Bio-informatics

Bioinformatics is the field where computer and information technology are used to collect, store, make accessible, analyse, interpret, and disseminate data from biomedical and/or biological research.

Key areas within this field include genomics, transcriptomics, proteomics (including protein modelling, structure, and function), metabolomics, and the integration of data from these areas. Bioinformaticians work in biological and biomedical research at scientific institutions, as well as in companies within the pharmaceutical, biotechnology, food, and plant breeding industries.

National Educational Programme

Body of Knowledge & Skills

Knowledge

Biology

• General Biology: organisms, tissues, evolution
• Cell Biology: cell structure, energy supply, transport, cell-to-cell communication, mitosis, meiosis, gene regulation, signal transduction pathways, metabolic pathways
• Genetics: DNA structure, replication, code, transcription, translation, epigenetics, mutations, SNPs, structural variations, inheritance, population genetics
• Microbiology/Virology: structure, diversity, metabolic strategies, evolution

Chemistry

• General Chemistry: atomic structure, periodic table, molecules, nomenclature, reactions, kinetics
• Biochemistry: building blocks, macromolecules, carbohydrates, lipids, proteins, enzymes, metabolism

Skills

Informatics

• Programming in Python: data structures, control structures, modular approach, GUIs, Biopython, Python-database approach, data types, object-oriented programming
• Programming in Java: object-oriented programming, application of algorithms, inheritance
• Programming in R: scripting, data analysis, statistics, data visualisation
• Web Technology: HTML, CSS, web services
• Databases: relational design, implementation, querying, and programmatic interaction (MySQL)
• Workflow Tools: e.g., Galaxy, Snakemake
• Linux: bash scripting, Regex

Bioinformatics

• Sequencing Technologies: NGS technologies, assembly, mapping, NGS application areas (e.g., de-novo & re-sequencing) exome sequencing
• Algorithmic Aspects of Sequences: alignment, mapping, graphs, scoring matrices
• Sequence Annotation: BLAST and related software
• Gene Expression Analysis: RNA-seq data, Bioconductor
• Homology and Phylogeny
• Practical Use of Bioinformatics Tools: e.g., BLAST, OMIM, Genome Browsers, Genbank, Uniprot, KEGG, MSA tools, topology prediction, PFAM, PROSITE, YASARA, PDBe, Gene Expression Omnibus, FASTQ, mappers & aligners & assemblers

Statistics & Data Analysis

• Sampling: types of data, population and sample, errors, bias, variation, (un)certainty
• Descriptive Statistics: e.g., mean, median, standard deviation, range, interquartile range
• Visualisation: e.g., box plot, histogram, scatter plots, Venn diagram, trees, heatmaps
• (Hypothesis) Testing: e.g., t-test, ANOVA, chi-square, Wilcoxon, non-parametric
• Cluster Analysis: distance measures, hierarchical clustering, k-means clustering
• Regression: Linear, Non-linear, Multivariate, PCA
• Data Mining/Machine Learning: e.g., Decision Trees, Naive Bayes, k-Nearest Neighbour, Neural Networks, SVM

The Body of Knowledge and Skills is a summary of graduates’ basic knowledge and basic skills which has been prepared by the HBO-programmes in consultation with the professional field. These are obtained during the first two years of education.