COURSE UNIT TITLE

: BIOINFORMATICS IN CANCER RESEARCH

DEGREE PROGRAMMES

Description of Individual Course Units

Course Unit Code Course Unit Title Type Of Course D U L ECTS
TRO 6017 BIOINFORMATICS IN CANCER RESEARCH ELECTIVE 1 0 0 3

Offered By

Translational Oncology

Level of Course Unit

Third Cycle Programmes (Doctorate Degree)

Course Coordinator

PROFESSOR DOCTOR YASEMIN BAŞBINAR

Offered to

Basic Oncology
Adeloscent and Young Adult Oncology PhD
Basic Oncology
Translational Oncology
Translational Oncology

Course Objective

provide knowledge about to bioinformatics tools and techniques.
How do I know that can take advantage of bioinformatics technologies, data banks, and to connect them to know this area is to provide assessments of bioinformatics.

Learning Outcomes of the Course Unit

1   Knowledgeable about bioinformatics.
2   Acquire knowledge of bioinformatics methods in cancer research
3   Be able to know biological sequences, sequence searching and alignment
4   Be able to know the structure and domain databases
5   A knowledge of the pathway and process data bases

Mode of Delivery

Face -to- Face

Prerequisites and Co-requisites

None

Recomended Optional Programme Components

None

Course Contents

Week Subject Description
1 What is Bioinformatics
2 Biological sequences: central dogma, nucleotide sequencing methods (Sanger dideoxy method, chromosome walking, automated sequencing), sequence types (e.g., gene, transcript, EST), protein sequencing methods (Edman degradation, mass spectrometry)
3 Sequence databases: Database types (nucleotide vs. amino acid, curated vs. uncurated) Genbank, NCBI Entrez, Refseq, Swissp
4 Sequence searching and alignment: alignment models and cost functions, global/semi-global/local alignment, protein similarity matrices (PAM and BLOSUM), exact alignment algorithms, BLAST algorithm, genome-scale alignment, alignment statistics, multiple alignments+phylogenetics
5 The NCBI BLAST Tools: nucleotide-nucleotide, protein-protein, and nucleotide-protein BLAST variants; multiple alignment with PSI-BLAST and CLUSTALW
6 Protein structure and domains: the structural hierarchy (primary, secondary, super-secondary, tertiary, and quarternary structures), methods of structure determination (X-ray, NMR, prediction), structure searching and alignment, protein domains
7 Structure and Domain Databases: Protein Data Bank (PDB) and associated viewers, Structural Classification of Proteins (SCOP), structure and domain databases (Pfam, Interpro, ProDom), finding structures and domains from sequence, resources for structure alignment and prediction
8 Genome Sequencing and Assembly: Clone-based assembly, shotgun assembly, environmental samples
9 Genome Browsers and Databases: NCBI MapView, UCSC Genome Browsers, some model organism databases (FlyBase, Mouse Genome Informatics, SachDB), (Entrez Genome)
10 Genetic variation and diseases: common genetic variations (RFLPs, SNPs, copy number variations, structural variations), Resequencing and variation typing, mapping (linkage vs. association)
11 Variation databases: dbSNP, PopSet, HapMap, links to phenotype (OMIM, OMIA, phenotypes in model organism databases)
12 expression clustering (hierarchical, k-means), expression statistics (t-test, PAM, SAM)
13 Gene and protein expression: technologies for measuring expression (microarrays, rtPCR, 2D-PAGE, mass spectrometry), Expression databases: Entrez GEO, GENSAT, Swiss 2D-PAGE
14 Networks and Pathways: transcriptional networks, metabolic networks, signaling networks, recent directions in networks and pathways
15 Pathway and Process Databases: transcriptional networks (RegulonDB), metabolic and signaling networks (KEGG, Reactome), Gene Ontology

Recomended or Required Reading

Stephen A. Krawetz, David D. Womble. Introduction to Bioinformatics.Humana Press, New Jersey 2003.
Barnes, M.R. and Gray, I.C., eds., Bioinformatics for Geneticists, first edition. Wiley, 2003.
Baxevanis, A.D. and Ouellette, B.F.F., eds., Bioinformatics: A Practical Guide to the Analysis of Genes and Proteins, third edition. Wiley, 2005.
Baxevanis, A.D., Petsko, G.A., Stein, L.D., and Stormo, G.D., eds., Current Protocols in Bioinformatics. Wiley, 2007.
Kohane, et al. Microarrays for an Integrative Genomics. The MIT Press, 2002.

Planned Learning Activities and Teaching Methods

Theoretical Lectures, the topics in-class activities (presentations and assignments) to consolidate and discussion and homeworks

Assessment Methods

SORTING NUMBER SHORT CODE LONG CODE FORMULA
1 PRF PERFORMANCE
2 FIN FINAL EXAM
3 FCG FINAL COURSE GRADE PRF * 0.40 + FIN*0.60
4 RST RESIT
5 FCGR FINAL COURSE GRADE (RESIT) PRF * 0.40 + FCGR*0.60


*** Resit Exam is Not Administered in Institutions Where Resit is not Applicable.

Further Notes About Assessment Methods

None

Assessment Criteria

Learning outcomes, intermediate and long-answer questions will be evaluated with classical written final exam. Strengthened by homework

Language of Instruction

Turkish

Course Policies and Rules

To be announced.

Contact Details for the Lecturer(s)

Prof Dr Yasemin Başbınar
yasemin.baskin@deu.edu.tr 0 232 4125890/5801

Office Hours

To be announced.

Work Placement(s)

None

Workload Calculation

Activities Number Time (hours) Total Work Load (hours)
Lectures 15 1 15
Preparations before/after weekly lectures 15 4 60
Final 1 1 1
TOTAL WORKLOAD (hours) 76

Contribution of Learning Outcomes to Programme Outcomes

PO/LOPO.1PO.2PO.3PO.4PO.5PO.6PO.7PO.8PO.9PO.10PO.11PO.12
LO.15
LO.25
LO.35
LO.45
LO.55

CONTACT INFORMATION
Dokuz Eylül Üniversitesi Cumhuriyet Bulvarı No: 144 35210 Alsancak / İZMİR
Phone: +90(232) 412 12 12 - Fax: +90 (232) 464 81 35

Copyright 2015 DEÜ. BİD

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