NIT Jalandhar Syllabus for VIth Sem Biotechnology
NIT VI Sem BIOTECHNOLOGY Syllabus
DEPARTMENT OF BIOTECHNOLOGY
Detailed syllabus 6th Semester:
BT-302 Bioinformatics [3 1 0 4]
Information search and data retrieval: Biological information resources and retrieval system;
data characteristics and presentation, major databases, data management & analysis, data mining.
Biological Data bases and their management: Introduction to SQL (Sequence Query
Language), Searching of databases similar sequence; The NCBI; Publicly available tools;
Resources at EBI; Resources on the web; Database mining tools.
Pairwise alignment: Pair wise and multiple sequence alignment, Scoring matrices, Secondary
Structure predictions, Fold recognition.
Multiple sequence alignment and Phylogenic analysis: Gene identification methods; data
mining (Genome databases) and phylogenetic analysis; tree evaluation, Predictive methods using
nucleic acids and protein sequences.
Genome analysis and gene mapping: Analysis Tools for Sequence Data Bank, sequence
homology searching using BLAST and FASTA, FASTA and BLAST Algorithms comparison.
Profiles and Hidden Markov Models: Explanation and application of the tools
Gene identification methods: Genomics and Human genome project; Pattern recognition, Gene
prediction methods, Strategy of genome sequencing.
Gene Expression and Microarrays: DNA Microarrays, clustering gene expression profiles,
tools for microarray analysis, application of microarray technology.
Bioinformatics Software: Molecular structure drawing tool (Chemdraw);
VMD/Rasmol/Insight-II; Clustal X1.8; OLIGO; PERL, Molecular modeling/ Docking (CAChe);
Clustal W, oligoprimer. ALSCRIPT, MOLSCRIPT, Rasmol, Phylip, Submitting sequence to
databases, Computational tools for DNA sequence analysis: GCG: The Wisconsin package of
sequence analysis programs; Web-based interfaces for the GCG sequence analysis programs.
1) Brgeron Bryan, “Bioinformatics Computing”, Prentice Hall of India (2003).
2) Rastogi S.C., Mendiratta N., Rastogi P., Bioinformatics, 2nd edition, Prentics Hall (2006).
3) Attwood T K, and Parry- Smith “Introduction to Bioinformatics”, Pearson Education,
4) David W. Mount, Bioinformatics: Sequence and Genome Analysis 2nd Edition, CSHL
5) P. E. Bourne and H. Weissig, Structural Bioinformatics, 2nd Edition, Wiley, 2008.
6) Westhed D R , Parish J H and Twyman R M, “Bioinformatics” ,Viva Books Pvt. Ltd. ,
New Delhi (2003).
7) Jonathan Pevsner, Bioinformatics and Functional Genomics,1st Edition, Wiley-Liss,
BT-304 Bio Process Modeling and Simulation [3 0 2 4]
Simulation: basics, discreet event simulation, conducting a simulation project, building a system
model, model verification and validation, Simulation of batch pharmaceutical manufacturing
Batch process simulation: concept, goals and capabilities.
Software: SuperPro Designer, K-Tops, Aspen
Modeling: basic process operations with SuperPro Designer, chemical reactions, separation
Study of Structured Models: Analysis of various bioprocesses; Model simulation using
MATLAB-SIMULINK and ISIM software packages.
Fundamental laws: continuity equation, energy equation, equation of motion, transport
equation, equation of state, Phase and chemical equilibrium, chemical kinetics.
Examples of Mathematical Models: Modeling of gene regulation (Genetic switches), Modeling
of signal transduction in prokaryotes and eukaryotes, Insilico microorganisms, metabolic flux
Elementary mode analysis: Heat and Mass Transfer Equipment such as Heat exchangers,
evaporators, flash distillation, differential distillation, continuous binary distillation in tray and
packed column, vaporizers, single phase separation adsorption, absorbers and strippers, agitated
vessels, mixing process. Reaction Equipment: Batch reactor, Semi batch reactor, Continuous
stirred tank reactor, Plug flow reactor, Packed column reactor, Bioreactors, Reactors used in
effluent treatments, Fluidized bed reactor.
1. Harrell, C., Ghosh, B., Bowden, R., “Simulation Using Promodel”, McGraw Hill (
Software: ProModel v.6.1 (incl. with the textbook) SuperPro Designer v. 6.0 or higher.
2. Luyben W L, “Process Modeling Simulation and Control for Chemical Engineers”,
international ed. McGraw Hill (1990).
3. Rose L M, “The Application of Mathematical Modeling to Process Development and
Design”, First Ed. Applied Science Publisher Limited. London (1974).
4. Bequette, “Process Dynamics- Modeling, Analysis and Simulation”, PHI International
5. Rase H F, “Chemical Reactor Design for Process Plants, Vol II: Case Studies and
Design Data”, 1st Ed., John Wiley and Sons, New York (1997)
6. Denn M Morton, “Process Modeling”, First Ed. Longman Publisher (1986).
7. J.R. Leigh, Modeling and Control of fermentation Processes, Peter Peregrinus, London,
BT-306 Bioinformatics Laboratory [0 0 2 1]
1. Various tools related to Bioinformatics, MATLAB Bioinformatics Toolbox
2. Handling of different primary databases and retrieval of primary data of both protein and
nucleotide (Expasy, Entrez) of a particular group or type of an enzyme.
