P12882
Q9UKX2
P02565
P11055
P13541
P12847
MODULE
OUTLINE
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Module Title
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BIOINFORMATICS
AND SPECIAL TOPICS
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Module Code
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SBIN704
SCIN072
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No. of Credits
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20
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Department
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BMBT
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School
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SMLS
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Pre-requisites Module Code
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NONE
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Co-requisites Module Code
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NONE
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Module Lecturers
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Dr
KLM Moganedi
Dr
TM Matsebatlela
Dr VP Bagla
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Office Address
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3026
Life Science building (Moganedi)
2nd
level Life Science building (Matsebatlela)
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Email address
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Kgabo.Moganedi@ul.ac.za
Thabe.Matsebatlela@ul.ac.za
victor.bagla@ul.ac.za
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Telephone No.
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3630
(Moganedi)
2337
(Matsebatlela)
3855 (Bagla)
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Consultation Time
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10h00
– 14h00 Monday to Friday
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Lecture Periods
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Mondays
– Thursdays
08h00
– 10h00
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Practical facilitator
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Dr
KLM Moganedi
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Office address
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3026
Life Science building
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E-mail address
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Kgabo.Moganedi@ul.ac.za
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Telephone no.
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3630
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Important Dates
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19/09 Test 1-Bioinformatics
18/09 Submission Assignment 1
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Learning Hours
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>3
hours per lecture
>Computer
exercises during own time
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Quarter/Semester
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4th
Quarter/ 2nd Semester
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Module outline evaluated by
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Prof
I Ncube
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Module Structure
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09/09/2013
– 18/10/2013
4 x 180 minutes per week, presented between
7h30 and 12h00
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Assessment Method
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Weighting
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Description
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Exercises
Assignment
Theory
test
Summative
Exam
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Formative assessment 60%
Exercises: 25%,
Test : 35%
Summative assessment 40%
Theory:
70%,
(Bioinformatics – 30%
Phytochemistry - 30%
Phylogeny – 10 %
Comprehension – 30%)
Comprehension 30%,
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Minimum
Formative Assessment mark for exam admission = 40%
Final
mark = 60% Formative Assess Mark
40% Summative Assess Mark
Minimum
Final Assessment mark to Pass = 50%
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MODULE
DESCRIPTION
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The theory component
of this module is presented in contact sessions by the lecturers. The
exercises that complement theory will be performed by students on their own
but guided by written instructions and descriptions from the lecturer. These
will be discussed in class. The emphasis is on collection, storage and
retrieval of biological data and how this information can be used to discern
relatedness between organisms and to determine functions and structures of
genes and proteins. The component of phytochemistry will place emphasis on
phytochemical contents and medicinal value of plants in drug discovery and
quality control of herbal products.
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MODULE CONTENT
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Collection and storage
of sequences; Biological data sources; Biological Databases; Searching and
retrieval of biological data from databases; Sequence Alignment; Prediction
of protein-coding genes; cDNA based approach; Ab initio gene discovery; Gene
identification through comparative analysis; Functional genomics: From gene
sequence to function, mutagenesis as a tool for studying gene function;
Transposon mutagenesis, gene knockout, knock-ins, gene silencing by antisense
RNA and RNAi; Phylogenomics. Type of phytochemicals that are of relevance in
ethnopharmacology, value of their prediction in extracts, approaches of
prediction of actives, their extraction, fractionation, and isolation. It will also deal with problems associated
with in-vitro and in vivo assays in ethnopharmacology.
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MODULE OBJECTIVES
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·
To
introduce the importance of bioinformatics in biological research; source and
storage of biological data.
·
To
acquaint students with how to search and retrieve biological data from
biological databases.
·
To
presents the importance of performing sequence alignments and how they are
carried out.
·
To
describe how protein-coding genes are predicted from nucleotide sequences and
their functions are determined.
·
To
learn how protein structures are predicted.
·
To
present how sequences from different organisms can be compared in order to
learn about their evolution in phylogenomics.
·
Provide
an insight into the medicinal value of plants and how best their medical
active constituents can be harnessed either as extracts, fractions or single
entities for drug discovery
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LEARNING OUTCOMES
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After successfully completing the
module, the student should show the ability to:
·
Explain
how protein and nucleotide sequences are generated, stored and retrieved from
databases
·
Describe
the importance of protein and nucleic acid sequences in homology searches,
inference of the function of the biomolecules and evolutionary relationships
between organisms
·
Demonstrate
the utilization of protein and nucleic acid sequences in homology searches
and inference of evolutionary relationship between organisms
·
Discuss
different approaches of determining protein-coding genes from nucleotide
sequences and their levels of reliability
·
Deduce
gene function from mutagenesis data
·
Have
the ability to analyze and argue research information from a research paper
·
Have
a knowledge of type of phytochemicals contained in plants and their
biological relevance
·
Have
an understanding of the approaches to identify the presence of actives in a
plant
·
Know
the type of solvent to use for extraction of a desired phytochemical of
interest
·
Detect
the presence of phytochemicals in a plant using detection methods and
reagents used for TLC
·
Have
the ability to detect type of compounds associated with a particular
biological activity
·
Demonstrate
the ability to extract, fractionate and isolate plant constituent
·
Have
a knowledge of why in-vivo assays should complement in-vitro assays
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ASSESSMENT CRITERIA
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The students must be able to:
·
Describe
protein and DNA sequencing techniques
·
Differentiate
types of databases according to biological data that is stored
·
Demonstrate
searching and retrieval of biological data from databases
·
Explain
the biological significance of performing sequence alignments
·
Describe
different approaches of determining protein-coding genes from nucleotide
sequences and their levels of reliability
·
Compare
and contrast different approaches of determining the function of a gene
·
Correlate
sequence information and degree of relatedness between organisms
·
Explain
the relevance and describe the applicability of a special topic to the
research niche area in the department
·
Explain
the scientific merit of a selected research paper
Indicate correlation of
the aim and methodology used to the findings of a research paper
·
For
phytochemistry will be as expected from the learning outcomes
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REFERENCE MATERIALS FOR THE MODULE
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These books are available in the
department (BMBT) for student loan:
1. Lesk AM. 2002. Introduction to
Bioinformatics. Oxford University press
2. Gibson G and Muse SV. 2004. A
primer of Genome Science. 2nd ed, Sinauer Associates, Inc
publishers.
3. Xiong J. 2006. Essential
Bioinformatics. Cambridge University Press
4. Felsenstein J. 2004. Inferring
phylogenies. Sinauer Associates, Inc.
5.
Page RDM
and Holmes EC. 1998. Molecular evolution. Blackwell Publishing company
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TENTATIVE LIST OF LECTURE TOPICS
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1.
Generation
of biological data
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2. Collection and storage of biological
data
Biological
Databases
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3.
Searching
and retrieval of biological data from databases
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4.
Sequence
Alignment
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5.
Prediction
of protein-coding genes
o Ab
initio gene discovery
o Gene
identification through comparative analysis
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6.
Functional
genomics
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7.
Phylogenomics
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8. Phytochemistry
and its application in drug discovery and quality control of herbal
preparation
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9. Type
of phytochemicals
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10. How
to predict the chemical types of actives present in a plant
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11. Approaches
to prediction of chemical types of actives present in a plant
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12. Extraction,
fractionation and isolation of plant constituents
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13. Problems
associated with in-vitro and in vivo assays in ethnopharmagology
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14. Value
of predicting the chemical types of actives present in a plant
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15. Comprehension: Research paper
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