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As you want to get the details of B.Sc Bioinformatics syllabus of Devi Ahilya Vishwavidyalaya, Indore so here it is for you:

Syllabus of B.Sc. (Bioinformatics)
Subject- Bioinformatics (as one subject)

B.Sc. I Year
Semester I
Paper I: Basic of Bioinformatics 85 marks
Practicals 50 marks

Semester II
Paper II: Mathematics I 85 marks
Practicals 50 marks

B.Sc. II Year
Semester III
Paper III: Structural Bioinformatics 85 marks
Practicals 50 marks

Semester IV
Paper IV: Mathematics II 85 marks
Practicals 50 marks

B.Sc. III Year
Semester V
Paper I: Computer graphics, Machine learning and Bioperl 85 marks
Practicals 50 marks

Semester VI
Paper I: Informatics in omics and application 85 marks
Practicals 50 marks

B.Sc. BIOINFORMATICS
B.Sc. Part - I
Semester - I

Paper I –Basic of Bioinformatics
Max. marks-85
Unit I Introduction to bioinformatics and data generation
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.

Unit II Biological Database and its Types
Introduction to data types and Source. Population and sample,
Classification and Presentation of Data. Quality of data, private and public data sources.
General Introduction of Biological Databases;
Nucleic acid databases (NCBI, DDBJ, and EMBL).
Protein databases (Primary, Composite, and Secondary).
Specialized Genome databases: (SGD, TIGR, and ACeDB).
Structure databases (CATH, SCOP, and PDBsum)

Unit III Data storage and retrieval and Interoperability
Flat files, relational, object oriented databases and controlled vocabularies. File Format
(Genbank, DDBJ, FASTA, PDB, SwissProt).
Introduction to Metadata and search; Indices, Boolean, Fuzzy, Neighboring search.
The challenges of data exchange and integration. Ontologies, interchange languages and
standardization efforts.
General Introduction to XML, UMLS, CORBA, PYTHON and OMG/LIFESCIENCE.

Unit IV Sequence Alignments and Visualization
Introduction to Sequences, alignments and Dynamic Programming;
Local alignment and Global alignment (algorithm and example),
Pairwise alignment (BLAST and FASTA Algorithm) and multiple sequence alignment
(Clustal W algorithm).
Methods for presenting large quantities of biological data: sequence viewers (Artemis,
SeqVISTA), 3D structure viewers (Rasmol, SPDBv, Chime, Cn3D, PyMol), Anatomical
visualization.

Unit V Gene Expression and and Representation of patterns and relationship
General introduction to Gene expression in prokaryotes and eukaryotes, transcription factors
binding sites. SNP, EST, STS.
Introduction to Regular Expression, Hierarchies, and Graphical models (including Marcov
chain and Bayes notes).
Genetic variability and connections to clinical data.

B.Sc. BIOINFORMATICS
B.Sc. Part - I
Semester - II

Paper II –Mathematics I
Max. marks-85

Unit I
Sets, Types of Sets, Subsets, Complement of Sets, union and Intersection of Sets, Difference
of Sets, Demorgan’s Law, Cartesian product of Sets.
Basics of Probability, Permutation and Combination.

Unit II
Measure of central tendency and dispersion: Mean, median, mode, range, standard deviation,
Variance

Unit III
Correlation and Regression: Types, Karl-Pearson’s correlation, Spearman’s Rank correlation,
Regression equation and fitting

Unit IV
Probability Distribution: Basics of Binomial, Poisson and Normal distributions and their
application in biology.
Random Variable; Discrete and Continuous Probability Distribution, Probability mass
function, probability Density function, Mathematical Expectation.

Unit V
Matrices, Types of Matrices, Addition of matrices, Subtraction of matrices and Product of
matrices.
Properties of Matrix Multiplication. Transpose of Matrix, Symmetric and Skew-symmetric
Matrices, Inverse of Matrix

B.Sc. Part - II
Semester - III
Paper III –Structural Bioinformatics

Max. marks-85
Unit I
Fundamentals of X-ray diffraction, NMR spectroscopy of macromolecules
Protein Structure: Primary, Secondary, Super Secondary, Domains, Tertiary, Quaternary,
Ramachandran plot.

