Syllabus of B.Sc. (Bioinformatics) · · 2012-02-04Syllabus of B.Sc. (Bioinformatics) Subject-...
Transcript of Syllabus of B.Sc. (Bioinformatics) · · 2012-02-04Syllabus of B.Sc. (Bioinformatics) Subject-...
Syllabus of B.Sc. (Bioinformatics)
Subject- Bioinformatics (as one subject)
B.Sc. I Year
Semester I
Paper I: Mathematics 50 marks
Paper II: Introduction to Bioinformatics I 50 marks
Practicals 50 marks
Semester II
Paper I: Statistics 50 marks
Paper II: Introduction to Bioinformatics II 50 marks
Practicals 50 marks
B.Sc. II Year
Semester III
Paper I: Coordinate Geometry, and Vectors 50 marks
Paper II: Structural Bioinformatics I 50 marks
Practicals 50 marks
Semester IV
Paper I: Matrices and Transforms 50 marks
Paper II: Structural Bioinformatics II 50 marks
Practicals 50 marks
B.Sc. III Year
Semester V
Paper I: Genomics 50 marks
Paper II: Metabolomics 50 marks
Practicals 50 marks
Semester VI
Paper I: Drug Designing and Cheminformatics 50 marks
Paper II: Computer Graphics and Machine Learning 50 marks
Practicals 50 marks
15 Marks 2CCE + 35 Marks End Semester Examination=50 Marks for Each Paper
B.Sc. BIOINFORMATICS
I year
SEMESTER-I
Paper I –Mathematics
Total Allotted Hrs.-35 Max. marks-50
Unit I
Sets, Types of Sets, Subsets, Complement of Sets, nion and Intersection of Sets,
Difference of Sets, Demorgan’s Law, Cartesian product of Sets, Sets of numbers,
Unit II
Significant figures and decimal places.
Law of Indices, trigonometric ratios, Inverse trigonometric functions.
Unit III
Sequences and series AP, GP, HP, Logrithmic and Exponential Series.
Binomial theorem
Unit IV
Basics of Functions and Limits, Elementary Differentiation and Integration
Unit V
Basics of Probability, Permutation and Combination
I year
SEMESTER IPaper II –Introduction to Bioinformatics I
Total Allotted Hrs.-35 Max. marks-50
Unit I Introduction to bioinformatics
• What is bioinformatics and its relation with molecular biology.
• Examples of related tools, databases and software
• Applications of bioinformatics.
Unit II General Introduction of Databases
• Nucleic acid databases (NCBI, DDBJ, EMBL).
• Protein databases (Primary, Composite, Secondary).
• Specialized Genome databases: SGD, TIGR, ACeDB
• Structure databases (CATH, SCOP, PDBsum)
Unit III Representation of patterns and relationship
• Sequences, alignments, regular expression, hierarchies, and graphical
models (including Marcov chain and Bayes notes)
• Genetic variability and connections to clinical data.
Unit IV Data generation
• Generation of large scale molecular biology data (General
introduction of Genome sequencing, Protein sequencing, Gel
electrophoresis, NMR Spectroscopy, X-Ray Diffraction,
Microarray), Quality of data, private and future data sources.
Unit V Data storage and retrieval
• Flat files, relational, object oriented databases and controlled
vocabularies.
• Indices, Boolean, fuzzy, neighboring search
• Introduction to Metadata
Practical Course
1. Measure of central tendencies- Mean, Mode and Median.
2. Explore NCBI.
3. To read GenBank flat file format.
4. To read SWISSPROT entries.
5. Search for a disease and related gene in OMIM using Boolean operator
6. To read PDB entries.
7. To analyze sequence patterns (motif, Domain).
8. Find ORF using ORF finder.
References
1. Bioinformatics- Sequence and Genome analysis- David W. Mount
2. Introduction to Bioinformatics – Terasa K. Attwood
3. Principles of Biostatistics, Authors- Pagano et al.
4. Cell and Molecular Biology – P. K. Gupta5. Bioinformatics, Author- Baxevanis.
6. Mathematics by R. D. Sharma
7. Mathematics By R. S. Aggrawal
I year
SEMESTER-II
Paper I – Statistics
Total Allotted Hrs.-35 Max. marks-50
Unit I
Introduction to datatypes and Source.
Population and sample, Classification and presentation of data
Unit II
Measure of central tendency and dispersion: Mean, median, mode, range,
standard deviation, variance
Unit III
Correlation and Regression: types, Methods of calculation Karl-pearson’s,
Spearman’s Regression equation and fitting
Unit IV
Probability Distribution: Basics of Binomial, Poisson and Normal distributions
and their application in biology
Unit V
Random Variable; Discrete and Continuous Probability Distribution, Probability
mass function, probability Density function, Mathematical Expectation.
