Asterisk * denotes non-core modules

Code                Description Credits

Level I Semester 1

HBB 131 Introduction to Bioinformatics                 12

HBB 135 Molecular and Cell Biology             12

*HBB 138 Analytical and Laboratory Techniques 12

HBB 139 Medicinal Chemistry             12

CS 131 Communication Skills             12

HCSCI 131 Introduction to Computers and 

Computer Applications 12

Level 1 Semester 2

HBB 132 Programming Languages For Bioinformatics             12

HBB 133 Biocomputing             12

*HABB 134 Principles of Genetics and Evolution             12

HABB 136 Microbiology             12

HBB 137 Experimental Design and Data 

Analysis for Biologists 1             12

HBB 140 Principles of Biochemistry             12

Level 2 Semester 1

HBB 231 Molecular Genetics             12

HBB 232 Immunology             12

HBB 243 Mathematical Methods for Bioinformatics             12

TCNP 201 Technopreneurship             12

GS 231 Gender Studies             12

*HBB 236 Introduction to Genomics and Proteomics 12

Level 2 Semester 2

HABB 235 Recombinant DNA Technology 12

HBB 237 Biological Databases and Data Mining 12

HABB 248 Bioethics, Safety, Regulation and IPR 12

*HABB 239 Fermentation Biotechnology             12

HBB241 Molecular Modelling and Drug Design I 12

HBB 242 Introduction to Whole Genome Sequencing 12

Level 3 Semester 1

HBB 330 Work-related Learning/Industrial Attachment I 40

Level 3 Semester 2

HBB 331 Work-related Learning/Industrial Attachment II 80

Level 4 Semester 1

HABB 441 Experimental Design and Data Analysis for Biologists 2 12

HABB 442 Generic Skills for Biologists             12

HBB 443 Molecular Modelling and Drug Design II 12

HBB 461 Biological Databases and Data Mining II 12

HBB 462 Scripting Language and Website Development for Bioinformatics 12

HABB 446 Plant Biotechnology             12

Choose at least ONE from the following electives:

*HABB 445 Environmental Biotechnology 12

*HBB 449 Animal Biotechnology 12

*HABB 444 Gene Structure and Function             12

Level 4 Semester 2

HBB 460 Research Project 36

Choose at least ONE from the following electives:

*HBB 448 Pharmacogenomics & IPR 12

*HABB 447 Industrial Biotechnology             12

SYNOPSES

HBB 131 Introduction to Bioinformatics 

What is bioinformatics and its relation with molecular biology? Examples of related

Tools (FASTA, BLAST, BLAT, RASMOL), databases (GENBANK, Pubmed, PDB) and

Software (RASMOL, Ligand Explorer). Data generation; Generation of large-scale molecular biology data. (Through Genome sequencing, Protein sequencing, Gel electrophoresis, NMR Spectroscopy, X-Ray Diffraction, and microarray). Applications of Bioinformatics.

HBB 132 Programming Languages for Bioinformatics 

Programming basics. Programming in C: Pointers, pointers to functions, macro programming in C, graphs, data structure – linked list, stack, queue, binary trees, threaded binary trees. File and exception handling in C, Programming in Visual Basic: Introduction to Application Development using Visual Basic; Working with Code and Forms. Variables, Procedures and Controlling Program Executor; Standard Controls; Data Access Using Data Control; Connecting to Database using VB. Introduction to JAVA, variables, constants, control structures, input-output, and classes. Jar and Java applets. Introduction to Linux. Introduction to Perl, Perl subroutines and regular Expressions, Perl modules, BioPerl

