Bioinformatics stands at the crossroads of biology, data science, and technology, playing a vital role in the future of healthcare, drug discovery, and genetic research. The OSHAA 30-Hours Diploma in Bioinformatics provides participants with the essential foundation to understand and apply computational tools for analysing biological data. Whether seeking to enter the field or expand existing knowledge, this course offers a comprehensive introduction to the principles and practical applications of bioinformatics.
The rapid expansion of genomic data has transformed how biological research is conducted. From understanding disease mechanisms to identifying new therapeutic targets, bioinformatics empowers professionals to manage, interpret, and draw insights from complex biological datasets.
This diploma has been designed for those looking to build practical skills in bioinformatics without requiring a background in computer science. Participants will gain experience with databases, sequence alignment, gene expression analysis, and basic programming techniques relevant to biological data.
Spanning 30 guided learning hours, the diploma covers the core topics and tools used in modern bioinformatics. Participants will learn how to access and work with online biological databases, understand sequence formats, use alignment tools, and analyse genetic and protein data. Key areas such as genomics, transcriptomics, and molecular modelling are introduced, with an emphasis on real-world research applications.
The OSHAA Diploma in Bioinformatics provides a strong platform for those aiming to lead or contribute to innovative research and development in health, life sciences, and digital biology.
OSHAA 30-Hours Diploma in Bioinformatics
Study Units
Learning Outcomes
Introduction to Bioinformatics and Its Applications (3 hours)
- Understand the scope and significance of bioinformatics in modern biological research
- Identify key areas of application including genomics, proteomics, and drug discovery
- Explore the interdisciplinary nature of bioinformatics combining biology, computer science, and statistics
- Recognise current trends and future directions in the field
Biological Databases and Sequence Retrieval Techniques (4 hours)
- Navigate major biological databases such as GenBank, EMBL, UniProt, and PDB
- Retrieve and manage DNA, RNA, and protein sequence data
- Understand accession numbers, database identifiers, and data entry formats
- Perform effective searches using tools like BLAST and Entrez
Sequence Formats, Annotations, and Data Standards (6 hours)
- Distinguish between various sequence file formats including FASTA, GenBank, and GFF
- Understand the structure and content of annotated sequence records
- Interpret metadata and biological features associated with sequence entries
- Apply data standards for consistent, accurate, and reproducible data handling
DNA and Protein Sequence Alignment Methods (4 hours)
- Explain the principles of sequence alignment and its biological significance
- Perform pairwise and multiple sequence alignments using tools such as Clustal Omega and BLAST
- Interpret alignment results to identify conserved regions, mutations, and evolutionary relationships
- Evaluate the accuracy and limitations of different alignment algorithms
Gene Expression and Transcriptome Analysis (3 hours)
- Understand gene expression profiling techniques such as microarrays and RNA-seq
- Analyse transcriptomic data to identify expression patterns and biological insights
- Use databases and tools to explore gene regulation and functional annotation
- Interpret expression results in relation to physiological and pathological conditions
Molecular Biology Tools for Computational Analysis (3 hours)
- Utilise tools for restriction mapping, primer design, and codon optimisation
- Apply in silico methods to support molecular cloning and genetic engineering tasks
- Understand how computational tools aid in structural biology and protein modelling
- Integrate laboratory data with bioinformatics analysis
Basics of Programming in Bioinformatics (Python/R) (4 hours)
- Write simple scripts to manipulate and analyse biological data
- Use bioinformatics libraries such as Biopython or Bioconductor for data processing
- Automate common tasks such as sequence parsing and data filtering
- Interpret and debug code for practical bioinformatics workflows
Data Visualisation and Interpretation in Bioinformatics (3 hours)
- Generate visual representations of biological data such as phylogenetic trees, heatmaps, and scatter plots
- Use software tools and packages for effective data visualisation
- Communicate bioinformatics findings through graphical outputs
- Interpret visual data to support biological conclusions and research reporting
Course Benefits: OSHAA 30-Hours Diploma in Bioinformatics
- Provides a solid foundation in the principles and applications of bioinformatics, suitable for both beginners and professionals in life sciences
- Equips participants with practical skills to access, analyse, and interpret biological data using widely adopted bioinformatics tools
- Enhances confidence in working with genetic, genomic, and proteomic data through real-world examples and case studies
- Introduces essential programming techniques using Python or R tailored for biological research
- Improves data management and analysis capabilities for research, diagnostics, or academic projects
- Enables participants to understand and apply sequence alignment, gene expression analysis, and molecular biology tools in computational contexts
- Supports interdisciplinary collaboration across biology, computer science, and healthcare
- Encourages awareness of ethical issues in handling genetic data and contributes to responsible research practice
- Offers a recognised qualification that strengthens career opportunities in biotechnology, bioinformatics, genomics, and biomedical research
- Provides a stepping stone to advanced study or specialisation in computational biology, health informatics, or systems biology
The OSHAA 30-Hours Diploma in Bioinformatics is designed for participants who wish to develop a foundational understanding of computational methods used in biological research. It is particularly suitable for:
- Life science graduates and professionals aiming to expand into data-driven research
- Laboratory technicians and researchers handling genetic or molecular data
- Biotechnology and pharmaceutical staff involved in research and development
- Healthcare professionals and clinicians interested in genomic data interpretation
- Participants pursuing careers in bioinformatics, genomics, or biomedical informatics
- Academics and educators seeking to integrate bioinformatics into their teaching or research
This course is ideal for participants with a background in biology or related fields who want to apply computational tools to solve real-world biological questions and improve their data analysis proficiency.