I year
SEMESTER-IIPaper II- Introduction to Bioinformatics II
Total Allotted Hrs.-35 Max. marks-50
Unit I Visualization
• Methods for presenting large quantities of biological data: sequence
viewers (Artemis, SeqVISTA), 3D structure viewers (Rasmol,
SPDBv, Chime, Cn3D, PyMol), anatomical visualization
Unit II Sequence Alignments
• Local and Global alignment, pairwise and multiple sequence
alignment (BLAST, Clustal W)
• Introduction to Dynamic Programming
Unit III Interoperability
• The challenges of data exchange and integration
• Ontologies, interchange languages and standardization efforts.
• XML, UMLS, CORBA, PYTHON and OMG/LIFESCIENCE
Unit IV PERL
• Introduction to PERL and its application
• Programming: Program to store a DNA and Protein Sequence,
Concatenating DNA fragments, Transcription: DNA to RNA,
Calculating the reverse complement, Reading protein sequence in
files, array and loops.
Unit V Gene Expression
• Gene expression in prokaryotes and eukaryotes, transcription
factors binding sites.
• SNP, EST, STS
Practical Course
1. Visualize protein molecule using RASMOL
2. Visualize protein molecule using SPDBv
3. To perform sequence similarity search using BLAST.
4. To perform multiple sequence alignment using Clustal W.
5. Perl Programming1
6. Perl programming2
References
1. Bioinformatics, Author- Baxevanis.
2. Principles of Biostatistics, Authors- Pagano et al.
3. Introduction to Biostatistics, Authors- Forthoter and Lec.
4. Beginning Perl for Bioinformatics by James Tisdall
5. Bioinformatics- Sequence and Genome analysis- David W. Mount
6. P. S. Verma and Aggrawal
7. Introduction to Biostatistics, Authors- Forthoter and Lec.
8. Introduction to Bioinformatics Arthur M. Lesk University of Cambridge
9. Fundamental of Mathematics and Statisticas; Kapoor Gupta
10. Fundamental of Statistics; S. C. Gupta
II year
SEMESTER-III
Paper I –Coordinate Geometry, Vectors
Total Allotted Hrs.-35 Max. marks-50
Unit I
Coordinate geometry: Distance between two points, section formula, Locus of
points, equation of lines
Unit II
Circle, Elipse, Parabola, Hyperbola
Unit III
Vector: Addition, subtraction, dots, cross, scalar triple product
Unit IV
Vector differentiation and vector integration
Unit V
Gradient, divergence, curl of a vector, equation of normal
II year
SEMESTER IIIPaper II –Structural Bioinformatics I
Total Allotted Hrs.-35 Max. marks-50
Unit I
Fundamentals of X-ray diffraction
NMR spectroscopy of macromolecules
Unit II
Protein Structure: Primary, Secondary, Super Secondary, Domains, Tertiary,
Quaternary
Ramachandran plot
Unit III
Protein secondary structure classification databases: HSSP, FSSP, CATH, SCOP
Unit IV
Protein secondary structure prediction methods: GOR, Chou-Fasman, PHD, PSI-
PRED, JPred
Unit V
Motif and Domain: Motif databases and analysis tools
Domain databases (CDD, SMART, ProDom) and analysis tools
Structural features of RNA: Primary, Secondary, Tertiary
References
8. Bioinformatics- Sequence and Genome analysis- David W. Mount
9. Introduction to Bioinformatics – Terasa K. Attwood
10. Molecular Modeling- Principles and application- Andrew R. Leach11. Principles of Biochemistry- Lehninger
12. Biochemistry- Stryer
13. Cell and Molecular Biology – P. K. Gupta14. Bioinformatics, Author- Baxevanis.
II year
SEMESTER-IV
Paper I- Matrices, Transforms
Total Allotted Hrs.-35 Max. marks-50
Unit I
Matrices, Types of matrices, Addition of matrices, Substraction of matrices and
Product of matrices, Properties of matrix multiplication.
Unit II
Transpose of matrix, Symmetric and Skew-symmetric matrices, Hermitian and
skew Hermitian matrices, Inverse of matrix
Unit III
Fourier transform, Laplace transform and other standard transform.
Unit IV
Boolean logic, addition, subtraction, multiplication and division using binary,
octal and hexadecimal system.