Introduction Meaning of sequence, sequence similarity, homology, meaning of alignment. Pairwise Sequence Alignment Different scoring models, Substitution matrices (PAM and BLOSUM), Pairwise Alignment: Concept of Global and Local Alignment, Dot matrix method, Dynamic programming (Needleman-Wunsch algorithm, Smith-Waterman algorithm, Choosing of best scoring matrix, gap penalties, Significance of score, EVD, FASTA and BLAST algorithms, Information theory and Shanon Entropy. Multiple Sequence alignment Multiple Sequence Alignment methods (MSA), Scoring of an MSA, Progressive (CLUSTALW and PILEUP), Iterative (Genetic) and Hidden Markov Model (HMM) methods of MSA, Local MSA (Profile and BLOCK analysis, and Pattern searching, and Expectation Maximization (EM) Algorithm (MEME) and Gibbs Sampler. Structural Alignment Tools and Protein Tertiary Structure Prediction Structure alignment algorithms & Homology modelling. Markov Chains and HMM Frequent words in DNA, Consensus word analysis, Transaction and emission matrix, Development of training set, CpG island prediction using HMM, Application of HMM in gene finding, and Multiple sequence alignment by HMM method. Phylogenetic Analysis Phylogenetic tree and terminology, different methods of Phylogenetic tree prediction: maximum parsimony, distance (UPGMA, NJ), maximum likelihood methods, bootstrapping, Jacknifing and Phylogenetic analysis by using Bayesian Network. RNA Structure Analysis Terminology of RNA secondary structure, inferring structure by comparative sequence analysis, RNA secondary structure prediction, Nussinov folding algorithm, energy minimization and Zuker folding algorithm.

Genetics: Mitosis and meiosis; Mendelian genetics and the chromosome theory of heredity; mutation and variation; introduction to population genetics. Evolution: population genetics and variation; the concept of, and evidence for evolution; theory of evolution by natural selection; adaptation and adaptive radiation; the nature of species; specific mate recognition systems; isolating mechanisms; speciation.

Microscopy, preparation of specimens for light and electron microscope; Cell theory; 

Prokaryotic and eukaryotic cell structures; Structure and function of different cell 

organelles; Cytoskeleton and cell motility; Interactions between cells and their 

environment; Traffic across membranes; Cell growth and division in the cell cycle; 

Cell differentiation; Cell signalling and Signal transduction; Cancer; Cytoplasmic 

membrane systems, Nature of the Gene and Genome, Molecular anatomy of genes 

and chromosomes.

The module explores microscopic life forms including bacteria, fungi and viruses. Emphasis is on the nature and behaviour of these microorganisms and their importance in manufacturing, agriculture, medical and food industries. Major topics include the history of microbiology, aseptic techniques, nutrient media, classes of microorganisms, microbial growth, procedures for characterization, and microbial energetics. Applications of microbiology in bioremediation, wastewater treatment, bio-fertilizers, animal-microbial symbiosis, and industrial microbiology, and control of microbial diseases. Practicals introduce the students to techniques involved in cultivation, enumeration and purification of microbes.

HABB 137 Experimental Design and Data Analysis for Biologists 1

Introduction: definitions, and uses of statistics (research, business, tourism, agriculture). Probability: multiplication law, addition law, condition probability, tree diagram, law of total probability. Probability distribution: random variables; discrete, continuous. Binomial distributions: normal distributions. Measures of central tendency and dispersion: mean, mode, range, variance, standard deviation, and standard error of the mean. Parametric and non-parametric statistic. Sampling techniques: simple, random, stratified, cluster, systematic. Data types, presentation and summarization techniques: tables, graphs, charts. Regression and correlation: regression parameters, correlation coefficient, coefficient of determ

ination. Simple statistical inference: hypothesis testing, confidence intervals, t-tests and chi-square tests.  Practicals using appropriate statistical packages (e.g. SPSS, GENSTAT, SAS

Laboratory safety practices and procedures. Standard Operating Procedures. Preparation of solutions – understanding of the terms molarity, molecular weight/mass, percentages, and basic units of volumes and weight. Principles, techniques and biological applications of Microscopy; Spectrophotometry; Electrophoresis; Centrifugation; Chromatography; Polymerase Chain Reaction. Basics of writing a scientific report. Practicals will develop competence in preparing stock solutions and accurate dilutions, accurate pipetting and using standard laboratory equipment, techniques in biochemical evaluation, techniques in molecular biology and statistics of instrumental analysis.