3. Nucleotide sequence of specific organs of specific organism, Analysis and comparison
of nucleotide sequence for specific gene between 2 animals or plants or microbes.
4. Sequence based and structure-based approaches to assignment of gene functions e.g.
sequence comparison, structure analysis (especially active sites, binding sites) and
comparison, pattern identification, etc.
5. Handling of different specialized databases: Pathway, protein folding classification,
Comparison of amino acid sequence of specific protein between different animals or
plants or microbes.
6. Different approaches of Prediction of Genes: Promoters, splice sites, regulatory regions,
application of methods to prokaryotic and eukaryotic genomes and interpretation, gene
7. Different approaches for analysis of ligand-protein and protein- protein interactions.
8. Study to find out potential drug targets for cardio vascular, neurological diseases etc.
using proprietary and public domain software’s (eg. VEGAZZ) (ligand design,
optimization and improvement)
BT-322 Bioprocess Equipment Design and Economics [3 1 0 4]
Design and Analysis of Bioreactors: Chemostat model with cell growth kinetics, Plug flow
reactor for microbial processes; optimization of reactor systems; Multiphase bioreactors, packed
bed with immobilized enzymes or microbial cells; three phase fluidized bed trickling bed reactor;
Component of Fermentor and their design, asceptic operations, RTD studies in bioreactors,
Design and analysis of the above reactor systems; Gas liquid reactors; Reactor with non-ideal
mixing; dispersion model; Tanks in series Model; Bubble column reactors, airlift fermenters etc.
Air and medium sterilization
Mechanical fittings in a bioreactor: vessel, agitation system materials, welds, finish, valves,
piping and valves for biotechnology, cleaning of production plants.
Instrumentation and control of bioprocesses: Physical and chemical sensors for the medium
and gases. Online sensors for cell properties, off-line analytical methods; Biosensors.
Cost Estimation: Capital investments (Fixed and working capital), Types of capital cost
estimates, Cost Indexes, Estimating equipment costs by scaling 6/10 Factor Rule, Purchase
Equipment Installation, Insulation costs, Instrumentation & Control, Piping , Electrical
Installation , Service facilities, Land, Engineering . & Supervision, Start –up expenses. Methods
of Estimating Capital Investment, Estimation of total product cost, Different costs involved in
the total product for a typical Chemical Process plant.
Interest & Investment Costs: Types of interest (simple & compound interest), Nominal &
Effective Rates of interest, Continuous interest, Present worth & discounts, perpetuities,
ccapitalized costs, Interest & Investment costs.
Depreciation: Types of Depreciation, Depletion, Service life, Salvage value, Present value,
Methods of Determining Depreciation.
Optimum Design: General procedure for Determining optimum conditions, Procedure with one
variable, Procedure with Two or More variables, Break even chart for production schedule and
its significance for optimum analysis. Examples of optimum design in a Chemical Process Plant.
1. Shuler M L, Kargi F, “ Bioprocess Engineering- Basic Concepts” , 2nd ed, Prentice Hall
of India Ltd. (2002)
2. Aiba S, Humphrey A E and Millis N F ,“Biochemical Engineering” , Academic Press
3. Stanbury P F and Whitaker A, “Principles of Fermentation Technology,” Pergamon
4. Bailey J E and Ollis D F, “Biochemical Engineering Fundamentals” , McGraw Hill
5. Peters, M S & Timmerhaus K D,“Plant Design and Economics for Chemical
Engineers”, McGraw Hill, New York , 4th Edition (2003)
6. Ulrich , G D,“A Guide to Chemical Engineering Process Design and Economics”, John
BT-324 Protein Engineering [3 1 0 4]
Structure of protein: Primary, secondary, tertiary, quaternary structure, Protein folding, molten
globule structure, characterization of folding pathways. Post translation modification.
Methods to alter primary structure of protein: Random mutation Site directed mutation,
Protein modification: thermal, enzymatic, physical, pressure, solvents, interactions.
Protein raw materials: cereals, legume, oil seeds and pseudo cereals. Muscle protein, Milk
protein, Egg protein, Hemoglobin, Collagen, Keratin. Nutritive role of food proteins.
Sequence and 3Dstructure analysis: Data mining, Ramachandran map, Mechanism of
stabilization of proteins from psychrophiles and thermophiles vis-à-vis those from mesophiles;
Methods to determine structure of proteins: Protein structure determination, X-Ray analysis
of protein, NMR and mass Spectroscopy, Absorption and Fluorescence, Circular Dichroism, FTRaman,
FT-IR, MALDITOF. Protein characterization, 2 D Gel Electrophoresis.
Structure and function prediction: Protein Bimolecular interaction, Drug protein interaction
Thermal properties of proteins and application of DSC. Protein denaturation, aggregation and
gelation. Flow properties of proteins and sensory properties of pertinacious foods.
