Introduction

Bioinformatic Methods I & II is a comprehensive, advanced training course designed to equip learners with computational, statistical, and analytical techniques essential for modern biological data analysis. Bioinformatic Methods I & II Training Course integrates molecular biology, genomics, proteomics, transcriptomics, and systems biology with algorithmic thinking, data science, and high-throughput sequencing technologies. Learners gain hands-on experience with biological databases, sequence analysis, structural bioinformatics, and functional annotation, addressing real-world biological and biomedical challenges.

This course emphasizes practical problem-solving using real biological datasets, preparing participants for careers in research, healthcare, biotechnology, pharmaceutical industries, and data-driven life sciences. Through case studies, tool-based learning, and workflow-oriented modules, learners develop proficiency in next-generation sequencing (NGS) analysis, comparative genomics, protein modeling, and systems-level biological interpretation, aligning with current AI-driven and precision medicine trends.

Programme Curriculum

Bioinformatic Methods I & II Training Course

Introduction

Course Duration

5 days

Course Objectives

Understand core principles of bioinformatics and computational biology
Apply sequence alignment and similarity search algorithms
Analyze genomic and transcriptomic datasets
Interpret functional genomics and gene annotation
Utilize biological databases and data repositories
Perform protein structure prediction and validation
Conduct phylogenetic and evolutionary analysis
Implement NGS data analysis pipelines
Explore proteomics and metabolomics workflows
Integrate systems biology and network analysis
Apply machine learning concepts in bioinformatics
Develop reproducible bioinformatics workflows
Solve real-world biological problems using case studies

Target Audience

Life science and biotechnology students
Bioinformatics and computational biology learners
Research scholars and PhD candidates
Faculty members and academic researchers
Biotech and pharmaceutical professionals
Clinical research and genomics analysts
Data scientists entering life sciences
Healthcare and precision medicine professionals

Course Modules

Module 1: Introduction to Bioinformatics

Biological data types and omics technologies
Bioinformatics workflow and data lifecycle
Key databases
Tools and software ecosystems
Case Study: Genome annotation of E. coli

Module 2: Sequence Analysis & Alignment

DNA, RNA, and protein sequences
Pairwise and multiple sequence alignment
BLAST and FASTA algorithms
Scoring matrices and gap penalties
Case Study: Disease gene identification using BLAST

Module 3: Genomics & Transcriptomics

Genome assembly and annotation
RNA-Seq data analysis
Differential gene expression
Variant calling and SNP analysis
Case Study: Cancer transcriptome profiling

Module 4: Structural Bioinformatics

Protein structure levels
Homology modeling techniques
Structure visualization tools
Protein-ligand interactions
Case Study: Drug target structure prediction

Module 5: Phylogenetics & Evolution

Molecular evolution concepts
Phylogenetic tree construction
Evolutionary models
Comparative genomics
Case Study: Viral strain evolution analysis

Module 6: Proteomics & Metabolomics

Mass spectrometry data analysis
Protein identification and quantification
Post-translational modifications
Metabolic pathway analysis
Case Study: Biomarker discovery in disease

Module 7: Systems Biology & Network Analysis

Biological networks and pathways
Gene regulatory networks
Pathway enrichment analysis
Network visualization tools
Case Study: Signaling pathway disruption in cancer

Module 8: Advanced Bioinformatics & AI Applications

Machine learning in bioinformatics
Big data analytics in life sciences
Cloud and high-performance computing
Reproducible research practices
Case Study: AI-based drug discovery pipeline

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Genomic data analysis Sequence alignment Computational biology Data interpretation

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Oct 19 2026

19 Oct — 23 Oct 2026

💻 Online / Virtual session

Online $1,000