HBB139 Medicinal Chemistry 

Pre-Regulatory Medicine and the Drug Approval Process:  Early natural products and synthetic molecules used as drugs, Safety issues in the first drugs, Modern drug discovery and approval process, and Intellectual property issues with drugs. Drug Targets: Structure of proteins, Enzymes, enzymatic activity, and inhibition, Receptors and molecules that modulate their activity. Pharmacokinetics: Drug transport in the blood, Clearance, Volume of distribution, Compartment modelling. Metabolism: Types of metabolic reactions, Genetic and population effects, Prodrugs. Binding, Structure, and Diversity: Intermolecular forces, Drug-target complementarity, Molecular diversity and chemical libraries, Combinatorial chemistry. Lead Discovery: Drug screening, Filtering hits to find leads, Existing drugs and natural products as leads. Lead Optimization: Functional group replacements, Alkyl group replacements, Isosteres and bioisosteres. Peptidomimetic.

Carbohydrates: classification, monosaccharide-structure, stereo isomers and structural isomers, and mutarotation. Oligosaccharides-Disaccharides -structure and importance of sucrose, lactose, maltose, cellobiose. Polysaccharides-structure and importance of homopolysaccharides and heteropolysaccharides. Lipids: definition and classification. Fatty acids: classification, nomenclature, structure and properties of saturated and unsaturated fatty acids. Essential fatty acids. Triacylglycerols: nomenclature, chemical properties and characterization of fats – hydrolysis, saponification value, acid value, rancidity of fats, Reichert-Meissel number. Biological significance of fats. Glycerophospholipids (lecithins, lysolecithins, cephalins. phosphatidylserine, phosphatidyl inositol, plasmalogens), sphingomyelins, glycolipids -cerebrosides, gangliosides. Amino acids: General properties, peptide bond, essential and non-essential amino acids. Protein chemistry: Classification, different levels of protein structure, forces stabilizing protein structure, and protein folding. Nucleic acids: Introduction, chemistry of nucleic acids, double helical structure and properties of DNA, RNA types, structure and functions. Vitamins: Introduction, properties, functions and deficiency diseases of fat soluble and water soluble Vitamins. Enzyme: Classification, Nomenclature, Mechanism of enzyme action, derivation of Michaelis Menten equation, Enzyme inhibition, Factors affecting enzyme activity, Allorteric enzymes, Isoenzymes.

HABB 231 Molecular Genetics

Chemical nature of DNA, epilcation, transcription and RNA processing, and translation. Mutations and genetic basis of cancer. Control of gene expression in prokaryotes, and eukaryotes. Applications of molecular genetics in control of cancer, manufacturing of antibiotics and anti-retroviral drugs. 

Definition of immunology; Cellular participants in immune response; Types of immunity; Cytotoxic T lymphocytes; cytokines; Primary and secondary responses; Antigens and antigen processing; Structure and function of antibodies; Antibody and antigen interactions; Antibody antigen reactions; Theory of vaccination; Basis of cellular immunity; Theory of McFarlane Burnet; Monoclonal vs. polyclonal antibodies; AIDS and HIV- immunological basis.

This module provides a background to recombinant DNA technology. Emphasis will be on techniques used to multiply, control, detect, screen, alter, express and propagate the recombinant DNA in foreign host systems. Topics include the enzymology of recombinant DNA technology, hosts and vectors, microbial genetics, DNA sequencing, DNA amplification by PCR, RNA labelling, site-directed mutagenesis, isolation of DNA/RNA, construction of DNA and cDNA libraries, screening and characterization of recombinant DNA libraries and methods used, in vitro translation, Northern/Southern blot analysis, restriction mapping, DNA cloning and expression and the principles behind the analytical techniques used in recombinant DNA technology.

HBB 236 Introduction to Genomics and Proteomics

Genome Annotation, Genome Assembly, Structural and Functional Genomics.

Comparative Genomics. Metagenomics: Introduction, metagenome, shotgun metagenomics (pyrosequencing). Tools in metagenomics, MEGAN, MG- RAST, and SEED. Application: Gene survey, Enviornmental genomes, Microbial diversity. Microarray: technique, Design, Analysis, Drug target identification. Metabolic pathway database (KEGG pathway database), Concept of metabolome and metabolomics. Drug Discovery and Design: Target identification, Target Validation, Lead Identification, lead optimization, preclinical Pharmacology & Taxology, proteomics and transcriptomics 

Overview of database management- Advantages of database systems, the architecture of database systems, Levels of abstraction, data models- hierarchical network and relational models, and Entity elationships. Relational data models, relational algebra, SQL and commercial RDBMS-ORACLE, Views, Triggers, cursors, exceptions. Data independencies and Normalization-First normal form, second normal form, third normal form, Boyce-Codd normal form, security and integrity constraints. Biological databases: sequence databases, structural databases.

