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Bioinformatics Daily
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Syed Mohammad Lokman
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Basics
Basics Tutorials
About BioinformaticsDaily
Phylogenetics
Projects for Beginners
Sequence Alignment
Short Theory
Statistical Method
Structural Bioinformatics
Workflow Management
Biological-databases
Statistics
Omics
Omics Tutorials
High-throughput Technology
Systems & Networks
Python
BioConductor
R
NGS
CADD
CADD Tutorials
Genetic Variation
Drug Informatics
ML
ML Tutorials
ML in Bioinformatics
Programming
Programming Tutorials
Cloud
Python
R
Courses
Interactive Tools
Basics
Omics
CADD
ML
Programming
Courses
Interactive Tools
Bioinformatics 101
biological-databases
1. What is a database?
2. Biological Database
3. Database Search & Retrieval
4. API access to Databases
5. Major Biological Databases
6. Data Submission & Curation
statistics
Basic Statistics in R
Statistical Method
1. Statistics
2. Estimates
3. Probability & Distribution
4. Hypothesis Test
5. Statistical Analysis
Sequence Alignment
1. Pairwise Sequence Alignment
2. Multiple Sequence Alignment
3. BLAST and its variants
Phylogenetics
1. Molecular evolution concepts
2. Phylogenetic tree construction
3. Ancestral reconstruction
4. Molecular clock estimation
Structural Bioinformatics
1. Structural Bioinformatics
2. Structural Prediction
AlphaFold2 and ColabFold: Predicting 3D Protein Structures Using Free Cloud GPUs
13. Protein structure hierarchy
15. Basic structure prediction methods
29. Mass spectrometry data analysis
30. Protein identification and quantification
PyMOL vs Chimera vs ChimeraX: Full Feature Comparison & Guide (2026)
Workflow Management
1. Workflow Management
2. Galaxy
3. KNIME
4. LINCS tools
5. Anduril
6. NextFlow
Short Theory
Protein
2. Central Dogma of Molecular Biology
3. Gene Regulation and Expression
4. DNA, RNA, and Protein Structure
9. Genome Structure and Organization
All About Bioinfo
Projects for Beginners
Codon Usage Analysis
About BioinformaticsDaily
MD Simulation Services
Services
Terms and Conditions
Privacy Policy
Epigenetics & Transcription Regulation
Omics
07. High-throughput Technology
Database
1. Navigating NCBI Databases
10. Systems & Networks
Systems & Networks
31. Metabolic pathway analysis
32. Integration of proteomics and metabolomics data
37. Biological network representations
38. Network analysis and visualization
12. Python
Data handling using Python
15. BioConductor
Differential gene expression analysis
25. RNA-Seq data analysis
28. Single-cell RNA-Seq analysis
67. Bioconductor
68. biomaRt in R
69. SummarizedExperiment in R
70. ExpressionSet in Bioconductor
ExpressionSet vs SummarizedExperiment vs GRanges: Bioconductor Data Structures
2. Downloading Data from Gene Expression Omnibus (GEO) using GEOquery
2. R
Basics of R and R Studio
NGS
10. Gene Prediction and Annotation
11 Comparative genomics
12. Next-generation sequencing technologies
22. Read mapping and alignment
23. Variant calling and annotation
24. Genome assembly techniques
27. Alternative splicing detection
NGS Data Quality Control: FastQC & Trimmomatic Workflow Guide
Single-Cell RNA-Seq Analysis with Seurat v5 in R: Quality Control, Normalization, Clustering, and Marker Identification
CADD
05. Genetic Variation
Database
Drug Informatics
Drug Informatics
16. Protein-ligand interactions
GROMACS Molecular Dynamics Simulation Protocol: Step-by-Step Protein-Ligand Simulation
Week 8: ML Overview
Week 9: Feature Engineering
Week 10: Model Evaluation
Week 11: Bias & Variance
AI/ML
09. ML in Bioinformatics
ML in Bioinfo
cloud
Week 12: Colab Basics
R in Google Colab (2026)
r
Week 3: R Environment
Week 5: EDA & Vis (Pt 1)
Week 6: EDA & Vis (Pt 2)
python
Python for Bioinformatics: Essential Biopython Recipes for FASTA, GenBank, and BLAST Parsing
BIOL4000L (Summer '26)
Final Capstone (20%)
All Tools Overview
DNA Reverse Complement
Protein Molecular Weight & pI
FASTA Validator & Formatter
AI/ML
1 min read
Welcome to the AI/ML section. Here you will find resources on:
Machine Learning in Bioinformatics
Drug Design using AI
Biomarker Discovery
Deep Learning applications
Continue Learning
ML in Bioinfo
A Short Theory Recap on Protein.
Week 11: The Bias-Variance Trade-off
Master the most important concept in machine learning. Understand overfitting, underfitting, and how to find the sweet spot for your models.