics in one code with optimization with group significances
34:30
28-Assignment Alert | Very important one
00:51
29-Group Significance in Alpha-diversity continuous variables with metadata
04:44
30-PERMANOVA Analysis for Beta-diversity metrics and Meta-data using QIIME2
16:51
31-PCoA plots to view and understand beta diversity using QIIME2
10:59
32-Alpha-rarefaction plots and ASVs with sequencing depth
11:37
33-Taxonomic analysis using Machine Learning
09:10
34-Taxonomy in Amplicon sequencing is an important step
07:41
35-Taxonomy analysis using QIIME2 using classifier training with ML
24:37
36-Taxonomy analysis in QIIME2 using pre-trained SILVA database classifier
10:14
37-Differential Abundance analysis using ANCOM-BC in QIIME2
18:34
38-Next steps in Amplicon Sequencing analysis using QIIME2
02:22
39-Complete A-Z Guided Tutorial of Microbial Ecology Analysis using QIIME2 for Amplicon sequencing
01:01:03
40-Impact of Amplicon sequencing analysis and figure interpretation
19:15
41-16S vs. 18S vs. ITS analysis
17:02
42-Tools for Amplicon sequence analysis
07:16
43-Amplicon sequence analysis from a published article
51:14
44-Download raw data based on publication
19:20
45-Code is available in this lesson
00:15
46-QIIME2 for ITS and Github copilot
16:45
47-Amplicon sequence with ITS completed
03:47

27-Metagenomics A-Z

01-Metagenomics | introduction for beginners
20:56
02-Key Terminologies and Analysis pipeline in Metagenomics
06:10
03-QIIME2 MOSHPIT installation and tools for metagenomics
16:08
04-Assignment for Students
02:28
05-Understanding Metagenomics Made Easy
06:10
06-Metagenomics with MOSHPIT QIIME2 workflow understanding
14:12
07-Raw Reads to Contigs building
10:27
08-Understanding De Bruijn Graphs in the Best Possible Way
22:28
09-Assembly QC
02:07
10-Read Mapping for Metagenomics
03:43
11-Contig Binning to MAGs reconstruction
06:26
12-MAGs QC and MAGs filtering
01:21
13-MAGs Dereplication
03:04
14-Taxonomic Classification
02:00
15-MAGs abundance estimation
02:43
16-Taxa Barplots for Taxa understanding
00:31
17-Summary, common mistakes and Conclusion
07:13
18-Hands on Tutorial for MAGs reconstruction using QIIME2 MOSHPIT
29:09
19-Assignment for Students
00:42
20-Exploring results of MAG reconstruction tutorial and what we actually need for paper
16:25
21-Cocoa Fermentation tutorial understanding and start
04:02
22-COCOA Fermentation Tutorial Understanding of Data and treatments
06:02
23-Download raw data with ENA using SRR list for cocoa fermentation if we need to use RAW reads
09:24
24-Anvio for metagenomics Installation of Anvio Pipeline
28:40
25-Anvio for Metagenomics and shortreads QC
30:06
26-Parallel computation and Anvio for Metagenomics
23:44
27-QC reports of reads
02:14
28-How did I select Samples subset?
01:44
29-Assignment Task for Students
01:22
30-Scripts used till now for Metagenomics and Data Retrieval
31-Megahit Co-Assembly is ready to view and check
10:11
32-QC Reports and MultiQC Reports
04:57
33-Co-assembly QC with Metaquast and graph with Bandage
11:36
34-Metaquast error due to insufficient RAM
04:42
35-QUAST and MetaQUAST worked with fewer references
05:55
36-Optimizing Metaquast: RAM issues killed the process
01:05
37-Metaquast is almost working properly
01:14
38-Metaquast worked fine and now we can see results
01:14
39-Anvio reformat fasta files of contigs before mapping
03:36
40-Reformatting and Indexing done Mapping started with parallel computation
03:39
41-Mapping done and results are ready
01:18
42-sorting and indexing of bam files
02:32
43-sorting completed and results are here
00:45
44-Creating ANVIO compatible database of contigs
01:06
45-Run HMMs on contigs with results
02:40
46-Display contigs stats in iteractive view of Anvio
02:41
47-Profiling of all samples using Anvi’o
08:31
48-Profiling completed and results are here
02:23
49-Merge all profiles using this command
02:33
50-Merging completed but with warnings
01:38
51-What Merging Profiles Means?
00:36
52-Binning and binning tools available for metagenomics and their installation outside Anvio env
03:51
53-Prepare for binning tools outside Anvio
02:55
54-Metabat2 binning algorithm and its outputs
01:34
55-Concoct as a binning algorithm: Script and output
02:11
56-MaxBin2 binning algorithm script and output comparison
03:04
57-Prepare outputs of all three binning algorithms for DAS Tool
08:22
58-DAS Tools to combine outputs of all three script and runtime
05:43
59-DAS tool output and files
02:11
60-DAS Tools output import in Anvio and summary details of final Bins
17:54
61-MAG quality Estimation after binning
07:29
62-All binning tools and MAGs quality estimation summaries
14:41
63-Taxonomic classification of MAGs using Anvio SCG Taxonomy Script is provided
06:10
64-Data visualization of Taxonomy
01:35
65-Data Visualization and publication ready figures from MAGs
08:29
66-Assign Taxonomy to Sample Metadata
03:31
67-Selection of High Quality HQ MAGs
03:36
68-Export fasta files of each MAG based on Quality and binning tool
02:51
69-Run Functional Annotation and Taxonomy for contigs to know who is there and what they are doing
03:42
70-We have learned so far these topics
03:38
71-PC management guide for Bioinformaticians using threads cores and ram with SSD
22:14
72-Anvi’o tutorials are important for everyone for OMICs
03:17
73-Simple read recruitment exercise using Anvio pipeline
44:50
74-Assignment task for students
01:20
75-Further tips and the use of the MetaWRAP pipeline for metagenomics analysis
05:52
76-Further analysis of MAGs are similar to WGS analysis
22:52
77-Limitation of doing metagenomics analysis in Pakistan or abroad
09:45
78-Assignment for students
00:48
79-What are we learning from now on
02:07