This module will cover alcoholic and non-alcoholic fermentation, industrial fermentation and brewing industry, construction of yeast, genetic systems with greater fermentation efficiency, fermentation design and control as well as downstream processing.  

HABB 248 Bioethics, Safety, Regulation and IPR

The module covers aspects of handling and disposal of hazardous biological and chemical substances of laboratory origin. Bioethics explores controversial issues brought about by advances in biotechnology and medicine. Ethical questions that arise in the relationships among life sciences, biotechnology, medicine, politics, law, and philosophy are addressed. The module mainly focuses on laboratory set-ups to contain possible epidemic situations when working with microbes, GMOs, and biohazards which become the epicentre of biosafety issues.

Structure of proteins: Principles and Anatomy of proteins; Hierarchical organization of protein structure- Primary, Secondary, Super secondary, Tertiary, Quaternary structure, internal coordinates of Proteins: Theory, Derivation and significance of Ramachandran Plot. Structure of Nucleic Acids: DNA and RNA; Base pairing- Watson Crick and Hoogestein; Types of double helices A, B, Z and their geometrical as well as structural features; Types of RNA and geometrical parameters of each and their composition. Molecular Interactions: Protein-Protein interaction, Structural Analysis of domain interactions, Protein-DNA interactions, Types of interactions of DNA with proteins and small molecules. Protein structure prediction: Principles of protein structure prediction, Secondary structure prediction- Chou Fasman and GOR method. Homology Modelling- concepts, basic principles and protocol. Molecular modelling tool: SPDBV, Structure visualization tools such as Rasmol, Cn3D, VMD, MOLMOL, and Chime. Basic concepts in structural bioinformatics.

HBB 242 Introduction to Whole Genome Sequencing 

The purpose of this module is to provide an overview of whole-genome sequencing and next-generation sequencing (NGS) technologies, including their historical, technical and utilization perspectives. Students will also be equipped with essential skills required to analyse next-generation sequencing data and carry out some of the most common types of analysis. Students will be exposed to the current best-practice workflows for Genome Assembling, Variant Calling, Trio Analysis, and Differential Expression Analysis as well as practical biological problems that motivate them.

Introduction to sets, Set operations- union, intersection- complementation- symmetric
difference, power sets (simple problems). Cartesian product- relations- functions, types of
functions (definition and examples only). Matrices: types of matrices, addition and multiplication of matrices, the inverse of matrices, the rank of a matrix, non-singular and singular matrices, elementary transformations, the inverse of elementary transformations, and equivalent matrices. Mathematical logic: propositional calculus, basic logic operations- conjunction, disjunction, negation, conditional and bi-conditional, converse, inverse and contrapositive statements, tautologies, contradiction, equivalence and implications. Integral calculus: a quick review of indefinite integral as anti-derivative, the definite integral, the fundamental theorem of Calculus. Graph theory: definition, terminology, paths and circuits, representation of graphs, path matrix, adjacency matrix; exterior paths and circuits, Hamiltonian paths and circuits, spanning trees, minimum spanning trees. Markov models, Cluster analysis: hierarchical and non-hierarchical methods. Phylogenetic analysis tools: Maximum Likelihood, Parsimony methods.

Introduction: nature and importance of technopreneurship, Differences between

technopreneurship and entrepreneurship; Relationship between technopreneurship and the national economy; Innovation and creativity, Qualities of an entrepreneur. Small business model and financial issues: developing a business model, basics of small business management, risks and stages of funding, sources of funding, financial funding for growth, product valuation, and how to form and register a small business in Zimbabwe. New Product Development (NDP): Opportunity recognition and creation, Sources of opportunity, Screening technology opportunities, Designing your product/service: design thinking; process thinking, strategic thinking; the NPD process: idea generation, idea screening, concept testing, market strategy development, business financial analysis, prototyping, test marketing, commercialization. Developing and Protecting Intellectual Property: Concept of intellectual property, theory behind IP protection, Intellectual Property (IP)-driven vs non-IP driven technopreneurship Trade secrets, Copyrights, Trademarks, Patent and Trademark protection and its significance, Basics of patenting, legislation governing IP in Zimbabwe. Case studies of successful technopreneurs. Project.

