Teaching & Knowledge Sharing
Mentorship, hands-on training, and academic research programs in computational biology & bioinformatics
Programs & Courses
Educational & Research Training Activities
Internship programs, specialized courses, and upcoming training initiatives offered through BioPC
Deadline Alert
20 September 2026
Duration:
4 Months Intensive
Level:
All
Format:
Online / Interactive
Organizer:
BioPC Lab
Cohort
4.0
• 4-Month Research
Track
Bioinformatics Research Internship 4.0
Bioinformatics Research Internship 4.0 is an intensive, multi-disciplinary 4-month advanced research program created to train aspiring computational biologists, graduate scholars, and researchers. Building on the success of its flagship predecessor — the Research Traineeship Program 3.0 (where Md. Mustak Khan served as one of the instructors mentoring over 80+ participants) — the 4.0 curriculum takes participants through modern computational drug design, quantum chemical DFT modeling, immunoinformatics vaccine development, cancer transcriptomics, and publication-ready manuscript writing.
Comprehensive 7-Module Curriculum
Click on any module below to inspect the topics and research tools covered:
01
Module 1 — Introduction to Bioinformatics and Biological Databases
Module 1 — Introduction to Bioinformatics and Biological Databases
- Introduction to bioinformatics: scope and applications in drug discovery
- Biological data types: DNA, RNA, and protein sequences
- Sequence data retrieval and database overview
- Key bioinformatics tools and workflows for molecular analysis
Tools Used:
NCBI
UniProt
PDB
BLAST
Deliverable: Annotated sequence/database report
02
Module 2 — Computer-Aided Drug Design (CADD)
Module 2 — Computer-Aided Drug Design (CADD)
- Drug discovery pipeline and target identification
- Structure-based and ligand-based drug design principles
- Protein structure analysis and chemical representation
- Ligand preparation and chemical structure drawing
- Drug-likeness evaluation and physicochemical profiling
- ADME and toxicity prediction
- Protein structure modeling, AlphaFold prediction, and model validation
- Pharmacophore modeling for lead identification
- Molecular docking and protein–ligand interaction analysis
- Interpretation of docking results
- Molecular dynamics and flexibility analysis of protein–ligand complexes
Tools Used:
AlphaFold
AutoDock Vina
Biovia Discover Studio
AdmetLab 3.0
Protox 3.0
Deliverable: Docking + ADMET report on a candidate compound
03
Module 3 — Network Pharmacology
Module 3 — Network Pharmacology
- Concepts of network and systems pharmacology
- Multitarget drug discovery strategies
- Identification of bioactive compounds from natural sources (IMPPAT 2.0, Dr. Duke's Database)
- Prediction of compound–target interactions and disease-associated targets
- Protein–protein interaction (PPI) network construction and analysis
- Hub target identification using network topology
- Functional enrichment (Gene Ontology, ShinyGO) and pathway (KEGG) analysis
- Construction of drug–target, target–pathway, and integrated drug–target–pathway networks
- Docking validation of key targets
Tools Used:
Venny 2.0
ShinyGO
IMPPAT 2.0
Dr. Duke's DB
GeneCards
STRING
Cytoscape
Swiss Drug Design
Deliverable: Compound-disease-target network diagram + pathway report
04
Module 4 — Density Functional Theory (DFT)
Module 4 — Density Functional Theory (DFT)
- Build and optimize molecular structures
- Perform DFT calculations using Gaussian
- Analyze HOMO-LUMO
- Perform IR, Raman & NMR calculations
- Interpret computational results
- Prepare DFT results for research publications
Tools Used:
Gaussian
GaussView
Avogadro
Deliverable: DFT analysis report with spectral interpretation
05
Module 5 — Vaccine Design
Module 5 — Vaccine Design
- Fundamental concepts of vaccine immunology
- Introduction to vaccines and major vaccine types
- Comprehensive vaccine design workflow
- Target virus identification and selection
- Target protein identification and sequence retrieval
- Physicochemical characterization of target proteins
- T-cell and B-cell epitope prediction
- Epitope screening based on antigenicity, toxicity, allergenicity, conservancy, and sequence homology
- Multi-epitope vaccine sequence construction
- Physicochemical characterization of the designed vaccine
- Secondary and tertiary structure prediction and validation
- Protein–protein molecular docking and interaction analysis
Tools Used:
IEDB
VaxiJen
AllerTOP
ProtParam
AlphaFold
ClusPro
AutoDock Vina
C-ImmSim
Deliverable: Multi-epitope vaccine construct workflow, validation & molecular docking analysis report
06
Module 6 — Cancer Bioinformatics
Module 6 — Cancer Bioinformatics
- Foundations of Cancer Biology
- Transcriptional Expression Profiling
- Proteomic Expression Assessment
- Survival Prognosis Evaluation
- Genetic Alteration and DNA Methylation Profiling
- Tumor Mutational Burden, Microsatellite Instability, and Immune Checkpoint Correlation