28-Viromics

29-Scientific Writing Training with Reference management

30-Scientific Writing 2026

01-What is Scientific Writing? How to Write Papers, Thesis & Articles!
47:28
02-How to actually write a paper: A Basic Plan
13:03
03-What is Plagiarism? and Types of Plagiarism in Scientific Writing
05:27
04-AI detection in Scientific Writing
03:36
05-Why Mentorship is Crucial in Scientific Writing
06:53
06-What are keywords?
02:29
07-Student Tasks: Designing Keywords
00:30
08-Resources to Learn Scientific Writing from Scratch
02:42
09-Importance of Scientific Writing
22:04
10-Join Our Scientific Community for Collaborative Writing
03:41
11-AI Detection and Plagiarism Things You Need to Know
04:19
12-How to find a research gap?
34:52
13-Six types of research gap in scientific writing
00:44
14-Read 5 to 10 to find research gap
06:58
15-Speed up finding research gaps in a scientific way
07:25
16-Plan your time for review paper
07:05
17-Future outlook for Scientific Writing Series
08:00
18-Reading 5 to 10 review articles and finding the research gap to build a database
03:04
19-Finding a research gap for your research paper and where to publish papers
03:07
20-Review articles are old how to find which is nice topic of research
01:55
21-Professor kehta hy maza nahi aya gap find ka k layen dobara
01:58
22-Research Gap to Research Questions formulation for research
13:11
23-Research Questions from a Microbiological Perspective
05:06
24-Research Questions from a Bioinformatics Perspective
11:18
25-Defining Keywords from Research Questions
15:17
26-Keyword queries for database searching
13:15
27-Scispace and other tools for searching databases
12:14
28-How to write using AI without AI detection?
00:53
29-How to manage your time for focused work
01:57

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About Course

🌱💻 Bioinformatics Ka Chilla

Master 40 Biological Data Science Topics

Introduction to the course

What Will You Learn?