This module will empower the students with knowledge and skills that enable them to be gender sensitive in the University, workplace and in all their social interactions. Topics covered include: understanding gender, gender analysis, gender issue in Zimbabwe, redressing gender imbalances, empowerment and strategies for creating gender responsive environment. Students gain insight into accounts of gender studies in Science and Technology

HBB 330 Work-related Learning/Industrial Attachment I

This internship allows the student to gain experience working in a professional environment and to apply knowledge gained in the first two years to acquire professional skills or competencies. Students will be able to expand their professional network, convert academic knowledge into industrial skills, narrow down their potential careers and gain unforgettable life experiences.

The main objectives of the training module are:

i) To help the student put into practice the basic experimental and theoretical skills which were learnt,

ii) To provide exposure to and experience of the industrial environment.

iii) To give the student an insight into the production activities of Zimbabwe’s main industries,

iv) To embark on a research project under the joint supervision of a member of the department and a member of the training institution.

The Industrial attachment will be assessed jointly by the industrial supervisor and the academic supervisor as well as by written reports submitted by the student on the industrial attachment experience.

HBB 331 Work-related Learning/Industrial Attachment II

This internship allows the student to gain experience working in a professional environment and to apply knowledge gained in the first two years to acquire professional skills or competencies. Students will be able to expand their professional network, convert academic knowledge into industrial skills, narrow down their potential careers and gain unforgettable life experiences.

The main objectives of the training module are:

v) To help the student to put into practice the basic experimental and theoretical skills which were learnt,

vi) To provide exposure to and experience of the industrial environment.

vii) To give the student an insight into the production activities of Zimbabwe’s main industries,

viii) To embark on a research project under the joint supervision of a member of the department and a member of the training institution.

The second part of the internship will be assessed jointly by the industrial supervisor and the academic supervisor as well as by written reports submitted by the student on the industrial attachment experience.

Importance of statistics in Biosciences. Hypothesis testing. Principles of Experimental Design. Types of experimental design – completely randomized design, randomized block design, nested designs, factorial design, repeated measures design, Before-After-Control-Impact studies in Ecology. Linear regression and correlation. Analysis of variance – one-way ANOVA, factorial ANOVA, repeated-measures ANOVA, random and fixed effects, checks for the assumptions of ANOVA/general linear models. Data Transformation. Non-parametric. Introduction to multivariate models – MANOVA for analysis of multiple response variables simultaneously; Principal Component and Factor Analysis for data reduction, Discriminate Function Analysis methods for discriminating between groups based on multiple variables. Competent use of at least one Statistical Software programme for data analyses.

Philosophy and ethics of Science. How to communicate effectively as a scientist. Effective reading, searching and evaluating literature. Students will receive training in scientific writing skills. Research and Grant proposal writing. GIS: An introduction to the use of GIS in life sciences, with the aim of providing the tools to access relevant spatial data sources, and construct basic maps of sampling sites etc.

To understand the Modelling of small molecules; to understand the computational chemistry principles and to familiarize the role of computers in the drug-discovery process.

Concepts of Molecular Modelling, Molecular structure and internal energy, Application of molecular graphics, Energy minimization of small molecules, Use of Force Fields and MM

methods, Local and global energy minima. Techniques in MD and Monte Carlo. Simulation for conformational analysis, Ab initio, DFT and semi-empirical methods. Design of ligands, Drug-receptor interactions, Classical SAR/QSAR, Docking of Molecules; Role of computers in chemical research; Structure representation, SMILES; Chemical Databases, 2D and 3D structures, reaction databases, search techniques, similarity searches; Chemo-informatics tools for drug discovery.