Unit II
Protein secondary structure classification databases: HSSP, FSSP, CATH, SCOP.
Protein secondary structure prediction methods: GOR, Chou-Fasman, PHD, PSI- PRED,
J-Pred.

Unit III
Protein Tertiary structure prediction methods: Homology Modeling, Fold Recognition, Ab- intio Method.
Protein folding, Molecular Dynamics of Protein, Molecular Docking of Protein, Small
molecule and Nucleotide, Concepts of Force Field

Unit IV
Motif and Domain: Motif databases and analysis tools.
Domain databases (CDD, SMART, ProDom) and Analysis tools.
HMM (Hidden Markov Model): Introduction to HMM, its application in Sequence alignment
and Structure prediction, HMM based Softwares (HMMER and HMMSTR)

Unit V
Structural features of RNA: Primary, Secondary, Tertiary.
Introduction to RNA Secondary structure prediction, Methods for RNA Secondary structure
prediction, Limitation of RNA Secondary structure prediction

B.Sc. Part - II
Semester - IV

Paper IV- Mathematics II
Max. marks-85

Unit I
Law of Indices, trigonometric ratios, Inverse trigonometric functions.
Binomial theorem.

Unit II
Sequences and series AP, GP, HP, Logrithmic and Exponential Series.

Unit III
Basics of Functions and Limits, Elementary Differentiation and Integration
Fourier transform, Laplace transform and other standard transform.

Unit IV
Coordinate geometry: Distance between two points, section formula, Locus of points.
Equation of lines, Circle, Ellipse, Parabola, Hyperbola

Unit V
Vector: Addition, subtraction, dot product, cross product, scalar triple product,
Vector differentiation and vector integration, gradient, divergence, curl of a vector, equation
of normal

B.Sc. Part - III
Semester - V

Paper V- Computer graphics, Machine learning and Bioperl
Max. marks-85

Unit I
Color models: CMY, HSV, RGB, Visualization techniques.
Graphics display devices, Raster and Random scan devices, color CRT monitors, LCD and
LED.
Unit II
Artificial Neural Networks, Genetic algorithm, Bayesian modeling, Monte Carlo Simulation
Method, Markov Models and their application

Unit III
Perl basic: Variables, Perl operations, A Program to store DNA sequence, Concatenating DNA
fragment, Transcription: DNA to RNA, Subroutines, scoping and subroutines, command-line
arguments and arrays passing data to subroutines, modules and libraries of subroutines, fixing
bugs.

Unit IV
Random number generators a program using randomization, a program to simulate DNA
Mutation, generating random DNA, analyzing DNA, Hashes, data structures and algorithms
for biology, the genetic code,

Unit V
Translating DNA into proteins reading DNA from files in FASTA format, reading frames,
Regular expressions, restriction maps and restriction enzymes,
Genbank files, Genbank libraries, separating sequence and annotation parsing, Annotations
indexing, parsing PDB files, parsing BLAST files.

B.Sc. Part - III
Semester - VI

Paper VI- Informatics in omics and application
Max. marks-85
Unit I:
Genomics: Genome Annotation, Genome Assembly, Structural and Functional Genomics.
Comparative Genomics
Microarray: technique, Design, Analysis, Drug target identification.

Unit II:
System biology: Introduction, Associated disciplines, Interactomics (PPI), Fluxomics,
Biomics.
Metagenomics: Introduction, metagenome, shotgun metagenomics (pyrosequencing).
Tool’s in metagnomics, MEGAN, MG- RAST, and SEED.
Application: Gene survey, Enviornmental genomes, Microbial diversity.

Unit III:
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.

Unit IV
Chemoinformatics: Cheminformatics tools for drug discovery.
Chemical Structure Representation (SMILE & SMART).
Chemical databases: CSD, ACD, WDI, ChemBank, hazardous chemical database,
PUBCHEM.

Unit V:
Quantitative Structure Activity Relationship (2D & 3D). Combinatorial libraries & their
design. High throughput screening, virtual screening, Lipinski's rule of five.

Contact Details:
Devi Ahilya Vishwavidyalaya
RNT Marg, Near Central Mall,
Nalanda Campus,
South Tukoganj,
Chhoti Gwaltoli,
Indore,
Madhya Pradesh 452001 ‎
0731 252 1887
India

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