- Immune Cell Infiltration Assessment
- Protein–Protein Interaction and Functional Enrichment Mapping
Tools Used:
cBioPortal
KM Plotter
Human Protein Atlas
GEPIA 2
UALCAN
GREIN
STRING
ShinyGO
Deliverable: Multi-omics cancer biomarker profiling, immune infiltration & survival prognosis report
07
Module 7 — Bioinformatics-Based Manuscript Writing
Module 7 — Bioinformatics-Based Manuscript Writing
- Research paper structure & IMRaD
- Literature review & research gap identification
- Scientific & academic writing
- Introduction, Methods, Results & Discussion
- Computational results writing
- Tables, figures & scientific data presentation
- Citation & reference management
- Plagiarism & research ethics
- Journal selection & manuscript formatting
- Cover letter & reviewer response
- Guided manuscript writing project
Tools Used:
Zotero
SciSpace
QuillBot
Grammarly
Turnitin
Mendeley
Deliverable: Draft manuscript section based on internship project
Expected Internship Competencies
- Master end-to-end computational drug design, docking, ADMET, and quantum DFT descriptors
- Construct network pharmacology and reverse vaccinology multi-epitope vaccine workflows
- Extract, process, and interpret cancer transcriptomic profiles from international datasets (TCGA/GEO)
- Formulate, draft, and format publishable manuscripts tailored for high-impact scientific journals
Who Should Apply
Undergraduate Students
(Biochem,
Biotech, Pharmacy)
Graduate Students &
Postgraduate Researchers
Any Life Science Students
& Researchers
Timeline: Feb 2026
– Mar 2026
Level: Intermediate
Course
Enrolled: 30+
Participants Mentored
In Silico Innovation: Computer-Aided Drug Design and Network Pharmacology
A focused intermediate-level training course designed to equip life science and pharmacy students with practical, hands-on computational drug discovery skills. Across 4 intensive modules, participants worked with biological databases, executed ligand-target docking workflows with AutoDock Vina, conducted ADMET pharmacokinetic profiling, and mapped complex plant-phytochemical target interactomes using Cytoscape. Over 30+ students and researchers across Bangladesh completed hands-on research assignments and project presentations.
4 Core Course Modules
Module 1: Intro to CADD &
Biological Databases
Module 2: Ligand- &
Structure-Based Drug Design
Module 3: Network
Pharmacology & Target Mapping
Module 4: ADMET Profiling
& Molecular Visualization
Course Outcomes & Achievements
- 30+ students gained direct hands-on competence in molecular docking using AutoDock Vina and PyRx
- Participants constructed multi-target pharmacology networks in Cytoscape and identified key hub proteins
- Researchers learned systematic ADMET property evaluation and pharmacokinetic filtering for lead candidates
Participant Demographics
Undergraduate &
Graduate Biochemistry Students
Pharmacy & Biotechnology
Researchers
Natural Product &
Phytomedicine Investigators
Participant Feedback
"The course gave me a clear understanding of how computational biology can be applied to real drug discovery problems. I completed my first molecular docking project independently after just 3 modules."
— Payel Chowdhury, Course Participant · BioPC 2026"Instructor Mustak's approach is very hands-on. Every session included a real dataset. I walked away with skills I could apply in my own research immediately."
— Maria Opsora, Course Participant · BioPC 2026
Cohort: Cohort 3.0
Participants: 80+
Researchers Mentored
Role: Program
Instructor
Platform: BioPC Lab
Cohort
3.0
• Flagship Predecessor to
Internship 4.0
Research Traineeship Program 3.0
The Research Traineeship Program 3.0 was an intensive research training initiative and the direct predecessor to the Bioinformatics Research Internship 4.0. Serving as one of the core instructors, Md. Mustak Khan guided over 80+ enrolled life science scholars, pharmacy graduates, and early-career researchers across Bangladesh through specialized practical pipelines in computer-aided drug design, AlphaFold structural modeling, reverse vaccinology, and scientific manuscript development.
Core Training Tracks Mentored
Drug Design Track (AutoDock
Vina & PyRx)
AlphaFold Structure Prediction &
Validation
CAVD & Vaccine Design
Track
ADMET Pharmacokinetics
(AdmetLab 3.0, Protox 3.0)
Publication & Manuscript
Preparation Track
Program Impact & Achievements
- Successfully trained and mentored 80+ aspiring computational researchers and students across Bangladesh
- Equipped learners with independent execution capabilities in molecular docking, protein modeling, and ADMET analysis
- Alumni successfully progressed to advanced research initiatives, thesis defenses, and peer-reviewed journal manuscript drafting
Alumna Feedback
"The hands-on training on AlphaFold structure prediction, AutoDock Vina, and ADMET profiling gave me the exact workflow to screen candidate compounds and interpret binding affinities with complete confidence."
— Mahfuja Akter, Program Alumna · Drug Design Track (Cohort 3.0)