Basic to Advanced Bioinformatics

Data Science Concepts for Life Scientists

Practical Skills

Data Visualization for Biology

Ethical, Legal, and Social Implications of Biomedical Data

Develop Your Own Bioinformatics Tools

40 Topics Covered

Course Teaching Methodology

What Will You Learn?

Course Content

00: Resources

Discord Server

01: Course Introduction and Registration

02: Know your Instructor

03: What is Bioinformatics?

04: Coding for Bioinformatics

05: Linux-Everything you need to know

06: Zoom Meetings to know everyone

Zoom Meeting No. 1

07: File Formats

Important File Formats for Linux | CSV, TSV, TXT, FASTQ, FASTQ.GZ, FASTA, fna, faa Explained

08: VScode installation

VScode installation and other software installation methods in Linux mint

09: Conda environments for Bioinformatics

Conda, Mamba & Python Environments for Bioinformatics and Data Science | Manage Packages Like a Pro

Install Miniconda in Linux Mint | Step-by-Step Guide for Bioinformatics & Data Science

Install Mamba in Linux Mint | Faster Alternative to Conda for Bioinformatics & Data Science

Create Conda Environments in Linux | Comprehensive Miniconda Guide for Bioinformatics & Data Science

10: git and gitHub

Git & GitHub in Linux for Bioinformaticians | Version Control Made Easy

11: R and RStudio

Install R and RStudio in Linux Using Command Line | Complete Guide for Data Science & Bioinformatics

R Programming Crash Course (11 h 55 m) – Learn R with Dr Aammar Tufail | Urdu/Hindi #rwithaammar

12: Linux Tool installation and use for Bioinformatics

Linux tips and updates about software use in bioinformatics

Tools installation and use | grabseqs and sequences download from NCBI

Download raw data from a manuscript from NCBI

Downloading raw data using terminal and other commands

Download completed in terminal with fasq.gz files having less space

Metadata related to fastq files and csv file opening in libre office linux

13: Sequencing Technologies

Seuencing Technologies

14: Quality Control of Short Reads

Quality control of short reads using fastqc and multiqc | understanding number of threads in Linux

15: DNA and DNA sequencing

Important Guide about sequencing technology

Sequencing workflow and fastq files | zipped vs. unzipped files

Bases vs. Base pairs in genome sequencing

16: Genes and Genome

Difference between Genes and Genomes

How big is a genome and how does it looks like?

17: Prokaryotic vs. Eukaryotic Genomes as bioinformatician’s perspective

Prokaryotes or unicellular organisms

Eukaryotes or Multicellular organisms

Prokaryotes vs. Eukaryotes Major differences

Prokaryotic genome structure

How to calculate GC content in a genome?

Eukaryotic genome structure | Exons vs. Introns

Genome Size Comparison Prokaryotes vs. Eukaryotic genomes

Prokaryotic genes vs. Eukaryotic Genes structures

Why should you start learning from prokaryotic genomes? | Bioinformatics

Resources and Databases for Prokaryotic & Eukaryotic Bioinformatics

Tools for Prokaryotic vs. Eukaryotic Bioinformatics analysis

Real Wold Application and Job Market | Prokaryotic vs. Eukaryotic Bioinformatics

Complete Guide with Notes

Quizzes-01

Quizzes for Practice _ Bioinformatics ka chilla

18: Marker Gene Analysis | 16S rRNA, 18S rRNA, ITS

16S rRNA gene and its importance for Microbial Ecology

What is taxonomy?

Levels of Taxonomy for Bacteria | Understanding Classification Theory with Examples

18S rRNA and ITS for community analysis | Metabarcoding | Amplicon sequencing

19: VScode, Git, GitHub, Markdown

Install and use VScode in Linux as editor and IDE with sync from your github

VScode experties | files, folders, interface, and settings

R Programming Crash Course (11 h 55 m) – Learn R with Dr Aammar Tufail | Urdu/Hindi #rwithaammar