Unit V
Computer Networking: LAN, WAN, Modem, Optical Vs Electronic Networking,
security of the network, Firewalls, Network Goals, Application Network
II year
SEMESTER-IV
Paper II –Structural Bioinformatics II
Total Allotted Hrs.-35 Max. marks-50
Unit I
Introduction to RNA Secondary structure prediction
Methods for RNA Secondary structure prediction
Limitation of RNA Secondary structure prediction
Unit II
Protein Tertiary structure prediction methods: Homology Modeling, Fold
Recognition, Abintio Method. Comparison between and tertiary structure
Unit III
Molecular Dynamics of Protein
Molecular Docking of Protein, Small molecule and Nucleotide
Unit IV
Protein folding, Protein Engineering, Concepts of Force Field
Unit V
HMM (Hidden Marcov Model): Introduction to HMM, its application in
Sequence alignment and Structure prediction, based Softwares (HMMER and
HMMSTR)
References
1. Bioinformatics- Sequence and Genome analysis- David W. Mount
2. Molecular Modeling- Principles and application- Andrew R. Leach3. Principles of Biochemistry- Lehninger
4. Biochemistry- Stryer
5. Bioinformatics from Genomes to Drugs- Thomas Lengauer
III year
SEMESTER-V
Paper I - Genomics
Total Allotted Hrs.-35 Max. marks-50
Unit I
Genome: Anatomy of Prokaryotic and Eukaryotic Genomes.
Genome Sequencing, Introduction to Genome Analysis
Unit II
Genome Databases: Human Genome database, Mouse Genome database, Plasma
Genome database, E. coli Genome database, Arabidopsis Genome database
Unit III
Gene identification: In prokaryotes and eukaryotes
Genome annotation
Unit IV
Genomics: Fundamentals of Structural, Comparative and Functional Genomics
and it’s applications
Unit V
Proteomics: Fundamentals concepts, Two dimensional electrophoresis, Mass
Spectroscopy
References
1. Bioinformatics- Sequence and Genome analysis- David W. Mount
2. Bioinformatics and Functional Genomics- Jonathan Pevsner
3. Genomes- T. A. Brown
III year
SEMESTER-V
Paper II - Metabolomics
Total Allotted Hrs.-35 Max. marks-50
Unit I
Metabolic Pathways: Glycolysis, Kreb Cycle, oxidative and non oxidative
phosphorylation, cyclic and non-cyclic photophosphorylation, Calvin’s cycle
Unit II
Enzyme chains, multi-enzyme complex, multi functional enzyme, Regulation
enzyme, Feed back control of metabolic pathways.
Unit III
Metabolic Pathway database (KEGG Pathway database), Concept of metabolome
and metabolomics
Unit IV
Biodiversity Informatics: Fundamental Concept, Species diversity.
Datasets in Biodiversity informatics: Tree of life, Species 2000, NBII, ATCC
Unit V
Phylogeny, Introduction to Phlogenetic analysis, Concept of Phylogenetic Tree
References
1. Principles of Biochemistry- Lehninger
2. Biochemistry- Stryer
3. Bioinformatics- Sequence and Genome analysis- David W. Mount
III year
SEMESTER-VI
Paper I: Drug Designing and Cheminformatics
Total Allotted Hrs.-35 Max. marks-50
Unit I
Microarray: Techniques, Design, Analysis, Drug target identification
Unit II
Drug Discovery and Design: Target identification, Target Validation, Lead
Identification, Lead Optimization, Preclinical Pharmacology & Toxicology
Unit III
Cheminformatics: Cheminformatics tools for drug discovery.
Chemical structure representation (SMILE and SMART).
Chemical databases: CSD, ACD, WDI, Chem bank, hazardous chemical database,
PUBCHEM
Unit IV
Quantitative structure activity relationship (QSAR, 2D and 3D-QSAR)
Combinatorial libraries and their design
Unit V
High throughput screening, Virtual screening, Lipinski’s rule of five
References
4. Bioinformatics- Sequence and Genome analysis- David W. Mount
5. Introduction to Bioinformatics – Terasa K. Attwood
6. Molecular Modeling- Principles and application- Andrew R. Leach
7. Structural Bioinformatics – Philip E. Bourne and Helge Weissig8. Introduction to Bioinformatics Arthur M. Lesk University of Cambridge
9. Bioinformatics, Author- Baxevanis.
III year
SEMESTER-VI
Paper II: Computer Graphics and Machine Learning
Total Allotted Hrs.-35 Max. marks-50
Unit I
Graphics display devices, Raster and Random scan devices, color CRT monitors.
Unit II
Color models: CMY, HSV, RGB, Visualization technique.
Unit III
Generation of lines, circle, polygons and color filling using standard functions in
C.
Geometric Transformations: Rotation, scaling, translation (2D & 3D).
Unit IV
Artificial Neural Networks, Genetic algorithm, Bayesian modeling and their
application
Unit V
Monte Carlo Simulation Method, Markov Models, Dynamic Programming and
their application
References
4. Bioinformatics: The Machine Learning Approach, Pierre Baldi and Søren Brunak
5. Genetic Programming On the Programming of Computers by Means of Natural
Selection John R. Koza
6. An Introduction to Genetic Algorithms Mitchell Melanie
7. Neural Network by Siman Haykins
8. Bioinformatics and Functional Genomics- Jonathan Pevsner
9. Computer Graphics by Hern and Backer