Control of gene expression in prokaryotes; Lysis and lysogeny in bacteriophage Lambda, Control of pathways; Mating behaviour in yeast; Control of gene expression in higher eukaryotes- Gene amplification, Gene rearrangement and mobile units, Regulation at the transcriptional level, Post-transcriptional regulation, Processing transcripts, Differential mRNA processing, Changes in chromatin structure and gene regulation.

Microbial diversity and its importance in biotechnology; Molecular methods for estimating the extent of microbial diversity; Environmental processes catalysed by microorganisms; Pollution control by microorganisms; Wastewater biotechnology; Bioremediation; Biomining; Environmental health and ecosystem sustainability e.g. bio-fuel production; Genetically modified organisms and the environment.

Overview of plant biotechnology; Model plants; Plant genomes; Gene structure; Control of gene expression; The ‘omics’ era; Plant breeding and crop improvement; Plant tissue culture; Recombinant DNA technology; Plant transformation systems; Plants as bioreactors; Applications of plant biotechnology; Diseases and pest resistance, Resistance to abiotic factors, Crop modification: society, ethics and regulatory issues.

Use of microorganisms as cell factories – examples of bio-based products on the market: enzyme, bio-ethanol, fine chemicals i.e amino acids, citric acid, vitamins etc; Fermentation; Bioreactor and Bioprocess design; High throughput screening for novel metabolites; Strain improvement; Gene discovery; Protein expression and production; Protein engineering; Use of recombinant microorganisms.

Bioinformatics companies, Genomes, transcriptomes and proteomes – their applications in medicine and agriculture, disease monitoring, and profile for therapeutic molecular targeting. Diagnostic drug discovery and genomics. Pharmacogenomics and its application. SNPs and their applications. Microarray and genome-wide expression analysis: Introduction to basic microarray technology, Bioinformatics in microarrays, Customised microarray design, Image processing and quantification, Normalization and filtering, Exploratory statistical analysis, Public. Microarray data resources. Patenting and data generation from patent literature for commercial benefits. IPR, and bioinformatics. Bioinformatics patents.

Structure of animal cell, history of animal cell culture, cell culture media and reagents, culture of mammalian cells, tissues and organs, primary culture, secondary culture, continuous cell lines, suspension cultures, somatic cell cloning and hybridization, transfection and transformation of cells, commercial-scale production of animal cells, application of animal cell culture for in vitro testing of drugs, testing of toxicity of environmental pollutants in cell culture, application of cell culture technology in production of human and animal viral vaccines and pharmaceutical proteins.

The research project involves an experimental or observational investigation of a fundamental or practical problem in Applied Biosciences Biotechnology or bio-product development. With guidance from an academic supervisor, each student should choose and propose his/her own project theme. Each student is required to submit a proposal, carry out an independent research project or develop a product; submit a final written report, and deliver an oral presentation. 

To understand the biological databases – types and formats and to learn the retrieval, deposition and analysis of sequences and structures from biological databanks.

Data warehousing, data capture, data analysis; Introduction to Nucleic Acid and Protein Data Banks; Nucleic acid sequence data banks: Genbank, EMBL nucleotide sequence data bank. AIDS Virus sequence data bank, rRNA data bank, Protein sequence data banks: NBRF-PIR, SWISSPROT, Signal peptide data bank; Database. Similarity Searches. BLAST, FASTA, PSI-BLAST algorithms; Pairwise sequence alignment -NEEDLEMAN and Wunsch, Smith-Waterman algorithms; Multiple sequence alignments – CLUSTAL, Patterns, motifs and Profiles in sequences. Derivation and searching; Derived Databases of patterns, motifs and

profiles: Prosite, Blocks, Prints-S, Pfam, etc.; Primer Design.

Introduction to Internet and World Wide Web. An overview of scripting languages, with applications towards biological data and sequence analysis. Complexity of DNA problems and their computational implications and applications. Introduction to HTML, DHTML, XML. Accessing different objects of the HTML page, Dynamic page generation, Cascading Style Sheets (CSS). JAVASCRIPT: Document object model, Elements of the document object model, basic principles of JS, object-based programming using JavaScript; data types and structures, array and string handling, function implementations, XML: DTD, XML schemas, XML document structure, retrieving data from database in XML format; various bio-based versions of XML. PHP: PHP beginning to advanced level, data types, array and