Protein engineering: definition, application; Features or characterstics of proteins that can be
engineered (definition and Electives methods of study)–affinity and specificity Spectroscopic
properties; Stability to changes in parameters as pH, temperature and amino acid sequence,
aggregation propensities, etc.
Methods of measuring the stability of a protein: Spectroscopic methods to study
physicochemical properties of proteins: far-UV and near-UVCD; Fluorescence; UV absorbance;
Hydrodynamic properties–viscosity, hydrogen-deuterium exchange; Brief introduction to NMR
spectroscopy – emphasis on parameters that can be measured/obtained from NMR and their
1. Permington S R , Dunn M J,“Proteomics from Protein sequence to function” , Viva Books
Pvt. Ltd., New Delhi
2. Edited by T E Creighton, Protein function. A practical approach. Oxford university press.
3. Cleland and Craik, Protein Engineering, Principles and Practice, Vol 7, Springer Netherlands
4. Mueller and Arndt., Protein engineering protocols, 1st Edition, Humana Press, 2006.
5. Ed. Robertson DE, Noel JP, Protein Engineering Methods in Enzymology, 388, Elsevier
Academic Press, 2004.
6. J Kyte, Structure in protein chemistry, 2nd Edition, Garland publishers, 2006.
7. Walsh G, “Proteins Biochemistry and Biotechnology” John Wiley and sons (2003).
BT-326 Computational Biology and Drug Design [3 1 0 4]
Databases: Primary and Secondary Databases; GenBank, EMBL, DDBJ, Swissplot, MIPS, PIR,
TIGR, Hovergen, TAIR, PlasmoDB, ECDC, Protein and Nucleic Acid Sequences.
Search Algorithm: Scoring Matrices and their use; Computational complexities; Analysis of
Merits and demerits; Sequence pattern; Pattern database; PROSITE, PRINTS, Markov chains
and Markov models; Viterbi algorithm; Baum-Welch algorithm; FASTA and Blast Algorithm;
Needleman-Wusch & Smith-Waterman algorithms.
Structure and Analysis: Representation of molecular structures; External and internal coordinates;
Concept of free energy of molecules; Introduction to various force fields; Molecular
energy minimization techniques; Monte Carlo Molecular Dynamics simulation.
Experimental Methods: Molecular structure Determination, Principle of X-ray crystallography
and NMR spectroscopy; 2D Protein Data bank and Nucleic Acid Data bank; Storage and
Dissemination of molecular structure.
Modeling: Homology modeling; Threading; Structure prediction; Structure-structure
comparison of macromolecules; Simulated ducking; Drug design; 2D and 3D QASR; Ligand
1. David W.Mount.Bioinformatics: Sequence and Genome Analysis 2 nd Edition,CSH
2. A. Baxevanis and F.B.F Ouellette,Bioinformatics: a practical guide to the analysis of
genes and proteins, 2nd Edition,John Wiley, 2001.
3. Jonathan Prevsner.Bioinformatics and Functional Genomics, 1st Edition, Wiley-
4. C.Branden and J.Tooze,Introduction to Protein Structure, 2nd Edition,Garland
BT-328 Biostatistics [3 1 0 4]
Applications of statistics in biological sciences and genetics: Descriptive statistics; Mean;
Variance; Standard deviation and coefficient of variation (CV); Comparison of two CVs;
Probability: axiomatic definition; Addition theorem; Conditional probability; Bayes theorem;
Random variable; Mathematical expectation; Theoretical distributions — Binomial, Poisson,
Normal, Standard normal and Exponential distributions; Sampling- parameter, statistic and
standard error; Census – sampling methods; Probability and non-probability sampling; Purposive
sampling; Simple random• sampling;, Stratified sampling.
Testing of hypothesis: Null and alternative hypothesis; Type I and type II errors; Level of
,significance; Large sample tests; Test of significance of single and two sample means; Testing
of single and two proportions – Small sample tests: F-test — testing of single mean; Testing of
two sample means using independent t test, paired t test; Chi square test: Test for goodness of fit
– association of attributes — testing linkage — segregation ratio.
Correlation: Pearson’s correlation coefficient and Spearman’s rank correlation; Partial and
multiple correlation — regression analysis; Sample linear and non linear regression; Multiple
Analysis of variance: definition — assumptions — model; One way analysis of variance with
equal and unequal replications; Two way analysis of variance; Non parametric tests — sign test
— Mann Whitney ‘U’ test — Kruskal Wallis test.
1. Jerrold H. Zar, Biostatistical Analysis, 4th Edition, Pearson Education, 1999.
2. Wayne W. Daniel, Biostatistics, 7th Edition, Wiley India, 2005
3. P.S.S. Sundar Rao, P.H.Richard, J.Richard, An introduction to Biostatistics, Prentice Hall of
India (P) Ltd., New Delhi, 2003.
4. Rangaswamy, R, A text book of Agricultural Statistics, New Age International (P) Ltd., 2000.
5. Panse V.G.Panse, Sukhatme P.V, Statistical methods for Agricultural Workers, ICAR
Publications, New Delhi, 2000